Episode 190

full
Published on:

2nd Feb 2024

Chris Schindler: Hedge Fund Sorcerer Schindler Shares Secrets from his Spellbook

In this episode, Adam Butler and Mike Philbrick of ReSolve Asset Management have

an in-depth conversation with Chris Schindler, a seasoned investment

professional. They delve into a range of topics, from the intricacies of

investing in tech and the dynamics of the credit market, to the complexities of

portfolio construction and the impact of market forces on investment

strategies.

Topics Discussed

•The challenges of investing in tech and the role of analysts in creating

crowding effects

•The importance of understanding the dynamics of the credit market and the

implications of holding credit right through maturity

•The intricacies of portfolio construction, including the importance of

diversifying across strategies, assets, and time

•The impact of market forces on investment strategies and the role of

benchmarking in driving investor behavior

•The evolution of the volatility market and the influence of large players on

market dynamics

•The concept of 'netting' in multi-strategy portfolios and its impact on trading

costs

•The challenges of attribution in multi-strategy portfolios and the importance

of understanding the underlying strategies

•The potential pitfalls of short-term investment strategies and the importance

of a long-term perspective


This episode is a must-listen for anyone interested in gaining a deeper

understanding of the complexities of the investment landscape. Chris Schindler

provides valuable insights into the nuances of portfolio construction, the

dynamics of the credit market, and the impact of market forces on investment

strategies, offering strategies to navigate the ever-evolving financial

landscape.


This is “ReSolve Riffs” – published on YouTube Friday afternoon to debate the most relevant investment topics of the day, hosted by Adam Butler, Mike Philbrick and Rodrigo Gordillo of ReSolve Global* and Richard Laterman of ReSolve Asset Management.

*ReSolve Global refers to ReSolve Asset Management SEZC (Cayman) which is registered with the Commodity Futures Trading Commission as a commodity trading advisor and commodity pool operator. This registration is administered through the National Futures Association (“NFA”). Further, ReSolve Global is a registered person with the Cayman Islands Monetary Authority.

Transcript
Chris Schindler:

Like in 10 years, if you had to build a portfolio and say,

2

:

10 years from now, this is the portfolio

I want, what would it look like?

3

:

And the key part of that statement

is you have no idea what the

4

:

world's gonna look like in 10 years.

5

:

You have no idea if you're gonna

like stocks more than bonds, if

6

:

you're gonna like commodities.

7

:

If you're gonna, you have no active, you

have no possible active view in 10 years.

8

:

And so that's the, and so think

of that as your definition of

9

:

passive, as your definition of beta.

10

:

Build the best portfolio you can that

you'd be happy having in 10 years.

11

:

And then think of active as everything

that you do between now and then.

12

:

Adam Butler: Okay, today everyone

is gonna be very excited to see

13

:

we've got Chris Schindler back in

the hot seat from Castle Field.

14

:

Chris, how you doing today?

15

:

How's Toronto?

16

:

Chris Schindler: not so bad right now,

one or two degrees better than last week

17

:

when it was about minus 10 and snowing.

18

:

So probably not quite as nice

as where you guys are, but,

19

:

Adam Butler: That's possible.

20

:

It's pretty gray here today

too, but no snow on the ground,

21

:

you'll be happy to hear.

22

:

Chris Schindler: Oh yeah.

23

:

Adam Butler: For those who

don't know, we've had Chris on

24

:

two or three times in the past.

25

:

They're always crowd favorites.

26

:

We both, we go broad and deep.

27

:

Chris's background we'll get,

we will obviously give a more

28

:

detailed background or bio for

Chris, worked at one of Canada's.

29

:

Major, public pension plans for, for many

years, ran their quant desk and has spun

30

:

off into his own, uh, quant hedge fund,

primarily trading global futures markets.

31

:

So, we're gonna cover a variety of

topics today related to his past and

32

:

his present and potentially his future.

33

:

And, um, so let's, let's start with what

34

:

Mike Philbrick: let's not, let's

not hide where, where he is at,

35

:

it's Castle Field, is that,

That's the name of the firm, right.

36

:

And, uh, where is there a website?

37

:

Is there, just let's get it

out there at the beginning too.

38

:

Chris Schindler: Uh uh, I mean,

there's a website that has, I believe,

39

:

a phone number and an email address,

and that's about it on it right now.

40

:

So, uh,

41

:

Mike Philbrick: Very, very

42

:

Chris Schindler: very professional.

43

:

Mike Philbrick: Close there.

44

:

I,

45

:

love

46

:

Adam Butler: The scarcity close.

47

:

Mike Philbrick: Yeah.

48

:

Adam Butler: So let's start with

what we're currently facing.

49

:

You know, it's funny because I think

ur first chat was probably in:

50

:

We had this crazy concentrated

tech rally, actually.

51

:

It was kind of like this meme stock,

low grade, low quality tech rally.

52

:

and we're, sort of back in a

way to where we were there.

53

:

We don't have any specs to contend with

at the moment, but it, you know, we're

54

:

back into that, massively concentrated

technology oriented large cap rally that

55

:

we experienced for much of the 2010s,

ertainly the back half of the:

56

:

So I thought it might be

useful to revisit that period.

57

:

You know, I think a, a lot of people

who've only been investing for the

58

:

last 10 or 15 years have only really

experienced an environment where U.S

59

:

and especially U.S, big cap tech.

60

:

Was really the only game in town.

61

:

Do you think we're back in that kind

of environment or do you think there's

62

:

gonna be a lot more opportunities

over the next decade than we

63

:

experienced in the previous decade?

64

:

Chris Schindler: Holy moly.

65

:

You guys come out swinging, eh?

66

:

so, uh, and, and I guess you don't go

back to twenty-tens, you can go wait, you

67

:

can go back to the two-thousands or, you

know, the, the, the Nasdaq bubble when

68

:

you really wanna talk about concentrate?

69

:

I

70

:

Adam Butler: mean, it was,

that was interrupted, right?

71

:

For that

72

:

2000 to 2012

73

:

period, right?

74

:

We had this.

75

:

Chris Schindler: in Canada, I remember

we, um, a huge problem for anyone forced

76

:

to benchmark to, to public markets

where, like a public market index

77

:

where, if you want to hold a Canadian

index, you have to have like 30 or 40%

78

:

of your weight in Nortel, you know,

and, and so, you know, it's, there's

79

:

obviously, a lot to this question,

and, do these environments show up?

80

:

They, yeah.

81

:

Like they obviously do.

82

:

Have we been through one?

83

:

We absolutely have been.

84

:

The future's a bit hard to predict, but.

85

:

But you can kind of point to some features

of tech that make it much easier, I

86

:

think, to explain how it can get so

concentrated and how it can get like what

87

:

looks bubbly at times I guess, as well.

88

:

and part of it I think has to do

with just, it'll be pretty hard

89

:

for someone to just say, I'm gonna

start up a new business and, and

90

:

turn it into a billion dollar show

and, you know, in a couple years.

91

:

But like, obviously with the infinite

leverage of technology, especially,

92

:

you know, online technology and,

and the huge scalability, you know,

93

:

you can create these huge potential

future businesses, uh, almost out of

94

:

like, it feels like out of nothing.

95

:

And, and, and they're so

hard to value and right.

96

:

Part of the problem with the NASDAQ

bubble was, everything looked reasonable.

97

:

Well, I dunno if stuff looked

reasonable or not, but you want, you

98

:

can imagine why this one company, if it

succeeds, could be massively successful

99

:

and could be massively valuable.

100

:

but the challenge was.

101

:

All 10 or 20 of them couldn't be.

102

:

and so you had situations where,

individually it might make some sense

103

:

if you didn't get a, a sense of the

context of the entire, space or sector.

104

:

So that's like, that's

part of the problem.

105

:

And we've seen that over and over

again where it, they, they can't all

106

:

succeed because they're together.

107

:

They're, they're making a bigger claim

on future, economic growth or future

108

:

wealth that that is impossible to exist.

109

:

And so together, like, all these

valuations can't make sense and then

110

:

you gotta figure out like, does the

entire index have to re reset or do

111

:

you have to go after the individuals

and, and figure out, you know, which

112

:

ones will go, which ones won't.

113

:

Because it's, it's so easy looking back

to say, man, these were billion dollar

114

:

companies, but if they're the one in 50

survivors or if you got entire spaces that

115

:

just didn't work and went to zero, it's,

much harder to predict that going forward.

116

:

But, you know, and, and like, I

mean obviously that's the challenge.

117

:

you know, and I guess the other thing is.

118

:

Because a lot of these businesses,

and, and I understand, I'm talking

119

:

about more of the ones that we just

don't know what they're worth yet.

120

:

Because, because so many their cash

flows are, way out in the future.

121

:

They're kind of, well they're,

they're almost like a private

122

:

equity firm that's marked to model.

123

:

They don't have anything that really moves

'em up and down, you know, uh, you know,

124

:

on sort of, on the, on the day to day.

125

:

And, they're just based on

some future possibility.

126

:

And that leads to two or three

really weird price dynamics, which

127

:

can lead to this concentration.

128

:

The first one is when you like, know

analysts and, and, and, and I think

129

:

that there's a, a fair amount of

evidence that analysts tend to crowd

130

:

with each other, and strangely, the

more volatile and uncertain the stock,

131

:

the more they tend to crowd with each

other relative to the volatility.

132

:

They have this benchmark risk of

being benchmarked to their peers and

133

:

looking wrong relative to their peers.

134

:

And so you actually find that for really

uncertain stuff that's a really high ball

135

:

that they crowd even more and it creates

more of these crowding effects and you

136

:

get more of these sort of bubbly effects.

137

:

And, and so that's like part of it

and that leads to momentum, in these

138

:

names, which can really happen.

139

:

And that, and of course they drag

retail in along with them along the way.

140

:

and you can put that up against what

feels like almost a totally different

141

:

statement, but I think are they actually

kind of work together, which is the,

142

:

you know, when you have a Dispersion of

opinions on something just straight up

143

:

though, like, and, and I'm not talking

about like analysts all crowded here.

144

:

I mean like actual people in the

market who are betting actually

145

:

have a dispersion of opinions.

146

:

You know, like cap in sort of assumes

that everyone has a modest expectations,

147

:

but like, that's clearly not true.

148

:

And as soon as you allow for

heterogeneous expectations, you get

149

:

these sort of weird effects where,

the more uncertain the outcome,

150

:

the more the price gets pushed up.

151

:

And I don't know if you guys have seen

any of these papers, but I mean, these

152

:

are, this is sort of a, a, is this

making any sense to you or do you want

153

:

me to go into this a bit more detail?

154

:

Yeah.

155

:

So, imagine if you had a world where,

you know, there's a, there's some

156

:

people thought a stock was worth

101 and some worth 102, and some

157

:

were 103 and somewhere 99, 98, 97.

158

:

And you kind of think that in a perfect

world, it would settle up what the

159

:

average dollar thinks it's worth.

160

:

And we've had this conversation a lot

about privates because it really, really

161

:

shows up in privates and in private

equity is the most extreme form of this.

162

:

The, the price doesn't settle what

the market thinks it's worth, the

163

:

price settles in what the most wildly

optimistic person's willing to pay.

164

:

So.

165

:

You know, if someone, if someone's

gonna buy a house and, and you know,

166

:

the market thinks it's worth a million

and some people think it's worth 800

167

:

and someone, and one guy goes, it's

worth 200 or it's worth 2 million.

168

:

It sells for 2 million.

169

:

It sounds more like, and, and so prices

push off to the right when you have

170

:

dispersion of opinion, when you can't

short the price back down to zero and

171

:

the privates cannot be shorted back.

172

:

So they go all the way to what the most

wildly optimistic person's gonna pay.

173

:

But if you have a world where you've

got more longs and shorts, or you have

174

:

a, a, not enough shorts to pull the

longs back, and we're always in a world

175

:

where there's a long bias, there's more

like there's more, you know, potential

176

:

long buyers and short buyers that a

dispersive opinion is going to bias you

177

:

towards the tails and to the right tail.

178

:

And so the bigger the dispersion of

like, like, I don't know, this thing is

179

:

worth, and some people think it's worth

nothing, something is worth a ton that

180

:

pushes you to the right as well and

creates a bubble in that space as well.

181

:

So you can kind of see how the massive

uncertainty of these things will result

182

:

in, in a, a bias high and momentum.

183

:

Which we see all the time.

184

:

and so, does it, so you can

push all that against Hmm.

185

:

It makes it pretty risky against, I

think like one other thing you have

186

:

to pay attention to and, and like,

look, there's always crazy issues

187

:

when you're doing market cap and

market cap waiting and people, people

188

:

have that as a benchmark, right?

189

:

And the challenge with market cap is

your benchmark meet is that it, it can

190

:

be an incredibly painful benchmark.

191

:

It's because if the, if the, if the

small number of names do extremely well

192

:

and, and you're anything other than

the, than the market you're going to

193

:

get, it it's gonna crush you at times.

194

:

And there are gonna be times when

you crush it because it does badly.

195

:

But it's, it's a really inefficient

benchmark in a lot of ways to

196

:

measure your performance against.

197

:

But it is, it is what people

do measure performance against.

198

:

And so you get these benchmark

issues associated with it.

199

:

and so like, there's, there's a whole

universe of quant and, and you know, how

200

:

do we think about alternative to market

cap indices, and think of them as, as

201

:

as processes and, and, and benchmarks

and, This is gonna go on, uh, uh, on

202

:

a total left turn, by the way here.

203

:

Um, but, uh, you know, I spend a lot of

time thinking about how do we alternatives

204

:

to market cap weighting because you do

get this massive concentration risk in a

205

:

small number of names and like, the most

naive alternative to market cap weighting,

206

:

which, which for sure eliminates

like, you know, any kind of mega a cap

207

:

bias is just to equal weight things.

208

:

And, it's actually like in the

very long term, a surprisingly

209

:

strong solution for equities is

just to equal weight All the names.

210

:

but it's, oh, it's shockingly naive.

211

:

and, and it's got, so we did

this, we, we, we ran like an

212

:

alternative to, to market cap weight.

213

:

We, we ran an equal weight and the

pro and there are lots of problems

214

:

with equal weight, but what it does do

is it says, I don't care what anyone

215

:

thinks this is worth, I don't care

what the market thinks it's worth.

216

:

I don't care.

217

:

I'm just gonna put $1 in each of

these things and, and, and so be it.

218

:

Now, lots of problems with that.

219

:

But one of the ones that always

bugged me about equating anything

220

:

was this definition of, well

what's the thing you're equating?

221

:

I mean, you could say like, imagine I'm

equating countries around the world and

222

:

I'm gonna put $1 in the United States

and $1 in Canada and $1 in France.

223

:

And then imagine the United States

breaks up into 50, you know,

224

:

independent little countries.

225

:

And that thing that used to have $1 in

you now go, now I'm gonna put $50 in it.

226

:

You're gonna bet 50 times as much

on the exact same thing, just

227

:

because of how it was defined.

228

:

And, and you have this problem

with equal weighting, which is,

229

:

I call the unit problem of equal

weighting, which was like, how

230

:

do I think about what's the unit?

231

:

Because it's clearly,

it's a definitional issue.

232

:

And if, if things come together, if

things split up, I'm gonna completely

233

:

change my weightings based on what

shouldn't change my weightings.

234

:

And that's like a big

problem with equal weighting.

235

:

And so market cap weighting, it's

got like a lot of efficiencies to it.

236

:

It's got a lot of, you know, like I

say, efficiencies, it's got theory

237

:

behind it that you can kind of stand by.

238

:

but at the end of the day, it's

people's opinions about things.

239

:

It's the whole market's opinion about

things, but the price does move on.

240

:

That Ecoweight's got this definition

of, of independent unit problem.

241

:

And so there's a subcategory

of things in between.

242

:

And, and so this is what we, this

is the sort of the three categories

243

:

of of alternative indices.

244

:

We created what we call kind of

like a fundamental valuator, right?

245

:

And a fundamental valuator is,

is is different again, because it

246

:

takes something about the companies.

247

:

And so like, you know, when Rob Arnett,

I, I think is a guy who's really

248

:

covered this a lot, but he would

say like, it's, it can be anything.

249

:

It could be a number of parking

spots in the parking lot.

250

:

It could be a number of employees, but

it's typically revenues or dividends or

251

:

cash flow or something that kind of speaks

to the size and he doesn't sell it this

252

:

Mike Philbrick: more towards

a fundamental criteria rather

253

:

Chris Schindler: biases it.

254

:

And, and so, so if you think about

Ecoweight and Ecoweight's got one extra,

255

:

really, this is totally off fire now,

but it's got one really cool feature

256

:

Ecoweight, which has got like a cult, like

an energy capture or a volatility capture.

257

:

If you have a number of companies that are

equal-weighted and you always have error

258

:

terms, you know, like you have surprises,

surprise the upside, surprise the

259

:

downside and, and what a market cap does.

260

:

Or if you take an equal weight and you

don't rebalance it, then the companies

261

:

that get surprised, the upsides grow.

262

:

So they have, they have positive

shocks and the companies that have

263

:

negative shocks shrink, and you end

up over-weighting the ones that have

264

:

positive shocks and under-weighting

the one with negative shocks.

265

:

And, and if there's any

reversion to the mean.

266

:

And so if, if prices project those

further out, if there's any reversion

267

:

to the mean, then you've, you're kind

of backwards in what you'd like to do.

268

:

What you really want to do is buy

the one you expect to, to revert back

269

:

and you wanna sell the one that's,

that's had a positive bias and market

270

:

cap is the exact opposite of that.

271

:

So anytime you equal weight or anytime

you rebalance to a starting process,

272

:

you're gonna capture some of that, that

natural mean reversion and, and in fact a

273

:

huge, huge proportion of a lot of quant.

274

:

Alpha and value add is in

fact that energy recapture.

275

:

And so I think Rob is able to show,

I don't know if he showed this or

276

:

something else did, but you could take

like the inverse of his portfolios

277

:

and they also beat market cap just

because that energy capture is, is

278

:

pretty, is pretty helpful anyway.

279

:

But so one of the things that, the,

that any kind of fundamental weighting

280

:

does is that, you know, when the

fundamentals change, you buy more

281

:

or less, but it doesn't move the

price because of people's opinions.

282

:

Because the market's opinion and

projecting that into the future

283

:

'cause that projecting into the

future tends to cause issues.

284

:

So, and if he's never sold it as this,

I've never really seen it presented

285

:

this, but the reason I like, I like

this idea is if I took a company, I

286

:

split it into 10 pieces, I will still

have the same amount of weight in that

287

:

new thing, split up 10 ways that I

would've had the original and vice versa.

288

:

And so it's kind of an equal weight,

but it's an equal weight by size

289

:

or something a bit more fundamental

than just like this equal weight.

290

:

And, and between those, now you

start to say, how do I invest

291

:

in a, in a market that's got.

292

:

some very, very concentrated

companies in it.

293

:

And, and you have to think, take

a step back and say, if those

294

:

concentrated companies were in

fact a hundred companies that came

295

:

together, well maybe it's not so bad.

296

:

Maybe that is, well, you know,

like it's a quarter of the weight.

297

:

But, but if it was a massive conglomerate

that brought together, maybe it's

298

:

not as concentrated as I think

299

:

Adam Butler: Mm-Hmm.

300

:

Chris Schindler: but if it's a

single thing with a, with a small

301

:

number of risk factors just blown

up a massive size and go, that's

302

:

when I gotta be more worried about.

303

:

And so we start to think again, which

is like, how do I determine how many

304

:

effectively independent companies

are in that company to get a proper

305

:

sense of how concentrated it is?

306

:

And, and, I'll just say those are,

there's a lot of topics in that, but

307

:

just say like, is there a fundamental

reason why tech, and especially tech with

308

:

earnings that are being projected way

out of the future is way harder to value?

309

:

Like Absolutely.

310

:

Does that result in trending

and possibly higher prices?

311

:

Look that, that then have to correct

and, and disappoint going forward.

312

:

Like probably, does that mean that.

313

:

Google.

314

:

Is Google a single factor

or is it a conglomerate, or

315

:

how do you think about it?

316

:

I think you gotta get a little bit

deeper before you say, is this, this

317

:

is a massive tech concentration.

318

:

'cause Google's not really

Google's a tech company, but

319

:

it's also an advertising company.

320

:

It's also, it's, it's a media company.

321

:

I mean, maybe it's a bit more, maybe it's

not quite as concentrated as it feels.

322

:

Adam Butler: Well, some of them

are more concentrated than others.

323

:

I mean, obviously Microsoft is exposed

to virtually every sector of the economy.

324

:

It's a massive global conglomerate.

325

:

Same with Google.

326

:

Nvidia reminds me more of like

a Nortel or JDS Uniphase, right?

327

:

I remember JDS Uniphase with their

optical switching and you know, everyone

328

:

assumed that the internet was gonna have

optical switching, and that was gonna

329

:

be the, tech that everyone settled on,

and JDS Unified just went to the moon.

330

:

You know, it's these kinds of concentrated

bets on, on these narrow tech,

331

:

outcomes that become especially risky.

332

:

Right.

333

:

But I mean, just from an advisor

standpoint, how do you manage this

334

:

and manage client expectations?

335

:

It terrifies me to see investing in global

cap weighted U.S equities above 60% of

336

:

global cap weight now, and seven companies

worth, you know, up almost 30% of U.S.

337

:

Equity valuation.

338

:

Like it's just a.

339

:

You just have this sort of, you're, you're

going on this massive amount of faith

340

:

and taking this huge concentrated bet.

341

:

If you don't, you risk

being totally left behind.

342

:

If you do, then you're

taking this concentrated bet.

343

:

It feels like a no-win situation.

344

:

I mean, how do big asset managers

deal with this, especially when

345

:

they're benchmarking against peers

on a year-in-year-out basis, like it

346

:

seems like it's just a hard problem.

347

:

Chris Schindler: Yeah.

348

:

And, and, the, challenge, and I, you know,

and I don't know how you break it, but the

349

:

problem with it is, is the benchmarking.

350

:

At the end of the day, if you are always

going compare someone to something,

351

:

then they are always going to have

to look somewhat like that thing.

352

:

And, and you've, and instead of being a

maximum share ratio investor where they're

353

:

trying to make as much money for, as, you

know, as much, much return, for as much

354

:

risk as possible, you've forced 'em to

have a different definition of risk, which

355

:

is, their tracking error to the benchmark.

356

:

And, and their optimization becomes

return over tracking outta the

357

:

benchmark, which is a fundamentally,

like, much less useful thing.

358

:

Uh, and, and it's much

less useful for you.

359

:

And I say like when typically I say

you're looking for managers and I

360

:

think you just have to get comfortable

with, I mean, if a manager's properly

361

:

a long, short space, they should have

no beta anyway, and you shouldn't care.

362

:

You literally should just say, I've got

my, you know, and, and whether I'm talking

363

:

about as a portfolio constructor, how much

of this stuff do I want in, in my beta?

364

:

Separate that question out for a second.

365

:

Say, let's say, let's say I've somehow

made that decision then for my managers.

366

:

I, I should give them the right benchmark

and I should give them the right risk

367

:

definitions and the right governance.

368

:

And so that, so that this

doesn't affect 'em at all.

369

:

They have a good stock pick over here and,

and, and they should make it regardless

370

:

of what the beta is and is doing.

371

:

Now, that's, that's, that's a pie

in the sky kind of nice statement.

372

:

It, it typically doesn't go that way.

373

:

But even for, you know, even if you're

saying like, I still, I'm investing my

374

:

money in this beta, what do I do about it?

375

:

And, and it's funny because when we

first started looking at this and how

376

:

to think about waiting countries and,

and I think we're doing this research

377

:

in the early two thousands and the,

and, and the country that really stuck,

378

:

stuck out in the history, you know,

the last 20 or 30 years was Japan.

379

:

'cause Japan in the late eighties had had

what looked exactly like the US does now.

380

:

It was a massive portion of MSCI

and of course it got super expensive

381

:

as again, there was all the tiger

funds and everyone was, was, was,

382

:

was just throwing money into it for

15 years and it got so expensive

383

:

and then, and then it just broke.

384

:

And it broke, and if you were MSCI

weighting Japan, you got crushed.

385

:

If you had, you know, underweighted a

bit, you did well because you had a very,

386

:

very large concentrated exposure to a

relatively small subset of the universe.

387

:

And, and I think over the very long

term, these moves tend to punish you

388

:

and you tend to want to disparate

because, because there's the, there's

389

:

always the mixture of the fundamentals

and then the market mania behind it.

390

:

And, and the market mania behind

it is the, is the piece that always

391

:

over-projects and, and any market cap

weighted, which is a mixture of the

392

:

fundamentals and the market's projection

of that into the future is, is almost

393

:

certainly gonna lead to over-projections.

394

:

The problem is, can you survive in

the short run long enough leading

395

:

against that to, to prove your thesis.

396

:

That's the tricky part.

397

:

Mike Philbrick: it's, it's the

combination of, of this, overvalued

398

:

market and a strong trend, right?

399

:

So, and this is where it gets

really dangerous because when the

400

:

overvalued market trend turns and

increasingly you get that larger

401

:

and larger spikes in volatility.

402

:

Where the dip is bought until such time,

it's a 25 or 30% and the dip isn't bought,

403

:

or it's only bought up 10 or 15, and

the trend is now changed and different.

404

:

And the world of investors is

always sort of slower to pick that

405

:

up in, in the final trend change.

406

:

And then you have this exposure, this

overexposure to the largest market

407

:

just by the market cap chasing.

408

:

And you have the risk unwind and, And so

that's, you know, the valuation side of

409

:

it is important, but man, when the trend

is strong, it's a really hard problem.

410

:

Chris Schindler: yeah.

411

:

And, which I guess when you're

saying the trend is strong girls

412

:

and the values, you're just, you're

also, to put it another way, you're

413

:

just saying the behavioral side

414

:

Mike Philbrick: Right.

415

:

It's that, it's that, it's that

momentum that, you know, that punching

416

:

fist through the, the, the enthusiasm

that continues and as long as it

417

:

continues, the valuations don't matter.

418

:

I mean, it, it's expensive.

419

:

It's not as expensive it's ever been.

420

:

It's not as expensive as Japan was, and we

don't know if any of those are even limits

421

:

on how expensive something could co become

in a, in a strongly trending market.

422

:

Chris Schindler: Yep.

423

:

So, uh, and that's exactly it.

424

:

And, and so then you end up with, you

know, sort of various forms of this, which

425

:

is like, look, you can stay along the

trend, but you've gotta be aware that the

426

:

more crowded it gets, the, the quicker and

sharper it can turn back on you because

427

:

there's, because there's like a growing

liquidity build up and there'll be a

428

:

growing liquidity rush on the way out.

429

:

I, I think, my guess is a

lot of players get that.

430

:

I don't know if the retail side sees

it as clearly, but I think a lot of

431

:

players get the growing riskiness of it.

432

:

But there's always that.

433

:

Yeah.

434

:

But you have to keep playing

while it's still happening.

435

:

And, and it's very, 'cause it's

just so painful to lean against it.

436

:

So, uh, and this, it all comes down

to it's a benchmarking problem.

437

:

Adam Butler: Did you ever

438

:

Mike Philbrick: a doubt.

439

:

Adam Butler: did you ever do any

work internally on, um, the, double

440

:

exponentials, like as the, as the

curve approaches a certain level

441

:

of criticality and the fractals

and all that kind of stuff?

442

:

I forget the name of the

French, mathematician who was

443

:

mapping all of that and you wrote

444

:

Chris Schindler: a way

445

:

Adam Butler: paper April.

446

:

Chris Schindler: it?

447

:

Mike Philbrick: or what?

448

:

Adam Butler: He, one of.

449

:

Mike Philbrick: Mandel.

450

:

Mandelbrot.

451

:

Is

452

:

Chris Schindler: Mandelbrot would be one

of like the fractal guys, but, but yeah,

453

:

so the, um, I mean, yeah, that's, that's

a big, so when markets go parabolic, the,

454

:

the issue is always is, is you know, like

it's the same definition of anything.

455

:

It's like a bubble is really easy to

see after the fact, after it's popped.

456

:

Um, it's very, very hard to know

if this thing that's running up,

457

:

is that the bubble yet or is it

the peak, the bubble, you know?

458

:

And Jeremy, Grantham, GMO has done

a huge amount of work on trying

459

:

to just, you know, he's, he's

basically all bubbles being revert.

460

:

But the, the challenge with that is,

after the fact, yes, all bubbles being

461

:

reverted because you kind of defined it as

a thing that went up and came back down.

462

:

It, you know, Microsoft or Apple,

just like, are they bubbles?

463

:

Well, it's hard to say.

464

:

They just, they kept going

for like 15, 20 years.

465

:

And, and so, I mean, maybe at some

point in, in the far future you'll

466

:

be to look back and say, yeah, yeah,

they were bubbles, they mean reverted.

467

:

But, but it's, it's, I don't

think it's quite as obvious.

468

:

And, and so he tries to fight in

bubbles relative to fundamentals.

469

:

But the, the problem is they mean

revert or the fundamentals catch up.

470

:

and it's one of those two,

471

:

Adam Butler: The story always need

to have a plausible outcome where

472

:

the fundamentals could catch up.

473

:

I mean, there's very good narratives

around why, you know, meta Google

474

:

NVIDIA, Microsoft, deserve these

ultra premium multiples, right?

475

:

The new story is AI and all the

compute that's gonna be required.

476

:

In 2000, it was, it was internet and

switches and all that kinda stuff.

477

:

In Japan, it was their six

Sigma manufacturing process.

478

:

They were gonna completely

dominate global tech, manufacturing

479

:

and auto manufacturing.

480

:

And, you know, that all got swept

up in their, in their banking sector

481

:

and, and the real estate sector.

482

:

You know, I remember in

:

483

:

in Tokyo was valued at a.

484

:

Higher total valuation than

all the land in California.

485

:

Right?

486

:

Like, and there's a plausible

reason for this every time, right?

487

:

And, there's this potential every time

for this time to truly be different.

488

:

You know, maybe, fast takeoff AI actually

does, mandate this kind of overvaluation,

489

:

maybe software, you know, uh, mark

Andreessen said Software eats the world.

490

:

Maybe this is the time when

software eats the world.

491

:

Like there's always gotta be this

plausible explanation in order

492

:

for the markets to rise to this

kind of bubble level, right?

493

:

Chris Schindler: Maybe, but then you,

I, I, it's like, unless there's, unless

494

:

it's also a, an incredible, like just

creator of mass wealth for everyone.

495

:

You, you can't, you can't plow this one up

because it's potential ability to grab the

496

:

ability and still keep these gut there.

497

:

There has to be like once again,

you gotta add all up what, like

498

:

those growths require what kind of

earnings and what kind of cash flows

499

:

and what kind of percentage of the

total world pie at some point you go.

500

:

Does that make sense?

501

:

Because if they're claiming two x

of what it it will ever be, then

502

:

no, those things don't all add up.

503

:

It's just the question is like, one

of those 10 may be correctly valued.

504

:

Maybe that goes even bigger.

505

:

But, but that's, I mean that's obviously,

yeah, there's, there's always a story.

506

:

Uh, there's no doubt

there's always a story.

507

:

and it has to make a bit of sense.

508

:

It can make a lot of sense.

509

:

The, the, the, you know, and we, we

all heard the stories, like all the

510

:

way through, like through the, through

the years and through the decades.

511

:

We've heard the stories.

512

:

I mean, I guess NFTs had a story.

513

:

I, it it doesn't necessarily mean that

they're gonna hold their wealth when

514

:

the story moves on to someone else

515

:

Mike Philbrick: The, the other thing

is the initial conditions can, they're

516

:

important and they're different.

517

:

Right?

518

:

1990, you had a significant

earnings contraction, yet

519

:

the market did not go down.

520

:

The early nineties, the

S&P kind of sailed through.

521

:

Whilst earnings were contracting, I

mean, yields were high and they, it

522

:

looked over the recession almost.

523

:

And so you also don't know what

the initial zeitgeist of the

524

:

market is when you go through

the, through the transition.

525

:

There's so many dimensions to this.

526

:

It's, it's

527

:

Chris Schindler: Yeah.

528

:

Well, yeah, it's, it like, no doubt.

529

:

and I think, you know, like, especially

when Japan peaked in 89 and, and I

530

:

mean, I'm gonna make up some numbers,

but I think like 15, 20 years

531

:

later, it's stock market was down.

532

:

I can't remember, like 90% in, in like,

like it was so much in its real estate

533

:

market was down ninety-five percent.

534

:

It was, it was just

unbelievable crushings.

535

:

Mike Philbrick: It's only

approaching those numbers today,

536

:

Chris Schindler: yeah.

537

:

Yeah, it's just

538

:

Mike Philbrick: but it's.

539

:

Chris Schindler: and, and, you know,

and, and, I think like from like

540

:

2000, 2010, I think Japan's earnings

growth was faster than the U.S.'s.

541

:

like it's starting points really matter.

542

:

And, and whether or not, and you're gonna

see this lots of times it's like, and,

543

:

and you think about, you know, like risk

parity stocks versus bonds and you go

544

:

like, like if you just went, like imagine

you just, you make some magic statement.

545

:

It's like they both should have

the same sharp ratio over time.

546

:

And maybe that's true,

maybe it isn't, who knows?

547

:

But like, you know, if this guy

runs off at a sharp of one over the

548

:

last 10 years, it's either getting

ahead of itself or catching up.

549

:

And I don't know if you really

know, because at the end of

550

:

the day I mean, who's to say.

551

:

But, uh, or maybe a bit of both and,

and it is either getting in front of

552

:

itself and you should sell it or it's

catching up and it's a good deal.

553

:

and I, I guess that's kind of

like a risk-parity statement.

554

:

It's like if you were, uh, if there, if

the only two things you could invest in

555

:

in the world were stocks and bonds and

you had 'em, would you care if this one

556

:

happened to take from this one and then

this one happened to take from this one?

557

:

If you have both of them, I guess

you're, you're probably kind of fine.

558

:

so if you have the world and the world is

taking from here to give to here, as long

559

:

as you've got a well diversified basket,

maybe you don't care as much, um, as,

560

:

as, as, as long as you do that, right?

561

:

Adam Butler: then you've got periods

like:

562

:

makes, makes a bit of a mockery of

that stock bond diversification, right?

563

:

Like this, you know, own

some stocks, own some bonds.

564

:

The idea is the bathtub.

565

:

There's always a drip into the bathtub,

and so the level always rising,

566

:

whether it rises more into equities,

that doesn't really matter versus

567

:

bonds because you own them both.

568

:

But when the, you know, that bathtub

sort of contracts, the levels contract,

569

:

then, you know, you've got stocks

and bonds both losing together.

570

:

Right.

571

:

Which is why stocks and bonds,

the, the two-legged stool

572

:

typically doesn't, balance Right.

573

:

You gotta add that, that third leg.

574

:

Chris Schindler: Yeah, I mean, at

least I, I and I, I guess that, so the

575

:

statement there was like, if stocks

and bonds were the only two things,

576

:

and you had, I guess, a world where you

couldn't lever and delever, obviously,

577

:

when we first started our risk parity

work, I mean, the very first thing

578

:

we did is went, stocks and bonds are

dangerous, like hugely dangerous.

579

:

And, and, and that would be a crazy

dangerous risk parity process.

580

:

and, and assuming correlations are

static and either zero or negative

581

:

is also massively dangerous.

582

:

And so, you know, if it, it's gonna

require some dynamicism and it is

583

:

gonna require some dynamicism on risk

and correlation measures, and it's

584

:

gonna require other stuff because

you, and I think I presented this

585

:

a while ago, to you guys I know I

ave this presentation back in:

586

:

When the last thing anyone in the world

was thinking in:

587

:

stretch your mind back and remember.

588

:

But it was like people were still kind

of freaking about deflation at that time.

589

:

And the last thing anyone was

thinking about was inflation.

590

:

But, but it was, it's just all it

is, inflation is always a risk and

591

:

discount rate shocks are always a risk.

592

:

And, and so building a portfolio

that's resilient to, to inflation

593

:

shocks and discount rate shocks,

Inflation shocks is easier 'cause you,

594

:

because you can put some other stuff.

595

:

You've got some, you know, some

gold or some break-evens or

596

:

some, you know, commodities.

597

:

There's things that you can put together

to, to get a decent attack on inflation.

598

:

I just can't write shock, you know,

that, that's, it's self distinct

599

:

from growth and inflation shocks

is much harder to defend against.

600

:

because, you know,

601

:

Adam Butler: We just haven't

had very many inflation shocks

602

:

over the last few decades.

603

:

So, you know, hedging against inflation

or owning assets in the portfolio that

604

:

are designed to do well during higher

than expected inflation shocks has kind

605

:

of made you look silly for a long time.

606

:

You get these sort of periodic spikes

where it, pays off and then you

607

:

go through these long stretches of

sort of this, you know, or at least

608

:

you have over the last few decades.

609

:

Gone through these long stretches

of disinflationary growth and, you

610

:

know, any I, any effort to diversify

outside of stocks and bonds kind of

611

:

makes you look silly for a long time.

612

:

And then, you know, you get this, you get

this spike and, and that sort of pays off.

613

:

But it's just the investors haven't

had much experience with that level

614

:

of diversity paying off over the

horizon that they've been managing

615

:

money or had money invested in markets.

616

:

So it's hard.

617

:

Chris Schindler: Sure.

618

:

totally right.

619

:

Um, to that, I guess I would

add a couple things uh, and I

620

:

can't remember what I presented.

621

:

Uh, I should probably would've rechecked

my old podcast before I, I came on.

622

:

But, the, um, inflation, uh,

so something like a breakeven.

623

:

While, while it should respond

and it responds to a certain type

624

:

of inflation shock over a certain

timeframe, which is not necessarily

625

:

what you're, you're always worried

about, probably has a negative expected

626

:

return over time, though, as a trade.

627

:

And, so if you think about the things

that, like that you mentioned where

628

:

you go, I, I want to have a positive

expected return because I want it

629

:

to contribute to my total portfolio.

630

:

And, and yeah.

631

:

Like it's gonna be spiky

at the right times.

632

:

And then how do you build something that's

inflation sensitive that has more of a

633

:

smooth, positive return over time while

still covering your inflation shocks?

634

:

And that was the big, I think, you

know, sort of effort in saying,

635

:

first of all, when we, when we built

our inflation sensitive asset class

636

:

against all sorts of pressure to

say like, why, why would we bother?

637

:

The answer is because it's

a risk and it could happen.

638

:

And, and so.

639

:

Whether or not you think it's

gonna happen, let's call that

640

:

your alpha on this whole thing.

641

:

But, but, you know, portfolio construction

at the, at the portfolio level is just,

642

:

I want to build things that are resilient

to a variety of outcomes, regardless

643

:

of who thinks what's gonna happen.

644

:

I call that like a data

portfolio construction.

645

:

And, and even then you

say, what's inflation?

646

:

And, and, and everyone's got a different

definition of inflation, right?

647

:

An economist might say it's a CPI

or, you know, wage inflation, or they

648

:

might say it's monetary inflation.

649

:

A lot of 'em will say it's

monetary inflation is the

650

:

correct definition of inflation.

651

:

you know, it, it obviously, as we saw

in the seventies and, you know, the

652

:

late sixties or even early eighties,

inflation can be driven by commodities.

653

:

Um, and it's, so I call

a supply side inflation.

654

:

And, and if the price of commodities like

go up by four times, well yes, that's

655

:

going to be massively inflationary.

656

:

If it's persistent and

it's across the set.

657

:

and so for each of those different

definitions of inflation, you

658

:

actually have different basket

of assets to, to handle them.

659

:

And so for monetary inflation,

like what, what's your, what's

660

:

your best defense guess?

661

:

Monetary inflation.

662

:

I don't know.

663

:

There's like, there's a variety

of things you can think about

664

:

from real assets to gold.

665

:

Uh, you know, if it's, if it's,

if you're looking purely at a

666

:

definition of something like CPI,

then maybe a real return bond or, or

667

:

a breakeven is a better focus on that.

668

:

If you're looking at like a source

of inflation from the energy side or

669

:

from the ags or from commodities in

general, then obviously commodities

670

:

are the best source of that.

671

:

You know, we built a, a very broad

basket inflation-sensitive set of assets

672

:

because we thought inflation can be,

there's lots of different definitions,

673

:

there's lots of different, causes, but

that the reason you care about inflation

674

:

and the reason you need this, this asset

class is because in general inflationary

675

:

shocks have a deleterious effect on most

of the other assets in your portfolio.

676

:

And so there's gonna be times

when your other assets get hit,

677

:

especially your bonds get hit

by inflationary, like unexpected

678

:

inflation, but so do your businesses.

679

:

And so, you know, if you think of your.

680

:

Your equity in your businesses and your,

you know, are, are, are generally exposed.

681

:

You need something to protect you.

682

:

And then the real question is, well,

how do you build something that

683

:

protects as well as possible, but

still has a positive drift to it?

684

:

And so that's where like, that's where

we kind of built a quant program or a

685

:

systematic program that does that, right?

686

:

And you can start to think about if I

got these, like, what am I trying to do?

687

:

Is I'm, I'm trying to cover

inflation, but I'm also trying

688

:

to get the positive risk premiums

and drifts in the commodity space.

689

:

Well then you gotta get, you

gotta dig a, dig a bit deeper than

690

:

just going along a couple things.

691

:

And that once again, requires a

bit more expertise, a bit more

692

:

specialization, and a bit more

leverage and a bit more like effort.

693

:

But ultimately I think something

like that can be really, really

694

:

helpful for a lot of investors.

695

:

Adam Butler: Yeah.

696

:

I mean, before we

697

:

Chris Schindler: to, once again, like

if, if, if you thought your bathtub

698

:

was just stocks and bonds Yeah.

699

:

You're, you're gonna get,

like, you're gonna get exposed.

700

:

the, the risk parity world is really

like, it's that statement of like, if

701

:

this just money sloshing around, then if

somehow you could own a bit of everything.

702

:

Uh, then in that world

maybe you're kind of okay.

703

:

Um, but then, then that goes

like, well, that's great.

704

:

Money's sloshing around.

705

:

And, and, and every single

investor's wants to get that alpha.

706

:

Like, I want to time that I want to

add value by getting in front of that

707

:

sloshing or avoiding the sloshing or,

you know, and of course that's what all

708

:

active and macro and everything is, is

trying to time the flows of money around.

709

:

And it's like, yeah, stocks

and bonds and commodities.

710

:

If you got that, if, if somehow

that flows your entire path, that's

711

:

great, but I'd still like to capture

some of that energy between them.

712

:

And, and that's where, you know,

I think a lot of the fun is.

713

:

Adam Butler: so speaking of Alpha and

trying to generate it, we spent a lot

714

:

of time, you know, debating where the

greater, if inefficiencies are right and

715

:

the more sustainable inefficiencies are.

716

:

And we chatted a little bit

about Samuelson's dictum on

717

:

this program, a few times.

718

:

And, you know, whether there's a,

a greater opportunity to generate

719

:

alpha through security selection

or in, in the macrospace, just in

720

:

terms of hedging inflation risk.

721

:

Like I.

722

:

Do you think it's, it's conceivable to

be able to manage inflation risk through

723

:

more effective security selection?

724

:

Like, can you just select a diverse

basket of equities and or credits that

725

:

make you more or less resilient to

inflation and you don't need to have

726

:

that third leg of the macro stool?

727

:

Chris Schindler: huh.

728

:

That's interesting.

729

:

Um, so Samuelson's dictum, that's

the microefficient macro inefficient.

730

:

Adam Butler: yeah, yeah.

731

:

Chris Schindler: I mean that's a, that's

an interesting statement and I think

732

:

it's one of those things that, um.

733

:

You know, I, I lemme just like quickly

sort of say about inflation, I would,

734

:

I would kind of think of, uh, what you

just said there is like, if I stock

735

:

pick correctly, can I, can I create,

like can I, can I cover inflation

736

:

from credit and stocks as opposed

to having to go into commodities?

737

:

Like Yeah, I mean there's probably

some inflation sensitive equities

738

:

and, and, and I think, you know,

you, you could probably find things

739

:

that have some inflation sensitivity.

740

:

you know, is that, is that going, is

that something you would add to your

741

:

basket of inflation sensitive assets?

742

:

Yeah, probably.

743

:

I think you have to be careful and

this is, um, you know, this is just an

744

:

alpha beta separation statement, but

you go, like, if, if you think of like

745

:

portfolio construction as I'm gonna try

and build my portfolio and, and I think

746

:

of past and we've had this conversation

before, like what's passive, like

747

:

nothing's truly passive, you know, and,

and what's beta and, and my definition

748

:

of beta like goes all over the place.

749

:

But if you say one definition

of it is like it's gonna do

750

:

what it's gonna do regardless

of what anyone expects it to do.

751

:

And, and so if you put money in it, it

doesn't matter what you think this is

752

:

gonna do once, if you just, if you just

leave it, it will, it does what it does.

753

:

Um, that definition of, beta,

well, if you go, I'm gonna put my

754

:

betas together to try and create

the best beta portfolio possible.

755

:

There's obviously some active decisions

there, but let's say there's like,

756

:

you know, a not as much timing,

then you need pieces that interact

757

:

with each other in a nice way.

758

:

And, and if you're leaning on your ability

to see the future and, and stock pick

759

:

correctly to cover your inflation risk,

that's, that's a little bit different.

760

:

That's, that's, that's like saying

like, if I could see the future properly

761

:

and I can call winners and losers,

then I don't have this risk because

762

:

I'm, because I can see the future.

763

:

And it's like, well, maybe

you do, maybe you don't.

764

:

But that's active management and

you're now relying on active management

765

:

to cover your inflation risk.

766

:

And I would say you, you

should do that as well.

767

:

But when I think about how pieces of

my portfolio interact and portfolio

768

:

construction the way, and this is how we

sold it to our board, and I think it's a

769

:

really interesting thought process when

you talk about your, portfolio, your beta.

770

:

And we said, what's the portfolio

you wanna have in 10 years from now?

771

:

It's like, not over the next 10 years.

772

:

Like in 10 years, if you had to

build a portfolio and say, 10 years

773

:

from now, this is the portfolio

I want, what would it look like?

774

:

And the key part of that statement

is you have no idea what the

775

:

world's gonna look like in 10 years.

776

:

You have no idea if you're gonna

like stocks more than bonds, if

777

:

you're gonna like commodities.

778

:

If you're gonna, you have no active, you

have no possible active view in 10 years.

779

:

And so that's the, and so think

of that as your definition of

780

:

passive, as your definition of beta.

781

:

Build the best portfolio you can that

you'd be happy having in 10 years.

782

:

And then think of active as everything

that you do between now and then.

783

:

So like I'll have a view over the next

month or the next two months, or the next

784

:

five years and start to layer on that.

785

:

But your center point, your starting

point should be that thing that, that,

786

:

that is the most, Unaffected by your

view of the future, because your view

787

:

of the future make it, make those

bets and, and, and decide how much

788

:

risk to put in that bet based on how

much, how confident you are in your

789

:

ability to see the future and do that.

790

:

But, but just understand that,

that you could be wrong and you

791

:

might not see the future right.

792

:

And you might not have that ability.

793

:

You might not be as good

as you think you are.

794

:

You might be better than you

think you are, who knows?

795

:

But, but, separate those two pieces

out and build the best beta you

796

:

can and that needs assets that

interact well together regardless

797

:

of your ability to call the future.

798

:

And then, and then if you want to

try and add value through active

799

:

management, absolutely do that.

800

:

And if you think part of that value

is alpha and part of it is inflation

801

:

protection, however you wanna

define that, for sure, go for it.

802

:

Size it, right?

803

:

But separate those decisions there.

804

:

Mike Philbrick: And the, the nice side

effect there, Chris, the way you explain

805

:

that is now you also have something

to measure your active bets against.

806

:

You have this, un, let's call it unbiased,

do no harm allocation of beta assets.

807

:

That you will have today and have in

10 years, and you're gonna make active

808

:

bets, you know, against that, or add

additional diversification to that.

809

:

And now you can actually measure whether

your steps were in fact a creative

810

:

or were they Dilutive to the actual

long-term returns of your portfolio?

811

:

Chris Schindler: percent.

812

:

And, and, and, and you're exactly right.

813

:

And that was a huge part of the push

for creating that, we call it the

814

:

theoretically optimal portfolio.

815

:

And, and you never quite get to it because

you have constraints and you have, and

816

:

you're not ever 10 years in the future.

817

:

You have, you know, and you have

a starting point and you're trying

818

:

to move from there to something.

819

:

There's, there's a lot to that.

820

:

But that's, if that's your center

point, that, then you can measure your

821

:

distance from that and you can start

to justify your distance from that.

822

:

And, and that starts to really be your

act, your set of active decisions.

823

:

You have to start justifying why

you are no longer what, what and why

824

:

you're not going in that direction

or why you're leaning against that.

825

:

And, and, start to think about how much

active risk you're taking in, in those

826

:

active decisions relative to that data.

827

:

It's a really, really helpful starting

point and it's a much, at least from

828

:

my opinion, 'cause this is what we

kind of, you know, put in place.

829

:

It's a much better benchmark portfolio

than almost anything else you can define.

830

:

Like, this is, like, we talked at

the beginning about the challenge of

831

:

benchmarks and if you're, if you have

your, your CIOs responsible for, for

832

:

investing at the total fund level and you

give them a benchmark that's 60 40, then

833

:

it's gonna be really hard for them to be

anything that's like too far off of 60 40

834

:

because you've made that their benchmark.

835

:

And now that their definition of

risk is tracking error to a 60 40.

836

:

And if you say your benchmark is the

median manager or the median pension

837

:

plan or the median, anything that's

gonna look a lot like a 60 40 or an

838

:

80 20 or it's gonna, you know, at

the end of the day, they, once again,

839

:

they're centered around something.

840

:

That isn't necessarily the,

the, the right starting point.

841

:

And you go, how do we ever move off

of that paradigm and how do we move to

842

:

something better if you're always getting

benchmarked back to that paradigm?

843

:

And, but then the question inherently

comes, well then what's, what do

844

:

you want your benchmark to be?

845

:

and that becomes a, a really

tricky question, but you say

846

:

like, look, this is a good center

point to start thinking about.

847

:

And, and, and you have to be

careful that it's, that it's not

848

:

too pie in the sky theoretical.

849

:

Like if you, it can't assume that you

can do certain things that you, you

850

:

can't, in reality, like, like a leverage

requirements or, you know, assets,

851

:

there's not enough real return bonds on

the planet to do what you want to do.

852

:

It's like, well, that's

not a fair benchmark.

853

:

So it has to be like, you know, it has

to move back to reality a little bit,

854

:

but like, as a, benchmark construct that,

that you sort of say like, I can measure.

855

:

And, and, and, and I guess the

one other way you can think about

856

:

benchmarking yourself, and this is

like also super weird, but we also

857

:

put in place a little bit, was.

858

:

Benchmark each year to

the start of that year.

859

:

So, 'cause I'm just trying to break the,

compare myself to the rest of the world

860

:

or do what the rest of the world's doing.

861

:

And now you can say, if I'd held the

portfolio that I started with for the

862

:

entire year versus what I actually

did, I could not measure my changes to

863

:

some arbitrary starting point, which

is just as arbitrary as anything else.

864

:

But I can start to like, once again, focus

in my alpha without contagioning it with

865

:

someone else's definition of alpha, which

is in their starting portfolio, which

866

:

is, which becomes my beta unfortunately.

867

:

And I, I don't want my beta to be

someone else's alpha as my starting

868

:

point because, because that really

messes up the whole decision,

869

:

Mike Philbrick: N nothing, nothing more

dangerous than having a false premise to

870

:

start the whole discussion of, oh, 60 40s

your benchmark and beat the media manager,

871

:

and that that premise just contaminates

every other decision down the track,

872

:

Chris Schindler: Yeah, absolutely.

873

:

And so portfolio construction at the

total fund level is, it's hard enough

874

:

as it is, but, understanding the, oh

Everything is affected by your benchmarks.

875

:

Like everything.

876

:

And, and so trying to break the paradigm

of, or like the worst thing if you're a

877

:

CIO is some other team that's not you.

878

:

Like a risk group creates your benchmark

and now you're like, well, who's the CIO?

879

:

Because the most important set of

decisions, the asset allocation,

880

:

maybe even the amount of risk you're

taking have been, ab like have been

881

:

taken over by a different group.

882

:

And, and, and now you're just

a, like a long short TAA around

883

:

someone else's starting benchmark.

884

:

And like, I believe the CIO should

own the total portfolio, should

885

:

own every major important decision.

886

:

And so, and, and you can really

see, the challenges of that.

887

:

But at the same time, you're a

board member, you go, oh, like what

888

:

are you completely unconstrained?

889

:

And so then you can start to define,

well here's a, here's an alternative

890

:

benchmark, or here's the definition

of risk, which is how much movement

891

:

from where we are comfortable

here to, to the end of the year.

892

:

Like, and, and, and we were just trying to

come up with alternative benchmarks that.

893

:

gave you the flexibility you needed to do

the right things without giving you too

894

:

much flexibility to, to cause unmitigated

895

:

Mike Philbrick: do the wrong things.

896

:

Chris Schindler: So,

897

:

Mike Philbrick: The CIO's dilemma is

just getting more and more, uh, complex

898

:

and uh,

899

:

Chris Schindler: it, absolutely is.

900

:

That was a, that was a big part

of the challenge was, was breaking

901

:

that, breaking that benchmark.

902

:

Adam Butler: Yeah.

903

:

Another irony is that the fact

that everybody is benchmarked to

904

:

something is the, you know, a big

reason why a lot of alternative

905

:

sources of return exist, right?

906

:

Like, you know, if, the true definition

of risk is tracking error and not

907

:

the deviations and the value of the

overall portfolio, then that is going

908

:

to drive behavior that is aligned with

minimizing tracking error, not aligned

909

:

with minimizing total wealth variance

and that produces the opportunities that

910

:

alternative managers, many alternative

managers use to generate their returns.

911

:

So, you know, you don't, you don't want

everybody to become enlightened and,

912

:

and abandon their benchmarks because

then it has the potential to, to kill

913

:

the goose that that lays the golden

eggs for many alternative managers.

914

:

Mike Philbrick: But,

915

:

Chris Schindler: Yeah,

I wouldn't say it's it.

916

:

Yeah, you're absolutely right.

917

:

It's, it's definitely one of the sources.

918

:

It's, it's probably not the only one,

like benchmarking, but it's definitely

919

:

one where, and you could kind of like

just argue, you know, as, I guess we

920

:

have in the past that it all comes

down to anti-crowdedness, right?

921

:

Like, it comes down to when you have a

bunch of people following some set of

922

:

rules or some process or some benchmark.

923

:

Whenever, whenever too many people crowd

into, into any particular area, the prices

924

:

get bid up and, you know, if the cash

flows aren't affected by that crowdedness

925

:

'cause why would they be, you know,

the, the, the prices get bid up and the

926

:

cash flows the same and returns fall.

927

:

Like crowdedness is always gonna

result in, in, lower Sharpe ratio.

928

:

Because at the same time is that, you

know, the returns fall, the risk goes

929

:

up because the possibility of that

crowd all trying to lead together at the

930

:

same time becomes significant as well.

931

:

So crowdedness of which benchmark

hugging is a major one, uh, is a

932

:

significant source of potential

alpha if you can, if you can avoid or

933

:

take advantage of that crowdedness.

934

:

so all of that to say, you know, if we,

if we backtrack and went, inflation and

935

:

we can come at it from the alpha side,

we can come at it from the stop making

936

:

side and, and whether or not, I know you

kind of started with inflation or, or you

937

:

even sort of went back and said, look,

are we, are we micro or macro efficient?

938

:

I don't know.

939

:

Like these, these are, these are

interesting questions because like in

940

:

one sense it really does look like,

we have massive examples where we've

941

:

been incredibly macro and efficient

over the last 20, twenty-five

942

:

years to the point of so obvious in

hindsight, and maybe for many people,

943

:

super obvious at the time as well.

944

:

and so, so you might argue them for

microefficiency and, and like, and I

945

:

guess microefficiency, it's got one other

thing going for it, which is like, as

946

:

human beings, if you think about it for

a second, like everything that we, like

947

:

all of our senses are, are really good at

relative, but terrible at absolute right?

948

:

Like, like I go, like, if, if you

asked me what stars brighter in the

949

:

sky, I could say That one's brighter.

950

:

But you know, or what's bigger,

you know, or what sound is louder.

951

:

I can, I can do relative really well.

952

:

And that's what our

senses are built to do.

953

:

We're terrible at absolute.

954

:

I could not give you like any sense

of it, how bright that that is.

955

:

And in fact, even our relative senses

are like log scale and you know,

956

:

like what seems like twice as loud

to us might actually be 10 times.

957

:

Adam Butler: Mm-Hmm.

958

:

Chris Schindler: More decibels and

the same thing with brightness.

959

:

And, so like, so we're quite

good at saying A versus B.

960

:

And so if you think of like micro

as a whole series of like, you got

961

:

specialists focusing on a small number

of stocks and you're stock picking

962

:

and you're going a whole series of A

versus B and doing some sort of ordinal

963

:

rank, that's probably what we're most

comfortable doing as humans, right?

964

:

And, and so we probably are very

confident in our ability to do that.

965

:

And we probably are quite good at

orderly ranking things, but then you,

966

:

I guess, like you got a bunch of things

that might even be ranked correctly,

967

:

but when the whole picture, the

absolute piece can just be miles off.

968

:

And I think as humans we're probably

no good at the absolute piece or, and,

969

:

and so without something to anchor

that absolute two, it, it probably

970

:

can go off, in extreme distances.

971

:

Adam Butler: Well, here, here,

here's, we sort of came at it, right?

972

:

We came at it from the

perspective of, two dimensions.

973

:

One is, portfolio agility, right?

974

:

the big players out there.

975

:

just don't have much ability to take

major bets, take major tracking error

976

:

against their policy portfolio, right?

977

:

Like taking major, equity overweight

versus target or major credit overweight

978

:

or duration overweight versus target

carries a lot of risk, whereas taking,

979

:

you know, maybe there's more tolerance

for risk within the, you know, individual

980

:

asset classes, And then there's just

the agility, like you're, you're

981

:

swinging these massive portfolios

around, you just don't have the, the

982

:

ability to move quickly enough to take

advantage of, of many of the macro

983

:

or micro inefficiencies that exist.

984

:

Right?

985

:

So, sort of taking a down one

level, I would argue kind of 99%

986

:

of all cognitive and computational

energy focused on investing.

987

:

Is within the individual silos, right?

988

:

So you've

989

:

got the equity group and

you've got the credit group.

990

:

You've got the, the

991

:

rates group, you got the

992

:

Chris Schindler: There's no way

the equity group can tell you

993

:

equities versus a commodity.

994

:

Like, it just doesn't, the

question makes no sense.

995

:

And so there, you know, I think

there's, there's probably another thing

996

:

that, that leads to microefficiency

as well is the stat art players like,

997

:

the ability to build a long, short

basket in ARB that is infinitely more

998

:

powerful than the one sided ARB of just

trying to sell something you think is

999

:

expensive or buy something you think

:

00:49:05,101 --> 00:49:05,391

Adam Butler: yeah.

:

00:49:05,551 --> 00:49:08,056

'cause you can hedge the beta

within the security space, right?

:

00:49:08,056 --> 00:49:10,756

But there's nothing to, there's,

nothing to hedge against directly in the

:

00:49:10,881 --> 00:49:12,256

Chris Schindler: and a, it's much slower.

:

00:49:12,256 --> 00:49:15,226

It's much lower breath,

it's a much riskier bet.

:

00:49:15,256 --> 00:49:18,646

It's one of those things that you, you

have to trust that a bunch of other people

:

00:49:18,646 --> 00:49:22,186

are gonna come in alongside with you

over time for it to work on your behalf.

:

00:49:22,651 --> 00:49:25,831

Whereas like in a Stata player, you

can, like, you can almost do it yourself

:

00:49:26,101 --> 00:49:29,881

if you know, so, and it's got a, it's

a very, very different risk profile.

:

00:49:30,137 --> 00:49:33,677

so I think like there's a lot of reasons

why you could think of micro-efficient.

:

00:49:33,857 --> 00:49:36,527

I can also say like, the last three or

four years, like the micro-efficiency

:

00:49:36,527 --> 00:49:39,504

argument seems to have like, you

know, if you get too many people,

:

00:49:39,894 --> 00:49:42,654

uh, you know, you've had a lot

of craziness, uh, uh, intraday.

:

00:49:42,654 --> 00:49:45,774

I mean, like, think about, I think much

of the market's changed in the last

:

00:49:45,774 --> 00:49:49,374

two or three years with, you know, we

were talking about the, the retail,

:

00:49:49,374 --> 00:49:52,584

like player just coming and doing

some crazy, you know, meme stocks.

:

00:49:52,584 --> 00:49:55,134

But you also have like, like what's

happened the last three years.

:

00:49:55,134 --> 00:49:58,374

It's like, I don't, I don't know how

many day traders are still playing with

:

00:49:58,374 --> 00:50:01,314

cash equities versus the ones that are

just playing with like, like massive,

:

00:50:01,344 --> 00:50:02,994

massive size of one day options.

:

00:50:03,534 --> 00:50:07,104

And the the ability for a small player

or a small set of players to come in and.

:

00:50:07,507 --> 00:50:11,767

significantly move the

market is, is changed a lot.

:

00:50:11,772 --> 00:50:14,722

And, and like these, I I don't know why

these things are like, it blows my mind

:

00:50:14,722 --> 00:50:17,242

that these, these are legal because

it just, it feels like if someone came

:

00:50:17,242 --> 00:50:19,822

in and fat fingered the market to the

size of the amount of manipulation,

:

00:50:20,092 --> 00:50:23,092

that's a market manipulation because

you just hammered the market that hard.

:

00:50:23,097 --> 00:50:26,392

But if you went to 10 dealers and you

bought, you know, enough of these things

:

00:50:27,052 --> 00:50:30,442

and then, and then just nudge it, then

suddenly you've got a whole bunch of other

:

00:50:30,442 --> 00:50:34,429

people buying aggressively on your behalf,

bracing each other and, potentially

:

00:50:34,429 --> 00:50:37,566

slamming way more into the market than,

you would ever do as an individual.

:

00:50:37,571 --> 00:50:41,329

And, and you've, just, you've given

like this incredible weapon to, to

:

00:50:41,329 --> 00:50:44,542

a small number of players and it's

been really disruptive at the micro

:

00:50:44,572 --> 00:50:47,162

and at the macro level, uh, you know,

over the last two to three years.

:

00:50:47,162 --> 00:50:49,922

And so you can really see like,

I mean that's changed a lot.

:

00:50:50,264 --> 00:50:50,354

Adam Butler: Yeah.

:

00:50:50,354 --> 00:50:52,904

I mean, you could, you could almost

corner the gamma market the way you

:

00:50:52,904 --> 00:50:55,634

could, you could, you could corner

the silver market back in the.

:

00:50:55,716 --> 00:50:56,916

In the eighties, you

:

00:50:57,081 --> 00:50:58,071

Chris Schindler: Oh, you absolutely have.

:

00:50:58,071 --> 00:51:01,274

I mean, and, and like, I mean the

the whole I mean, vol is, is such an

:

00:51:01,274 --> 00:51:04,394

interesting asset class, but it's changed

so much in the last three or four years.

:

00:51:04,737 --> 00:51:08,554

you know, you've got dealers now who are,

who are stuck, you know, short calls, like

:

00:51:08,554 --> 00:51:10,144

massively like in the market right now.

:

00:51:10,144 --> 00:51:13,327

And, and so, and the same way as,

you know, like when, when you still

:

00:51:13,327 --> 00:51:16,867

think about the and this is, I think

fundamentally, and I think big pension

:

00:51:16,867 --> 00:51:17,827

plans kind of get this wrong too.

:

00:51:17,827 --> 00:51:21,127

And they go like, I'm being very, I'm

being a good, I'm being a good player.

:

00:51:21,127 --> 00:51:24,667

When I, when I, buy a big put because

I, you know, like if the market crashes,

:

00:51:24,667 --> 00:51:25,897

I make this money on the other side.

:

00:51:26,107 --> 00:51:29,151

And what you don't realize is

an option is not really a thing.

:

00:51:29,317 --> 00:51:30,907

you know, you buy equity,

you bought a thing and you

:

00:51:30,907 --> 00:51:31,777

kind of know what you've got.

:

00:51:31,777 --> 00:51:35,137

But an option is kind of a

promise by someone else to

:

00:51:35,137 --> 00:51:36,427

buy and sell on your behalf.

:

00:51:37,027 --> 00:51:39,127

Because when you buy an

option with a dealer.

:

00:51:39,457 --> 00:51:42,391

You know, they have to delta hedge

it and so on the other side of that

:

00:51:42,391 --> 00:51:45,211

trade, if you're, if, if the dealer's

on the wrong side market starts to

:

00:51:45,211 --> 00:51:49,141

rise and they have to buy to cover

that, that, you know, the deltas that

:

00:51:49,141 --> 00:51:52,741

runs away from them, they become a

massive accelerant into the market.

:

00:51:52,746 --> 00:51:54,241

And same thing on the put side.

:

00:51:54,241 --> 00:51:56,701

And so if the dealers get stuck on the

wrong side of that trade, which they

:

00:51:56,701 --> 00:51:59,221

do all the time now, like this is,

like, this has been the last three or

:

00:51:59,221 --> 00:52:00,301

four years, this has been the story.

:

00:52:00,701 --> 00:52:04,031

it, it's just, it's just quite an

incredible, force in the short term.

:

00:52:04,031 --> 00:52:07,931

And it can be an incredible short, and so,

so you can, you can really like see a lot

:

00:52:07,936 --> 00:52:11,291

of market movement when the dealers are on

the wrong side of their gamma exposures.

:

00:52:11,524 --> 00:52:14,134

now they, they've started to reprice

it and they started to figure it out.

:

00:52:14,134 --> 00:52:17,224

But, but it's, it's been a real change

in the market because, I mean, for

:

00:52:17,224 --> 00:52:21,304

the longest time ever it was, you

know, it was priced by puts and, and

:

00:52:21,309 --> 00:52:24,964

you know, as such there was this like

strong negative correlation between

:

00:52:25,024 --> 00:52:28,321

the VIX and the S&P and p and like

that has gone positive at times.

:

00:52:28,321 --> 00:52:31,417

And, and, and, and the whole

relationship between, you know,

:

00:52:31,417 --> 00:52:33,457

vol and market moves is growing.

:

00:52:34,042 --> 00:52:35,962

And, and these one-day

options are super interesting.

:

00:52:36,142 --> 00:52:39,952

Uh, they really transform things, but like

I, I would say that they're taking a ton

:

00:52:39,952 --> 00:52:42,262

away from Microefficiency as we speak.

:

00:52:42,262 --> 00:52:45,082

um, you see how the stat-art guns

are able to pull that together?

:

00:52:45,864 --> 00:52:47,994

Adam Butler: So, Sorry,

Mike, you had looked like you

:

00:52:48,044 --> 00:52:50,169

Mike Philbrick: Oh, I, I think you're

gonna transition, just like I was

:

00:52:50,169 --> 00:52:52,959

thinking, the same thing you've got

if you're transitioning to sort of

:

00:52:52,959 --> 00:52:55,209

strategies and changes in the market

:

00:52:55,284 --> 00:52:58,224

Adam Butler: Yeah, well, I wanted to talk

more broadly about diversification, right?

:

00:52:58,224 --> 00:53:01,344

Like, we, we've done a lot of

that on, on previous episodes.

:

00:53:01,344 --> 00:53:02,994

I, I wanted to really round it out, right?

:

00:53:02,994 --> 00:53:08,291

So, once you sort of, we talk about

stocks, bonds, and inflation, hedge

:

00:53:08,291 --> 00:53:13,804

assets, I, I'd love for you to kinda

rank for me, right, like, what are, what

:

00:53:13,804 --> 00:53:18,829

are some of the other alternative betas

or, premia or whatever that, and I know

:

00:53:18,829 --> 00:53:20,449

it's always a co a continuum, right?

:

00:53:20,454 --> 00:53:24,369

From, beta alpha and, you know, you've

already talked about that a little bit.

:

00:53:24,369 --> 00:53:29,589

But, but how would you kind of rank, where

would you wanna start as you're adding.

:

00:53:29,802 --> 00:53:33,882

You know, completely different flavors

to the portfolio in terms of what

:

00:53:33,882 --> 00:53:36,102

big players can actually allocate to.

:

00:53:36,339 --> 00:53:39,759

you know, with the actual dollar

size of these premia are large enough

:

00:53:39,759 --> 00:53:43,539

for a sufficient number of players

to actually be able to participate.

:

00:53:43,809 --> 00:53:46,749

Like how would you think about,

adding to the diversification

:

00:53:46,749 --> 00:53:48,069

of the portfolio in what order?

:

00:53:48,069 --> 00:53:49,539

If you could, if you could rank

:

00:53:49,559 --> 00:53:49,779

Chris Schindler: Huh.

:

00:53:50,521 --> 00:53:51,391

so I guess there's a couple.

:

00:53:51,511 --> 00:53:55,411

So, so first of all, there's the, there's

the diversification into assets and

:

00:53:55,411 --> 00:53:57,271

there's diversification into strategies.

:

00:53:57,271 --> 00:54:00,234

And even then I would say that

inflation-sensitive, it kind of has to

:

00:54:00,234 --> 00:54:02,214

be in between an asset and the strategy.

:

00:54:02,214 --> 00:54:05,154

I think if you, I think like what you

described as if it was just assets,

:

00:54:05,154 --> 00:54:07,614

then it doesn't do what you needed to

do and people aren't gonna stick with it

:

00:54:07,614 --> 00:54:11,574

because it's, yeah, it'll spike, but we're

talking like once every 10 years or so.

:

00:54:11,574 --> 00:54:13,584

You need it and then you look

like a loser for nine years.

:

00:54:13,584 --> 00:54:16,069

But if you can get strategies that,

that, that actually make money over

:

00:54:16,069 --> 00:54:18,499

time and give you that protection,

you're miles ahead just 'cause

:

00:54:18,499 --> 00:54:19,609

there's so much easier to stick with.

:

00:54:19,609 --> 00:54:19,789

And.

:

00:54:19,994 --> 00:54:25,887

And so, the alternative assets to stocks

and bonds are obviously, you know,

:

00:54:25,887 --> 00:54:27,537

credit and, and then the privates.

:

00:54:27,537 --> 00:54:29,727

And, and we, and that's a

totally separate discussion.

:

00:54:30,357 --> 00:54:31,797

Adam Butler: But are

they alternative assets?

:

00:54:31,797 --> 00:54:32,847

Like do we even need to go there?

:

00:54:32,847 --> 00:54:38,277

Like credit's, you know, credits short

ball at your, it's capital structure?

:

00:54:38,277 --> 00:54:39,091

Like, I don't know.

:

00:54:39,091 --> 00:54:39,781

I've argued on.

:

00:54:40,376 --> 00:54:45,236

Many, many podcasts and in, in

many papers that credits not

:

00:54:45,236 --> 00:54:46,616

even really its own asset class.

:

00:54:46,646 --> 00:54:48,656

And is private equity any

different than equity?

:

00:54:49,721 --> 00:54:52,721

Chris Schindler: so I, uh, I've also

made the exact same argument with credit.

:

00:54:52,751 --> 00:54:56,501

I mean, we, when we first tried to look

at bringing it in as an asset class

:

00:54:56,501 --> 00:54:59,831

at the portfolio level, like once you

cover, it's got an equity risk, it's

:

00:54:59,831 --> 00:55:02,321

got a fixed income risk, it's got a

credit risk, and it's got a shortfall

:

00:55:02,326 --> 00:55:03,551

piece, it's got the illiquidity.

:

00:55:03,791 --> 00:55:07,601

And once you take those pieces out of

it, like as an asset class, it doesn't

:

00:55:07,601 --> 00:55:08,861

bring anything to your portfolio.

:

00:55:09,101 --> 00:55:12,131

But it's actually a very cool asset

class in its own because it's this.

:

00:55:12,476 --> 00:55:14,696

It's not exactly risk parity,

but it's a nice mixture of

:

00:55:14,906 --> 00:55:16,106

four different risk premiums.

:

00:55:16,106 --> 00:55:17,336

So it looks pretty good on its own.

:

00:55:17,666 --> 00:55:21,056

It just doesn't bring as much as people

think it does to a, to a total portfolio.

:

00:55:21,296 --> 00:55:24,656

But it's a, but it's a really

big universe for value add.

:

00:55:25,226 --> 00:55:27,956

And so there's a, there's a lot of room

for value add within credit, and I think

:

00:55:27,961 --> 00:55:30,116

there's a, there's a lot of, so, so is

:

00:55:30,181 --> 00:55:32,396

Adam Butler: I think, you know, the,

the opportunity is to, is take a

:

00:55:32,396 --> 00:55:33,836

little away from the equity, right?

:

00:55:33,836 --> 00:55:35,096

And, and add a little bit to credit.

:

00:55:35,096 --> 00:55:36,956

Acknowledging the credit

gives you some of that equity

:

00:55:37,286 --> 00:55:38,156

Chris Schindler: I mean, from a factor.

:

00:55:38,161 --> 00:55:40,526

So this is, this was like, you know,

this is once again going back to the

:

00:55:40,526 --> 00:55:43,316

work we're doing at teachers, at the

portfolio level, but like from a, we tried

:

00:55:43,316 --> 00:55:46,196

to get things into a factor perspective,

and once you transform into a factor

:

00:55:46,201 --> 00:55:50,512

perspective, you go, like if your factors

are either call it growth and inflation,

:

00:55:50,512 --> 00:55:54,406

you can call it stocks and bonds and,

and some short ball and some illiquidity,

:

00:55:54,706 --> 00:55:57,529

then you've mostly just defined credit.

:

00:55:57,859 --> 00:56:00,619

you know, you've also come pretty

close to defining most of the factors

:

00:56:00,619 --> 00:56:01,849

that are in your privates as well.

:

00:56:01,954 --> 00:56:04,302

and so, you know, when it comes down to.

:

00:56:05,374 --> 00:56:07,024

A little bit of a timeframe.

:

00:56:07,264 --> 00:56:10,474

Uh, you know, privates are,

like they are diversified.

:

00:56:10,474 --> 00:56:13,504

Like they literally, like, they're

definitely diversifying in the short term.

:

00:56:13,504 --> 00:56:18,051

So if you look at your one year, uh, you

know, model privates, they look, they look

:

00:56:18,051 --> 00:56:21,741

really uncorrelated because they're lagged

and because they're smooth and the smooth

:

00:56:21,741 --> 00:56:23,451

means you get to make up their valuations.

:

00:56:23,456 --> 00:56:27,474

And, and in some cases you really just

make up the valuations and they're

:

00:56:27,474 --> 00:56:28,824

lagged because it doesn't matter.

:

00:56:28,974 --> 00:56:30,534

They, they're not in real time anyway.

:

00:56:31,074 --> 00:56:34,427

And so, you know, those two

effects are incredibly helpful

:

00:56:34,432 --> 00:56:36,084

for CIO in the short term.

:

00:56:36,301 --> 00:56:39,961

They're probably not that useful

for a sponsor in the long term.

:

00:56:40,321 --> 00:56:43,591

And so that's a, that's, I call it like a

classic agent management mismatch because

:

00:56:43,591 --> 00:56:45,751

the CIO gets paid on return on risk.

:

00:56:45,751 --> 00:56:48,991

And, you know, anything that cuts risk

that significantly and recently is

:

00:56:48,996 --> 00:56:50,941

doing boosting returns is super helpful.

:

00:56:51,157 --> 00:56:54,067

but it's not necessarily really accretive

to the portfolio in the long term.

:

00:56:54,697 --> 00:56:57,997

Um, so, so that's the, you know, that's

the trade or, or it is in some cases,

:

00:56:58,177 --> 00:57:01,417

and it probably is at a certain size,

it's just probably gets over allocated

:

00:57:01,417 --> 00:57:05,204

to, because it looks artificially,

diversifying and artificially

:

00:57:05,204 --> 00:57:06,494

less risky than it actually is.

:

00:57:06,494 --> 00:57:09,827

And so, from that perspective, it probably

gets over invested to, so illiquidity

:

00:57:09,832 --> 00:57:13,274

in general is probably over invested

in portfolios and it, and it has some

:

00:57:13,279 --> 00:57:16,274

inherent sources of risk as well that,

that you have to be super aware of.

:

00:57:16,827 --> 00:57:19,447

but if we say like, let's set

the assets aside and think about

:

00:57:19,447 --> 00:57:21,937

strategies, my gosh, there's so many.

:

00:57:21,997 --> 00:57:25,541

and, and I think if you're saying, I,

I I, I'm gonna invest in strategies or

:

00:57:25,541 --> 00:57:28,331

I'm gonna invest in man, just creating

strategies, you've gotta, you gotta

:

00:57:28,331 --> 00:57:31,781

split them into, I'm trying to think

about the buckets you put them into.

:

00:57:32,141 --> 00:57:34,721

I mean, obviously, you break 'em

down by asset classes and you

:

00:57:34,721 --> 00:57:35,801

break 'em down by holding period.

:

00:57:35,831 --> 00:57:38,201

I think it's probably

the, the starting point.

:

00:57:38,201 --> 00:57:40,586

And then you say within asset classes

and holding periods, what have you got?

:

00:57:41,292 --> 00:57:42,777

And, know, holding period is.

:

00:57:43,242 --> 00:57:47,052

Particularly important because

it's such a significant source

:

00:57:47,052 --> 00:57:48,656

of diversification, right?

:

00:57:48,656 --> 00:57:53,666

Like if, if you have managers who are

trading intraday, you know, even in and

:

00:57:53,666 --> 00:57:57,506

out a couple times a day, they're for sure

gonna be uncorrelated with your managers.

:

00:57:57,506 --> 00:58:01,286

They're holding for five days or for

10 days or 20 and, and they actually

:

00:58:01,286 --> 00:58:04,166

create, like at the daily level,

it was like a different asset, And

:

00:58:04,166 --> 00:58:07,456

so, from a pure diversification

perspective, that's super helpful.

:

00:58:07,461 --> 00:58:10,546

I mean, you can have a bunch of managers

who are uncorrelated all trading at

:

00:58:10,546 --> 00:58:12,496

the same frequency, let's say 10 days.

:

00:58:13,186 --> 00:58:16,366

Then, you know, if over the long

time, over the long period, you

:

00:58:16,366 --> 00:58:18,226

know, they're, they're, they're doing

different things from each other.

:

00:58:18,226 --> 00:58:21,369

They're gonna look uncorrelated

instantaneously, they're all

:

00:58:21,369 --> 00:58:23,859

either long or short at the same,

at the same time for a given day.

:

00:58:23,859 --> 00:58:26,414

So whatever happens that day, they're

gonna look like they're either, they're

:

00:58:26,414 --> 00:58:27,879

either lost or, or won together.

:

00:58:28,474 --> 00:58:32,739

And, and this is, this is one of the

challenges with diversification over time.

:

00:58:33,249 --> 00:58:36,309

Is that some definition of time,

you don't, you're not diversifying.

:

00:58:36,309 --> 00:58:36,429

Right?

:

00:58:36,429 --> 00:58:39,099

I think we've talked about this before,

but you know, diversification sort of

:

00:58:39,099 --> 00:58:42,562

says if I have two assets that are,

that are uncorrelated, then I get a

:

00:58:42,562 --> 00:58:46,912

square root of two reduction in my

risk, like 1.4 times reduction in my

:

00:58:46,912 --> 00:58:48,562

risk between two uncorrelated assets.

:

00:58:48,567 --> 00:58:50,782

And that happens at

any definition of time.

:

00:58:51,382 --> 00:58:55,129

But if I have two managers that are

uncorrelated over the long term at

:

00:58:55,129 --> 00:58:58,369

any, like, at some definition of time,

they're either both long, the SMP or both

:

00:58:58,374 --> 00:59:01,369

short, the SMP and, and, and, and, and

that's, that's actually not diversifying.

:

00:59:01,374 --> 00:59:02,329

That's a, that's additive.

:

00:59:02,854 --> 00:59:04,802

And, at some definition of time.

:

00:59:04,802 --> 00:59:07,982

So at the one day level or the one hour

level, your managers don't diversify.

:

00:59:07,982 --> 00:59:09,332

They add and subtract to each other.

:

00:59:09,662 --> 00:59:11,822

But over time, that turns

into diversification.

:

00:59:11,822 --> 00:59:15,036

And so, it's, it's very, very

helpful to have managers with that

:

00:59:15,036 --> 00:59:16,086

have different holding periods.

:

00:59:16,621 --> 00:59:20,062

And, you know, if you are building

a multi-strat of managers, that's

:

00:59:20,062 --> 00:59:22,012

probably one of the things you start

to think about, to start with is how

:

00:59:22,012 --> 00:59:22,972

do I get different holding periods?

:

00:59:23,842 --> 00:59:25,672

And, and then what are the strategies?

:

00:59:25,702 --> 00:59:28,402

Well, what are intraday strategies and

what are the risk readings of those?

:

00:59:28,432 --> 00:59:29,902

And, and how do I collect them?

:

00:59:30,526 --> 00:59:32,146

and, and my God, there's,

there's a lot to think about

:

00:59:32,191 --> 00:59:34,191

Adam Butler: And what's the

capacity of intraday too, right?

:

00:59:34,191 --> 00:59:34,661

I mean,

:

00:59:35,261 --> 00:59:35,511

Chris Schindler: what's that?

:

00:59:36,541 --> 00:59:38,671

Adam Butler: you know, not everyone can

allocate the, well, not everyone can

:

00:59:38,671 --> 00:59:42,964

allocate anything, but, but intraday would

be especially difficult for, you know, to

:

00:59:42,964 --> 00:59:46,771

allocate a massive amount of capital to,

or, or to even get a meaningful amount

:

00:59:46,771 --> 00:59:49,577

of risk into for many larger managers.

:

00:59:49,982 --> 00:59:50,582

Chris Schindler: a hundred percent.

:

00:59:50,582 --> 00:59:53,006

So, so it's, extremely hard

from an oversight perspective.

:

00:59:53,011 --> 00:59:55,586

It's, it's hard from a leverage

perspective and capital efficiency

:

00:59:55,586 --> 00:59:57,926

perspective, it's, it's hard to,

from a portfolio construction.

:

00:59:57,926 --> 01:00:00,956

So you see, you see like, um,

multi-managers doing it and

:

01:00:00,956 --> 01:00:02,126

doing it somewhat successfully.

:

01:00:02,706 --> 01:00:05,496

you know, if you think, if you're

a multi-Strat and you've got all a

:

01:00:05,496 --> 01:00:07,746

bunch of these strategies together,

I mean, you think about this for

:

01:00:07,751 --> 01:00:11,526

a second and you go, one of the

massive advantages to a multi-Strat,

:

01:00:11,589 --> 01:00:14,139

especially if they're trading lots of

different models in the same space.

:

01:00:14,832 --> 01:00:15,582

Is netting.

:

01:00:15,642 --> 01:00:19,372

And I don't think, you know, I don't

think it's quite as obvious to people

:

01:00:19,682 --> 01:00:20,852

like what a big advantage that is.

:

01:00:20,852 --> 01:00:23,402

But if you had 10 managers and

at any given point in time, you

:

01:00:23,402 --> 01:00:25,919

know, some are buying S&P and P

and some are selling, well then

:

01:00:25,919 --> 01:00:27,299

you don't get any netting, right?

:

01:00:27,299 --> 01:00:28,374

And, and you what is that worth?

:

01:00:28,379 --> 01:00:32,664

And the answer, it is worth a, a, a

shocking amount because massive amount,

:

01:00:32,664 --> 01:00:35,844

because transaction costs are so

expensive and, and they're such a big

:

01:00:35,844 --> 01:00:38,094

part of, of any, of any trading strategy

:

01:00:38,424 --> 01:00:40,944

Mike Philbrick: Well, especially if

there's a performance fee on top of that,

:

01:00:41,064 --> 01:00:41,574

Chris Schindler: Yeah.

:

01:00:41,754 --> 01:00:42,174

Mike Philbrick: wrong.

:

01:00:42,174 --> 01:00:45,324

You're wrong on one trade and you're

getting 80% of the other trade.

:

01:00:45,564 --> 01:00:45,984

Chris Schindler: yeah.

:

01:00:45,989 --> 01:00:48,634

And, and, and once again,

this is the difference between

:

01:00:48,964 --> 01:00:50,464

cancellation and diversification.

:

01:00:50,464 --> 01:00:53,494

But if you, if you had only two, one

manager's long, the S&P one year and

:

01:00:53,494 --> 01:00:56,074

the other one's short, the S&P the

whole year, that's not diversifying.

:

01:00:56,134 --> 01:00:58,894

That's just you've got no exposure

and you're paying fees of the

:

01:00:58,894 --> 01:01:00,934

a hundred percent certainty,

one side versus the other.

:

01:01:01,234 --> 01:01:02,134

So that's the last thing you want.

:

01:01:02,134 --> 01:01:03,964

You don't want cancellation,

you want diversification.

:

01:01:04,431 --> 01:01:06,999

but if, if you were to

think about like, you know.

:

01:01:07,369 --> 01:01:10,639

let's say, let's say for us, we have like

20 models, and if you look at any one of

:

01:01:10,639 --> 01:01:11,839

these models, there's a couple of things.

:

01:01:11,959 --> 01:01:14,269

There's a couple really interesting

concepts that come into play.

:

01:01:14,756 --> 01:01:17,246

on one hand you could think about

it, you said like, imagine I was

:

01:01:17,246 --> 01:01:19,611

intraday playing and I had lots of

different strategies that came and,

:

01:01:19,736 --> 01:01:23,036

and I was running like a, what we

call a complex event processor, which

:

01:01:23,036 --> 01:01:25,166

is, which is responding in real time.

:

01:01:25,166 --> 01:01:30,626

It says like it's 10 0 2 and your trend

falling model said buy, or it's 10 14,

:

01:01:30,626 --> 01:01:33,536

and this model said do this or it's,

and, and if you just do those, all

:

01:01:33,536 --> 01:01:37,016

those in real time, yeah, you get that

diversification benefit, but what, but

:

01:01:37,021 --> 01:01:40,286

you lose all netting because you've

said, I'm trading this at this time,

:

01:01:40,286 --> 01:01:42,746

and you go and you buy and then an hour

and a half later you trade this one

:

01:01:42,746 --> 01:01:44,336

and, and, and, and, and you're selling.

:

01:01:44,336 --> 01:01:45,656

And, and those don't touch each other.

:

01:01:45,656 --> 01:01:47,726

And so you're paying twice

the transaction costs.

:

01:01:47,982 --> 01:01:50,712

If you can take all those trades

and bring them together and trade

:

01:01:50,712 --> 01:01:52,242

them like say one time a day.

:

01:01:52,737 --> 01:01:55,377

Then by definition, you know, some are

buying, some are selling, and you're

:

01:01:55,377 --> 01:01:58,647

gonna net those guys out and, and you,

and that's, that's, you know, so, so you

:

01:01:58,647 --> 01:02:02,007

connect, so you take trading time and

instead of trading in real time, you,

:

01:02:02,007 --> 01:02:05,307

you, you, you compress that down to one

or two or a certain number of times a day.

:

01:02:05,577 --> 01:02:08,007

Well then you, then, you've

created a netting process.

:

01:02:08,127 --> 01:02:10,227

But the trade off is you're,

you're a bit slower in responding.

:

01:02:10,257 --> 01:02:13,344

So like, the question is like, how do I

trade off the speed of response versus

:

01:02:13,344 --> 01:02:14,934

the, the, the value of this netting.

:

01:02:15,534 --> 01:02:17,004

And you've gotta quantify both of those.

:

01:02:17,004 --> 01:02:19,314

What's my alpha decay, what's

my cost of waiting to do a

:

01:02:19,314 --> 01:02:21,894

trade versus my netting value?

:

01:02:22,284 --> 01:02:23,839

And, and it's, it's quite amazing.

:

01:02:23,844 --> 01:02:26,989

Like for us it's a, it's, it's one

of the assets that you think you have

:

01:02:27,019 --> 01:02:30,139

as a manager is like, if you only

had one process, and let's say it

:

01:02:30,139 --> 01:02:34,202

was a sharp ratio of one, but before

transaction costs and it's making 10%

:

01:02:34,202 --> 01:02:35,972

a year, but your t cost cost 5% a year.

:

01:02:35,972 --> 01:02:37,262

It's like, well, that, you

have to think of that thing

:

01:02:37,262 --> 01:02:39,122

as losing 5% in trading costs.

:

01:02:39,512 --> 01:02:43,132

If you had 20 of those and you

went to bring that, that new one

:

01:02:43,132 --> 01:02:46,009

into your process, you might, like

literally net out something like

:

01:02:46,009 --> 01:02:48,079

75 to 80% of the trading costs.

:

01:02:48,454 --> 01:02:50,374

And so that becomes much more accretive.

:

01:02:50,374 --> 01:02:53,824

And in fact, it's, it's, it's something

that you have when you have like

:

01:02:53,824 --> 01:02:57,357

multi-processes is, kind of this

brand new, call it like an asset,

:

01:02:57,357 --> 01:03:00,267

this new benefit, which is that if I

wanted to run this new process, if I,

:

01:03:00,267 --> 01:03:02,997

if this was, if this was, if I was a

single manager and this was the only

:

01:03:03,002 --> 01:03:05,397

thing I did it may not be feasible.

:

01:03:05,697 --> 01:03:08,577

But when I, when I bring it in and when

I net it with the rest of my process,

:

01:03:08,607 --> 01:03:10,527

like it's T-cost almost disappear.

:

01:03:11,007 --> 01:03:13,107

And it's a bit of a function of

how big it is and how it turns and

:

01:03:13,107 --> 01:03:14,277

how it trades with the other stuff.

:

01:03:14,282 --> 01:03:17,817

But like it's, it's quite amazing how much

of this T-cost can, can diversify away

:

01:03:18,147 --> 01:03:20,307

or just disappear into, into the process.

:

01:03:20,692 --> 01:03:23,542

Adam Butler: So this raises

another, another, quandary,

:

01:03:23,609 --> 01:03:24,659

which we also struggle with.

:

01:03:24,689 --> 01:03:26,519

'cause we also obviously run multi-strats.

:

01:03:26,519 --> 01:03:28,739

But, so you've got all

these different strategies.

:

01:03:28,739 --> 01:03:31,216

They, you know, even if you're,

if you're trading 'em all at the

:

01:03:31,216 --> 01:03:35,086

same time, so you obviously you're

maximizing the netting effect with that.

:

01:03:35,386 --> 01:03:38,736

But, attribution gets really tough, right?

:

01:03:38,736 --> 01:03:41,856

So you've got different strategies

that on their own, for example,

:

01:03:42,156 --> 01:03:46,356

may not be particularly accretive,

but when you trade them with other

:

01:03:46,361 --> 01:03:50,406

strategies because of the trade

netting effects and the diversification

:

01:03:50,406 --> 01:03:51,786

you get within the portfolio.

:

01:03:52,186 --> 01:03:57,526

it's highly accretive, but then you've

got an investor who wants to know where

:

01:03:57,526 --> 01:04:00,766

you generated your returns from, right?

:

01:04:01,036 --> 01:04:04,786

You could, you could obviously describe

that at the market level very easily,

:

01:04:04,949 --> 01:04:09,479

but going one level below the market

level into the model level or the

:

01:04:09,479 --> 01:04:14,909

strategy level, that gets really hard,

Because you don't know on a net basis

:

01:04:14,969 --> 01:04:18,779

how each of these constituents has

contributed to the overall process.

:

01:04:18,779 --> 01:04:19,889

How do you guys think about that?

:

01:04:20,714 --> 01:04:23,384

Chris Schindler: So I guess there's a

couple, there's a couple points there.

:

01:04:23,479 --> 01:04:28,411

The, if you, if you do everything in gross

space, if you do all your models, you say

:

01:04:28,411 --> 01:04:31,681

like, I'm just gonna take t-cost as this

thing that's charged at the very end.

:

01:04:32,281 --> 01:04:34,951

Instead of trying to attribute it back

to the models, you can at least describe

:

01:04:34,951 --> 01:04:39,061

what the, what the end of it like model,

process was before transaction costs.

:

01:04:39,286 --> 01:04:39,811

Adam Butler: Yeah, the growth.

:

01:04:40,021 --> 01:04:42,841

Chris Schindler: you can't, there's no

way to take that final t-cost and give it

:

01:04:42,841 --> 01:04:47,191

back to individual models or, or you're

wildly overestimating transaction costs.

:

01:04:47,196 --> 01:04:48,691

And, and I don't think

that makes a lot of sense.

:

01:04:49,284 --> 01:04:52,674

it gets even more complicated if you're

doing anything on top of the models,

:

01:04:52,674 --> 01:04:56,754

like any kind of portfolio construction,

uh, which, which we do, right?

:

01:04:56,754 --> 01:05:00,174

So, so, and then, then it's like,

well, like, I like to let my models

:

01:05:00,174 --> 01:05:03,251

run independently, but every now and

then if, if every single one of 'em

:

01:05:03,251 --> 01:05:05,891

is long equities today, I'm gonna say,

I'm like, I'm not sure I'm gonna bet

:

01:05:05,891 --> 01:05:09,191

20 times as much equities when just

because all 20 models like it, it's

:

01:05:09,191 --> 01:05:10,541

very unfrequent and very unlikely.

:

01:05:10,541 --> 01:05:11,111

But yeah.

:

01:05:11,711 --> 01:05:15,457

And so there's gonna be, a point in

time when you, when you're gonna lean

:

01:05:15,457 --> 01:05:17,047

against the, that aggregate decision.

:

01:05:17,047 --> 01:05:19,957

And, and maybe that should come

at a, a negative expected cost.

:

01:05:19,957 --> 01:05:21,096

You're leaning against the alpha process.

:

01:05:21,102 --> 01:05:23,317

But, but hopefully it's a creative

on the risk side because like

:

01:05:23,317 --> 01:05:25,627

there are occasional times when

you know when it wants to do that

:

01:05:25,627 --> 01:05:26,887

and you go, those are super risky.

:

01:05:26,892 --> 01:05:29,377

Like if something happens in the market

that one day you could, you could

:

01:05:29,377 --> 01:05:30,697

have a really good or really bad day.

:

01:05:31,297 --> 01:05:32,437

Uh, but it's pretty random.

:

01:05:32,857 --> 01:05:35,617

And so, you know, we, you know,

we say, well, we've got aggregate

:

01:05:35,617 --> 01:05:36,577

risk that we're trying to control.

:

01:05:36,577 --> 01:05:39,577

And now, and now you're at the level

of, I'm, I'm mixing models, I'm

:

01:05:39,577 --> 01:05:44,047

netting models, I've got overlays

on, on aggregate risk, and how do

:

01:05:44,052 --> 01:05:45,397

I assign those back to the models?

:

01:05:45,397 --> 01:05:46,237

And you just can't.

:

01:05:46,652 --> 01:05:51,581

And, and so the best you can do is,

is, I say, is talk about the models in,

:

01:05:51,807 --> 01:05:56,617

growth space and then, and then describe

these layers and, and speak 'em almost

:

01:05:56,617 --> 01:05:58,311

as if they're models themselves, right?

:

01:05:58,311 --> 01:06:01,901

This is a transformation process and,

and this transformation process, it

:

01:06:01,901 --> 01:06:05,351

transformed risk this way and it, and

it cost us, or it added this value.

:

01:06:05,666 --> 01:06:07,916

And think of it as a, as

a process That's a yield.

:

01:06:07,971 --> 01:06:11,211

It's, it's in there because you

think it's utility or creative.

:

01:06:11,211 --> 01:06:13,596

And, and then you always have to just

pay attention to how much risk is in

:

01:06:13,596 --> 01:06:15,486

that thing relative to these things.

:

01:06:15,486 --> 01:06:17,826

And, and, and in terms of the utility

that you're trying to provide from it.

:

01:06:17,856 --> 01:06:21,169

'cause it's from a, if you think of it

as a, you know, either Sharpe ratio or

:

01:06:21,169 --> 01:06:25,221

utility enhancer, it's, it's gotta be,

it is gotta be either reducing risk or

:

01:06:25,227 --> 01:06:27,862

improving return or improving utility

in some way that makes it creative.

:

01:06:28,387 --> 01:06:28,507

Adam Butler: Yeah.

:

01:06:28,537 --> 01:06:31,867

And then you're also, you're constrained

in your ability to articulate the

:

01:06:31,867 --> 01:06:34,027

value of that trade netting too, right?

:

01:06:34,027 --> 01:06:37,601

Like, it's actually important to be

able to demonstrate, yeah, you could

:

01:06:37,601 --> 01:06:41,705

have owned five different funds with

this, with similar exposures, but your

:

01:06:42,274 --> 01:06:46,461

net return would be expected to be sort

of 40% lower because you're not taking

:

01:06:46,461 --> 01:06:47,821

advantage of, of this trade netting.

:

01:06:47,836 --> 01:06:52,476

But you, you know, articulating that

in a, in any sort of defensible,

:

01:06:52,476 --> 01:06:55,012

quantifiable way is also very difficult.

:

01:06:55,012 --> 01:06:59,199

And then, while you can communicate

this to institutional investors or, you

:

01:06:59,199 --> 01:07:04,119

know, accredited or qualified investors,

then you can't communicate any of this

:

01:07:04,269 --> 01:07:09,069

extra context or color to non-accredited

or non-qualified investors, right, who

:

01:07:09,069 --> 01:07:14,246

always operate at a, a, major disadvantage

to qualified investors who are able to

:

01:07:14,246 --> 01:07:18,026

then provide all this extra color, even

though it's actually a possible, from

:

01:07:18,026 --> 01:07:23,156

an accounting standpoint to describe

the accretion from all these different

:

01:07:23,156 --> 01:07:27,619

strategy sleeves that are trading the same

markets within the same, the same account.

:

01:07:28,609 --> 01:07:29,269

Chris Schindler: Yeah.

:

01:07:29,419 --> 01:07:31,669

Adam Butler: it introduces all of

these different complexities for

:

01:07:31,674 --> 01:07:34,489

different classes of investors

that I think are counterproductive.

:

01:07:35,089 --> 01:07:35,538

Chris Schindler: Yeah.

:

01:07:35,538 --> 01:07:39,482

I, I mean, I think you can make

a statement of, if I had no

:

01:07:39,482 --> 01:07:42,842

turnover control and no netting,

my trading costs would be X..

:

01:07:42,846 --> 01:07:46,442

And, and you can, and like we can do that

calculation that's like, imagine I, I,

:

01:07:46,442 --> 01:07:49,742

these are independent managers and, and

you charge a T cost assumption dollar

:

01:07:49,747 --> 01:07:51,602

and you go, boom, what's your number?

:

01:07:51,737 --> 01:07:52,967

Adam Butler: it's, it's an estimate,

:

01:07:53,221 --> 01:07:53,971

Chris Schindler: It's always an estimate.

:

01:07:54,122 --> 01:07:55,592

It, it trading costs.

:

01:07:55,622 --> 01:07:59,366

It, like, when it comes right down

to anytime you do any kind of trade

:

01:07:59,371 --> 01:08:03,056

cost attribution, uh, you're gonna be

estimating at, at that point, at, if

:

01:08:03,056 --> 01:08:05,396

you're gonna try and put it back to

models, you're gonna try and do anything.

:

01:08:05,666 --> 01:08:07,946

You have your actual, this is

the amount we actually paid.

:

01:08:08,576 --> 01:08:12,296

and, and, and and then anything else as an

attribution back is gonna be an estimate.

:

01:08:12,611 --> 01:08:16,076

But you can start with like, I mean,

and we do do this and, and so it's a,.

:

01:08:16,076 --> 01:08:18,026

If we had no netting,

what would our T cost be?

:

01:08:18,055 --> 01:08:19,435

And with netting, what's our T costs?

:

01:08:19,435 --> 01:08:22,975

And it's really interesting because

it's the, what is the incremental

:

01:08:22,975 --> 01:08:25,435

transaction cost associated

with adding this new model?

:

01:08:25,435 --> 01:08:29,156

And you have to say like if we, and,

even then, like adding new models,

:

01:08:29,156 --> 01:08:31,406

people always get this wrong, but you

go like, I'm expecting this model to

:

01:08:31,406 --> 01:08:34,316

make $10 million because I'm gonna put

this much and expect the Sharpe ratio of

:

01:08:34,316 --> 01:08:36,356

one, but it, it doesn't work that way.

:

01:08:36,356 --> 01:08:36,506

Right?

:

01:08:36,506 --> 01:08:40,376

It's like when you add a new model, unless

you take your risk up, the new model

:

01:08:40,376 --> 01:08:42,591

doesn't get to make it standalone money.

:

01:08:42,591 --> 01:08:45,291

It's just, it's just how much did it

improve your expected Sharpe ratio?

:

01:08:45,770 --> 01:08:48,804

Because, if it, if it only takes your

risk up by, by, you know, 1% when you

:

01:08:48,804 --> 01:08:52,314

gotta shrink the rest of the process

by 1% to, keep the same risk target

:

01:08:52,689 --> 01:08:55,294

and you know, whatever it's suspected

to make comes out the other side.

:

01:08:55,294 --> 01:08:57,274

And so it's really, it always

comes down to how much does

:

01:08:57,279 --> 01:08:58,533

improve your expected Sharpe ratio.

:

01:08:59,112 --> 01:09:03,312

And you can also say, if I was

running this amount of money, here's

:

01:09:03,312 --> 01:09:04,992

the total dollars I'd pay in t-cost.

:

01:09:04,992 --> 01:09:07,992

And if I was just running this model

alone, here's the dollars I pay in t-cost.

:

01:09:07,997 --> 01:09:11,261

And when I add them together at the same

risk, what does my dollars in t-cost?

:

01:09:11,261 --> 01:09:13,782

And it's interesting 'cause occasionally

you can add models that are, that

:

01:09:13,787 --> 01:09:16,062

have quite high turnover and you can

add 'em to the whole process and your

:

01:09:16,067 --> 01:09:19,482

transaction costs come down and it has

a little bit to do with the size of the

:

01:09:19,482 --> 01:09:20,742

model versus the stuff you're doing.

:

01:09:20,742 --> 01:09:22,782

It has a lot to do with what

is the model buying when the

:

01:09:22,782 --> 01:09:23,652

rest of your stuff is buying.

:

01:09:23,742 --> 01:09:27,448

And, and so, you know, if it's truly

uncorrelated, you know, it might add

:

01:09:27,448 --> 01:09:30,479

incrementally or it might take away

because every single time that the

:

01:09:30,479 --> 01:09:33,702

rest of the process is buying and this

guy's either buying or selling, you

:

01:09:33,702 --> 01:09:36,372

save some transaction costs on this,

but you also save it on this one.

:

01:09:36,822 --> 01:09:39,015

And so you, you can,

it it is quite amazing.

:

01:09:39,015 --> 01:09:43,276

But bringing stuff in that turns over

quite high can take your transactions

:

01:09:43,276 --> 01:09:47,716

down and, and suddenly you go, that's a,

that's a huge benefit to a multi-strap.

:

01:09:47,746 --> 01:09:48,616

I think it's a huge benefit.

:

01:09:48,831 --> 01:09:50,716

Mike Philbrick: Well, if you, if you

think about it, you're, you're adding

:

01:09:50,746 --> 01:09:55,516

a model that has a trading frequency

and that frequency isn't going to be

:

01:09:55,521 --> 01:10:00,346

more, or it's unlikely to be more than

all of the other existing models within

:

01:10:00,346 --> 01:10:02,026

the portfolio at that moment in time.

:

01:10:02,617 --> 01:10:04,532

Is that, am I kind of getting that right?

:

01:10:04,532 --> 01:10:09,062

So you've got this high transaction

model and you've got 20 models over here.

:

01:10:09,529 --> 01:10:14,089

It's unlikely that that one model trades

at a more rapid frequency than all of

:

01:10:14,094 --> 01:10:17,256

the other models, and then it helps

inform those other models on their

:

01:10:17,276 --> 01:10:18,831

Adam Butler: If you're not

accounting for the averaging,

:

01:10:19,211 --> 01:10:22,296

Chris Schindler: So it, it could

trade more rapidly than your average.

:

01:10:22,356 --> 01:10:25,386

it has to do with how big it is relative

to your average, because if you've got

:

01:10:25,446 --> 01:10:28,326

10 or 15 and, and like at any given

point in time, some are buying, there's,

:

01:10:28,776 --> 01:10:29,796

call it like the lightest level.

:

01:10:29,796 --> 01:10:32,309

There's a 50% chance that, the rest

of your guys are doing is in the

:

01:10:32,309 --> 01:10:33,269

opposite direction with this guy.

:

01:10:33,479 --> 01:10:36,419

So like, straight up the bat, if

it's small enough, you can come

:

01:10:36,419 --> 01:10:38,619

pretty close to 50% of, of coverage.

:

01:10:39,106 --> 01:10:41,216

But that's just what

this covers of this guy.

:

01:10:41,546 --> 01:10:44,156

Every time you do that, this guy

covers some of this one as well.

:

01:10:44,156 --> 01:10:46,346

And so like that comes right

back on the other side.

:

01:10:46,346 --> 01:10:48,896

And so if you realize the total

savings, it's both of those

:

01:10:48,896 --> 01:10:50,516

together, you can get to 75, 80%.

:

01:10:50,516 --> 01:10:55,202

And so it's a, it's a pretty interesting

reduction, meaning that you go, if you

:

01:10:55,232 --> 01:10:59,042

found, if you found these five processes

and five different managers and they're

:

01:10:59,042 --> 01:11:02,956

each a sharp ratio one, but like they

lose 5% in trading costs when you bring

:

01:11:02,956 --> 01:11:06,316

'em all together, or if you bring 20 of

these guys together, these incremental

:

01:11:06,316 --> 01:11:10,306

managers are only, are, are coming

at like 20% of, of, of the turnover.

:

01:11:10,486 --> 01:11:12,256

Which, which is, which is just incredible.

:

01:11:12,346 --> 01:11:15,526

And so it's not, we're not talking

about the diversification of the alpha.

:

01:11:15,676 --> 01:11:16,456

We're talking like that.

:

01:11:16,516 --> 01:11:19,846

In addition to that is this

massive reduction in cost.

:

01:11:19,846 --> 01:11:23,302

which, which is what you can see is

like, the, and this is where, you know,

:

01:11:23,812 --> 01:11:26,422

like if you have these, I don't know,

like a medallion, like who's, who knows

:

01:11:26,427 --> 01:11:29,512

what they're up to, but assume that

they're doing a ton of short-term stuff.

:

01:11:30,077 --> 01:11:33,041

and the danger with, with, individual

short-term stuff, once again, as we said,

:

01:11:33,041 --> 01:11:35,707

is that, you don't get your netting,

but if you do enough of it and then you

:

01:11:35,707 --> 01:11:40,481

can aggregate it carefully into slices,

you could probably get a ton of netting

:

01:11:40,481 --> 01:11:42,221

and just incredible diversification.

:

01:11:42,221 --> 01:11:44,794

So, and so, time diversification

is super important.

:

01:11:44,824 --> 01:11:46,954

And, and all of this was just to

say like, if I was putting together

:

01:11:46,954 --> 01:11:49,961

a multi-Strat, you gotta think

about the different feature sets

:

01:11:49,961 --> 01:11:50,891

that you're diversifying across.

:

01:11:50,891 --> 01:11:53,051

And so you're diversifying

across strategies and across

:

01:11:53,056 --> 01:11:54,071

assets and across time.

:

01:11:54,071 --> 01:11:56,384

And that's the three major distinctions.

:

01:11:56,384 --> 01:11:59,564

And to all of that across strategies

and time, you've got this netting

:

01:11:59,564 --> 01:12:02,024

thing to think about, or even

assets and strategies and time.

:

01:12:02,024 --> 01:12:03,524

You've got this netting

consideration, which is, which

:

01:12:03,524 --> 01:12:04,484

is an important consideration.

:

01:12:04,984 --> 01:12:06,844

Um, and I went way off

track on your question.

:

01:12:06,844 --> 01:12:09,874

but, and then you say, what

are the big categories?

:

01:12:09,934 --> 01:12:14,434

And, so at the, global macro level,

you know, if you, you've got your.

:

01:12:14,629 --> 01:12:16,489

Broadly speaking, you've got your carries.

:

01:12:16,489 --> 01:12:20,332

And so, you know, obviously like most

fixed income models start with, relative

:

01:12:20,332 --> 01:12:23,752

or absolute carries, and whether they're

risk-based or not is a big question.

:

01:12:23,752 --> 01:12:25,282

If they're not risk-based, then

you're still gonna end up with

:

01:12:25,282 --> 01:12:26,242

a bunch of betas underneath it.

:

01:12:26,242 --> 01:12:29,872

But like, you know, some concept of

carries, like, like obviously FX carries

:

01:12:29,872 --> 01:12:31,282

a really big and well-known strategy.

:

01:12:31,782 --> 01:12:33,792

you've got your carries, you've

got the values, you've got the

:

01:12:33,792 --> 01:12:36,642

qualities, and you've got momentum,

and then you've got the volatilities.

:

01:12:36,672 --> 01:12:39,102

And I think broadly speaking,

that captures a lot of 'em.

:

01:12:39,107 --> 01:12:43,092

And you can capture that, that set,

in all of your major asset classes.

:

01:12:43,509 --> 01:12:47,589

Then you have, you know, like the other

ones like merger arbitrage, classic

:

01:12:47,589 --> 01:12:50,929

risk premium where it's, it like the

classic definition of risk premium

:

01:12:50,934 --> 01:12:53,782

where it's like, you know, like someone

owns a company, you know, it's trading

:

01:12:53,782 --> 01:12:56,859

at 20 and, you hear that there's a,

there's a merger announced and it

:

01:12:56,889 --> 01:12:59,349

immediately pops to something and you

go, what, what does it popped here?

:

01:12:59,611 --> 01:13:01,831

and like obviously a lot of people spend

a lot of time thinking what they think

:

01:13:01,831 --> 01:13:06,391

it should, it should go to, but it, goes

to, it used to be a company that's prices

:

01:13:06,391 --> 01:13:10,254

moved, you know, based on earnings and it

had a beta and, and suddenly what you own

:

01:13:10,254 --> 01:13:12,264

for a brief period of time is a coin flip.

:

01:13:12,264 --> 01:13:15,774

And it's a coin flip on the probability of

this merger going through the price popped

:

01:13:15,774 --> 01:13:19,854

from 20 to 30 and if the merger doesn't go

through, I guess it goes back down to 20.

:

01:13:19,854 --> 01:13:22,434

If it goes through, it goes to

something, it's, that's usually a

:

01:13:22,434 --> 01:13:24,024

posted price that maybe it's 40.

:

01:13:24,234 --> 01:13:26,094

And you go, why is it

trading at 30 and not 40?

:

01:13:26,094 --> 01:13:28,764

It's like, well, there's an implied

probability of this deal going through.

:

01:13:29,034 --> 01:13:33,917

And so what you own briefly, you've

just made 20, do you, it was at 20

:

01:13:33,917 --> 01:13:36,707

a day ago, now it's at 30 and now

you own this thing, which is no

:

01:13:36,707 --> 01:13:38,087

longer a stock, it's a coin flip.

:

01:13:38,459 --> 01:13:39,714

and you said, I don't want a coin flip.

:

01:13:39,714 --> 01:13:42,864

I don't wanna like make or

lose $10 on this thing that I

:

01:13:42,869 --> 01:13:43,734

have no understanding about.

:

01:13:43,734 --> 01:13:46,344

And I'm gonna ask someone else, like,

someone else can take that trade on from

:

01:13:46,344 --> 01:13:47,693

me and they can own that and diversify.

:

01:13:47,693 --> 01:13:48,474

And I want out.

:

01:13:48,684 --> 01:13:49,494

It's a classic risk-free.

:

01:13:49,499 --> 01:13:51,654

So someone else will take on,

they say, I'm gonna, I'm gonna.

:

01:13:52,149 --> 01:13:54,309

I'm gonna buy these things and I'm

gonna, I'm gonna bet that there's a

:

01:13:54,309 --> 01:13:57,949

certain probability of default and, a

certain, probably this thing failing.

:

01:13:57,949 --> 01:14:00,259

I mean, and, and a certain

probably going through.

:

01:14:00,259 --> 01:14:02,059

And I'm gonna price and

size this thing correctly.

:

01:14:02,119 --> 01:14:05,568

And so that was, you know, merge arbitrage

is, is a very classic risk premium.

:

01:14:05,952 --> 01:14:08,652

and, and like, I think a beautiful

one, if it's done well, where, where

:

01:14:08,652 --> 01:14:11,682

I always saw it done badly is on

the portfolio construction side.

:

01:14:11,832 --> 01:14:14,492

Because like, like anything else, people

would tend to screw it up and market cap

:

01:14:14,492 --> 01:14:17,702

weight it and they go, the size of the

deal would dictate how much what I owned.

:

01:14:17,942 --> 01:14:20,882

And the last thing you want when you're

flipping coins is to bet a thousand

:

01:14:20,882 --> 01:14:23,252

times more here and then bet because,

because at the end of the day, that's

:

01:14:23,252 --> 01:14:26,409

gonna catch you, uh, one day because the

only thing that matters is the big one.

:

01:14:26,409 --> 01:14:28,659

And then the other thing to understand

is that if you have a whole portfolio

:

01:14:28,659 --> 01:14:30,939

lease, you have a, a growing data risk.

:

01:14:31,257 --> 01:14:34,507

We saw this in oh eight, if the market

crashes or if you have a credit crisis

:

01:14:34,507 --> 01:14:37,417

or something happens, then all these

deals, which you think are independent

:

01:14:37,417 --> 01:14:39,367

coin flips, can suddenly be very

highly correlated with each other.

:

01:14:39,372 --> 01:14:41,857

And so that's like you have

in the background, a tail beta

:

01:14:41,857 --> 01:14:43,357

risk in merge arbitrage as well.

:

01:14:43,631 --> 01:14:47,057

but like, a great risk for you to, to

add if you can, if you can find it.

:

01:14:47,394 --> 01:14:49,914

and I really ran through

like the, like quality.

:

01:14:50,511 --> 01:14:54,157

there's so many different definitions

of quality in across asset classes.

:

01:14:54,162 --> 01:14:55,027

Within asset classes.

:

01:14:55,027 --> 01:14:56,407

Like that's a very broad statement.

:

01:14:56,797 --> 01:14:57,847

Uh, same thing with value.

:

01:14:58,297 --> 01:14:59,172

Adam Butler: Across asset classes.

:

01:14:59,977 --> 01:15:02,617

Chris Schindler: so I would say

maybe not across asset classes.

:

01:15:02,617 --> 01:15:04,927

It's probably better to think of

it across sectors within equities,

:

01:15:04,927 --> 01:15:07,019

but it's a, um, if you think of.

:

01:15:07,517 --> 01:15:09,767

Yeah, I think like, I guess

you, you would not, you wouldn't

:

01:15:09,767 --> 01:15:11,207

do a cross sectional quality.

:

01:15:11,207 --> 01:15:13,097

What you would like, the

best you would have is a time

:

01:15:13,097 --> 01:15:14,327

series definition of quality.

:

01:15:14,327 --> 01:15:16,997

And then if you had like a, a

variety of asset classes with a time

:

01:15:16,997 --> 01:15:18,317

sectional definition of quality.

:

01:15:18,317 --> 01:15:20,537

Some are higher, some are lower at

any given point in time, and you can

:

01:15:20,542 --> 01:15:21,917

kind of think of that as a relative.

:

01:15:22,277 --> 01:15:24,047

You could even risk that

guy if you wanted to.

:

01:15:24,317 --> 01:15:26,747

And we actually do have one

model that that does that.

:

01:15:27,017 --> 01:15:29,867

But, but it's like that, that

it, it's a very sloppy definition

:

01:15:29,867 --> 01:15:31,037

of cross sectional quality.

:

01:15:31,037 --> 01:15:34,397

but it's, you know, like a series of

time series definitions brought together.

:

01:15:34,517 --> 01:15:37,097

We'll have it all around our

weight, across sectors and,

:

01:15:37,097 --> 01:15:38,387

and of a quality definition.

:

01:15:38,772 --> 01:15:42,524

Um, you know, and then, so we got,

think about FX for a second and say

:

01:15:42,524 --> 01:15:46,564

like, the major risk periods and

effects would be momentum value.

:

01:15:46,686 --> 01:15:47,376

Carry.

:

01:15:47,436 --> 01:15:51,246

And then, maybe some definition like, like

country, like, whether they, whether they

:

01:15:51,246 --> 01:15:52,626

sit in value or not, like value quality.

:

01:15:52,631 --> 01:15:55,201

And that would be kind of like a,

a throw-together concept there.

:

01:15:55,531 --> 01:15:58,021

But that, like even that, that

three-legged stool in FX is a

:

01:15:58,026 --> 01:15:59,371

pretty powerful starting spot.

:

01:15:59,641 --> 01:16:01,411

and then you always got your vol and so

:

01:16:01,586 --> 01:16:03,736

Adam Butler: value would be sort

of like per relative to purchasing

:

01:16:03,736 --> 01:16:04,786

power parity kind of thing.

:

01:16:05,191 --> 01:16:06,751

Chris Schindler: that, that's

a very weak definition.

:

01:16:06,751 --> 01:16:06,841

Yeah.

:

01:16:07,046 --> 01:16:07,336

Yeah.

:

01:16:07,891 --> 01:16:11,011

That's a good starting point and, and a

surprisingly decent starting point of a

:

01:16:11,016 --> 01:16:13,201

long-term definition of value in, in, FX.

:

01:16:13,681 --> 01:16:15,441

and then if you think about, credit.

:

01:16:15,791 --> 01:16:19,258

So credit, credit still has

like, well, credit's complicated.

:

01:16:19,258 --> 01:16:22,498

'cause as we said, it's, it's a mixture

of things, but you know, credit's gonna

:

01:16:22,503 --> 01:16:23,728

have a term structure piece to it.

:

01:16:23,728 --> 01:16:25,228

It's going and like the credit.

:

01:16:25,424 --> 01:16:28,574

So the interesting, when we first started

trying to think about, and this is like

:

01:16:28,579 --> 01:16:31,844

back to:

bringing credit to the portfolio level.

:

01:16:31,844 --> 01:16:34,724

But way back before we were talking

about bringing into our risk parity.

:

01:16:34,954 --> 01:16:36,934

and so we were building our risk

parity as a mixture of stocks and

:

01:16:36,934 --> 01:16:39,934

bonds and commodities and, and

strategies across all these non-assets.

:

01:16:40,414 --> 01:16:42,994

And, and when it came time to

look at credit, we found credit

:

01:16:42,999 --> 01:16:44,554

is a super weird asset class.

:

01:16:44,964 --> 01:16:50,144

especially if you're staring at, IG

and this is back in:

:

01:16:50,144 --> 01:16:53,193

we were looking at it going, it's

really weird because if you just

:

01:16:53,193 --> 01:16:57,081

invest in, in investment grade, if you

look at the returns of that process

:

01:16:57,081 --> 01:16:58,941

over time, they're not very good.

:

01:16:59,458 --> 01:17:01,948

But meanwhile, if you go to the

academic literature at the time it

:

01:17:01,948 --> 01:17:04,318

was literally saying like, we don't

understand what's going on with credit.

:

01:17:04,407 --> 01:17:06,028

Why does credit pay so much?

:

01:17:06,478 --> 01:17:09,238

Like it's if the credit spread

is paying more than it should.

:

01:17:09,243 --> 01:17:11,281

And, and, and there was this

massive disconnect between

:

01:17:11,281 --> 01:17:12,241

what the academics were saying.

:

01:17:12,241 --> 01:17:15,481

Like, look, if you look at company

by company, look how much, look

:

01:17:15,486 --> 01:17:17,731

at the probability default and

look at the actual defaults and

:

01:17:17,736 --> 01:17:18,481

look what they're getting paid.

:

01:17:18,486 --> 01:17:21,511

And like this is like, we can't

explain why the spread is so rich.

:

01:17:21,871 --> 01:17:24,811

Meanwhile, the people investing

in credit are making very little.

:

01:17:25,576 --> 01:17:27,556

And, and it was super unusual.

:

01:17:28,103 --> 01:17:32,266

And it turns out the disconnect was

most people when they invest in credit

:

01:17:32,266 --> 01:17:34,659

are, you know, for the same reason

that you'd see that, like the bond

:

01:17:34,659 --> 01:17:36,669

investors, they're trying to get

some duration and they're sitting

:

01:17:36,669 --> 01:17:37,898

at the back end of the credit curve.

:

01:17:38,529 --> 01:17:42,489

And if you, if you're sitting like

I own credit, I, I buy a ten-year

:

01:17:42,489 --> 01:17:45,309

bond and then maybe by the time such

as seven, I roll it back out to 10.

:

01:17:45,309 --> 01:17:48,009

And if you're doing that sort of seven to

10 rolling out process, which is where the

:

01:17:48,009 --> 01:17:52,209

vast majority of people sit, you capture

almost none of the credit risk premium.

:

01:17:52,866 --> 01:17:55,186

it's, you get all the risk

and almost none of the fun.

:

01:17:55,216 --> 01:17:57,046

I mean, the sharp ratio

there is, is almost nothing.

:

01:17:57,706 --> 01:18:00,706

But if you hold credit right through

the maturity, which means that you're

:

01:18:00,706 --> 01:18:03,466

holding companies that live with one to

two years of default and, and, and the

:

01:18:03,466 --> 01:18:06,136

other default that they don't, it's a very

different structure where if you hold it,

:

01:18:06,136 --> 01:18:07,666

that's where the all the sharp ratio is.

:

01:18:07,666 --> 01:18:09,466

And you go, that's super weird.

:

01:18:09,646 --> 01:18:12,826

And then once again, it was like early on

in our research going, that's this clearly

:

01:18:12,826 --> 01:18:15,689

a leverage issue because to get the amount

of risk that you need and to get the

:

01:18:15,689 --> 01:18:18,976

exposure you need and the cash that you

need to hold the stuff at the front end.

:

01:18:19,391 --> 01:18:23,839

like very few people hold bonds

right through to, they either like,

:

01:18:23,864 --> 01:18:25,214

like right through to time zero.

:

01:18:25,364 --> 01:18:27,314

But if you do, that's where

all the Sharpe ratio is.

:

01:18:27,704 --> 01:18:29,084

You go, why is everyone out here?

:

01:18:29,534 --> 01:18:30,974

And it's like, oh, there's two reasons.

:

01:18:30,979 --> 01:18:33,193

And the first one is like, and

they're both classic credit reasons.

:

01:18:33,193 --> 01:18:35,443

And the first one is the vast majority

of credit players who are just rolling

:

01:18:35,443 --> 01:18:37,394

this process out thinking they're

collecting the risk premium because

:

01:18:37,394 --> 01:18:40,228

they're taking the risk without knowing

that, that, there's this massive in

:

01:18:40,233 --> 01:18:43,138

the curve because you've got these

people selling here and buying here.

:

01:18:43,521 --> 01:18:46,668

And at the other side is like, it

turns out that the credit curve is,

:

01:18:46,728 --> 01:18:49,938

is the discount curve for corporate

liability for pension plans.

:

01:18:50,388 --> 01:18:52,668

And so if you want to immunize

your pension plan, that's

:

01:18:52,668 --> 01:18:53,958

the piece you have to hold.

:

01:18:54,168 --> 01:18:56,358

It's like, well you should never

be investing in a space where

:

01:18:56,358 --> 01:18:59,318

people are forced to be investors

because that's gonna be a very

:

01:18:59,318 --> 01:19:01,838

naturally crowded, it's the last

place in the world you want to be.

:

01:19:01,838 --> 01:19:04,538

But the vast majority of people playing

credit at the time were out there at the

:

01:19:04,543 --> 01:19:07,657

back end of the curve where there was just

like no Sharpe ratio and all the risk.

:

01:19:07,968 --> 01:19:10,313

Adam Butler: It's like the long

end of the duration curve for the

:

01:19:10,313 --> 01:19:12,413

insurance sector and for the, for the,

:

01:19:12,983 --> 01:19:13,343

yeah.

:

01:19:13,553 --> 01:19:16,553

Chris Schindler: so, you know,

credit like, my God, like, like if

:

01:19:16,553 --> 01:19:19,043

you just wanted to have a form of

credit, all you would do is just

:

01:19:19,103 --> 01:19:22,463

buy from five or six years and hold

it right through to maturity, like

:

01:19:22,673 --> 01:19:23,963

significantly higher sharp rates you go.

:

01:19:24,293 --> 01:19:24,983

Is that a risk premium?

:

01:19:24,983 --> 01:19:25,282

Yes.

:

01:19:25,282 --> 01:19:26,223

Is it an active strategy?

:

01:19:26,273 --> 01:19:29,452

Eh, it's just different than, than what

the vast majority of people are doing.

:

01:19:29,618 --> 01:19:33,128

Adam Butler: all the, all the ETFs,

like all the index ETFs exposure to

:

01:19:33,128 --> 01:19:35,228

credit are all constant maturity.

:

01:19:35,228 --> 01:19:36,907

So they're all, that's

exactly what they're doing.

:

01:19:36,907 --> 01:19:42,068

They're constantly rolling into new bonds

of TAR that, around that target maturity.

:

01:19:42,098 --> 01:19:42,338

Right.

:

01:19:42,343 --> 01:19:43,598

So they're just not collecting that

:

01:19:43,823 --> 01:19:44,183

Chris Schindler: Yeah.

:

01:19:44,273 --> 01:19:48,439

So, anyway, that, that, I assume this

is obsolete information 15 years after

:

01:19:48,439 --> 01:19:50,689

we discovered it, but, but it's still,

it's, it is quite surprising where

:

01:19:50,689 --> 01:19:53,696

it's, it is, I remember working with

the, the head of credit at the time and

:

01:19:53,696 --> 01:19:56,216

because, it was just one of those, like,

we don't understand, like, like why,

:

01:19:56,216 --> 01:20:00,266

why would you just buy a bold process

of credit, a constant maturity role?

:

01:20:00,266 --> 01:20:03,356

Like why is, why is the sharp ratio so

low when, when it looks like they haven't

:

01:20:03,356 --> 01:20:05,486

made a lot of defaults and we know that

they're paying a lot and the answer is.

:

01:20:05,951 --> 01:20:09,198

Well, because it's, it's literally the

curve has a pretty significant kink

:

01:20:09,198 --> 01:20:11,388

because this is where the buyers are

and this is where the sellers are.

:

01:20:11,443 --> 01:20:13,516

And, and it's huge pressure points.

:

01:20:13,516 --> 01:20:16,006

And if you just hold past that, there's,

there's something quite interesting there.

:

01:20:16,011 --> 01:20:17,026

You know, it's the same thing.

:

01:20:17,386 --> 01:20:18,556

We talked about this a lot.

:

01:20:18,556 --> 01:20:21,496

you know, if, if all you're allowed

to invest in is investment grade,

:

01:20:21,556 --> 01:20:24,466

well then every time something gets

downgraded, you're forced to sell it.

:

01:20:24,471 --> 01:20:27,196

And, and that's, you know, that

it's you, you wouldn't sell it if

:

01:20:27,196 --> 01:20:28,246

you didn't, if you didn't have to.

:

01:20:28,246 --> 01:20:30,286

And you know, it's a bad trade, you

know, it's a money losing trade.

:

01:20:30,496 --> 01:20:33,646

But across that, you know, constraint of,

if I, if I own this name, once they're

:

01:20:33,646 --> 01:20:34,816

being downgraded, I'm gonna get fired.

:

01:20:34,821 --> 01:20:37,336

I'm, I'm happily gonna sell

it and I'm gonna give that

:

01:20:37,336 --> 01:20:38,506

money to someone else happily.

:

01:20:38,506 --> 01:20:41,056

And that, transfer of utilities

is, is a classic risk premium.

:

01:20:41,416 --> 01:20:43,606

So if you're an unconstrained

investor buying the fallen Angels,

:

01:20:43,611 --> 01:20:46,126

like this is like, this is like

20-year-old unknown strategies.

:

01:20:46,131 --> 01:20:49,151

But buying the Fallen Angels is

a, is a very winning strategy and

:

01:20:49,196 --> 01:20:51,656

Adam Butler: continues to be, you

know, it's amazing and like a, a

:

01:20:51,656 --> 01:20:55,550

number of managers come out and tried

to launch these Fallen Angel ETFs and

:

01:20:55,556 --> 01:20:58,699

I always look at 'em and go, this is

such a great, risk premium to own.

:

01:20:58,699 --> 01:21:01,579

And then they, you know, a year later they

delist them 'cause nobody's interested.

:

01:21:02,629 --> 01:21:04,846

Chris Schindler: Well, and I

guess the reason it exists is

:

01:21:04,846 --> 01:21:06,286

because people can't do it.

:

01:21:06,406 --> 01:21:09,586

I mean, it's like, as, as long as

you're, if you're an unconstrained

:

01:21:09,586 --> 01:21:12,106

investor, you absolutely should,

you know, once again, these aren't

:

01:21:12,106 --> 01:21:13,456

really, maybe they're strategies.

:

01:21:13,461 --> 01:21:16,906

I, I, if you think about it that way,

I mean, I mean, you're seeing just an

:

01:21:16,966 --> 01:21:20,896

absolute ton of overriding strategies

that are coming into the market nowadays.

:

01:21:21,286 --> 01:21:23,909

Uh, you know, 'cause, 'cause

they're index enhanced and, like

:

01:21:23,909 --> 01:21:25,318

it, to me it's quite incredible.

:

01:21:25,349 --> 01:21:28,079

You know, how much of these you're seeing

and, and once again, these are stuffing

:

01:21:28,079 --> 01:21:31,606

the dealers full of haha just, crazy

amounts of gamma I thought they're trying

:

01:21:31,606 --> 01:21:32,836

to handle, like, on the sharp downside.

:

01:21:32,836 --> 01:21:33,916

So, so, you know, it's just like.

:

01:21:34,411 --> 01:21:36,674

But, um, you know, those

are very simple strategies.

:

01:21:36,674 --> 01:21:40,108

I, I'm not a big fan personally of

every aspect of that, but like, you

:

01:21:40,108 --> 01:21:43,468

know, if you build a proper, vol

selling process and size it, right?

:

01:21:43,468 --> 01:21:46,498

Like, like, like vol selling

within FX within actually,

:

01:21:46,618 --> 01:21:47,698

of course is the main one.

:

01:21:47,898 --> 01:21:49,428

and to a certain extent

in some, in commodities.

:

01:21:49,428 --> 01:21:51,438

Like, there's, there's

interesting opportunities there.

:

01:21:51,714 --> 01:21:55,004

so if you think about like, like what

are the major strategies the very,

:

01:21:55,004 --> 01:21:59,414

like, as I would've defined them

back in:

:

01:21:59,414 --> 01:22:02,384

You've got a,, well, you've actually got

a, let's call it a low vol if you want.

:

01:22:02,384 --> 01:22:02,984

Define it that way.

:

01:22:03,044 --> 01:22:05,174

Where's the least leverage

point within assets?

:

01:22:05,174 --> 01:22:07,124

You've got a low vol piece, you've

got an inventive piece, you've got

:

01:22:07,124 --> 01:22:09,104

a vol piece, you've gotta carry it.

:

01:22:09,104 --> 01:22:12,824

And you've got like some vol, some

value versus quality definition.

:

01:22:13,050 --> 01:22:16,141

and then every major asset probably

has some sort of seasonality

:

01:22:16,146 --> 01:22:17,491

or cyclicities in it as well.

:

01:22:17,911 --> 01:22:22,282

And so, That basket is probably like the

modern alternative risk premium basket.

:

01:22:22,282 --> 01:22:24,989

And then I would say like, you know,

next generation that we sort of focused

:

01:22:24,994 --> 01:22:27,419

on a little bit is like, well, what

about the players playing those baskets?

:

01:22:27,989 --> 01:22:30,089

Because if there's all those baskets

and all those players, and, and in

:

01:22:30,089 --> 01:22:32,999

many cases now the risk premium of

the player playing the basket is

:

01:22:33,004 --> 01:22:34,259

stronger than the basket itself.

:

01:22:34,549 --> 01:22:38,539

and you'll see this all, and like

that's by the way, longer term macro,

:

01:22:38,709 --> 01:22:41,573

you know, ETF index anticipation.

:

01:22:41,573 --> 01:22:43,709

You know, like, like I, I'm trying

to, trying to anticipate names

:

01:22:43,714 --> 01:22:44,729

coming in outta the indices.

:

01:22:44,729 --> 01:22:47,699

Like you've got so many players

who are so big and, and doing that,

:

01:22:47,759 --> 01:22:48,779

it's such aggressive size now.

:

01:22:48,779 --> 01:22:52,739

Like, like in anything, you can easily

get more people offering the insurance

:

01:22:52,739 --> 01:22:53,969

than, than you have people buying it.

:

01:22:53,969 --> 01:22:55,529

And you can get caught on

the other side of that trade.

:

01:22:55,529 --> 01:22:58,148

I mean, it's almost like, I think a lot

of those strategies, which has sharks

:

01:22:58,148 --> 01:23:00,914

of two have just gone like minus two

because very, very quickly it's like, Too

:

01:23:00,914 --> 01:23:04,881

many people tried to hoard toilet paper

during, covid and then, and they all

:

01:23:04,881 --> 01:23:06,321

tried to give it back at the same time.

:

01:23:06,321 --> 01:23:08,871

It's like you're, you're literally

trying to buy the toilet paper before

:

01:23:08,871 --> 01:23:11,511

someone else buys it, and hopefully

there's enough buyers to buy it from you.

:

01:23:11,838 --> 01:23:14,398

but if too many people do that,

you can get, you can get caught

:

01:23:14,403 --> 01:23:16,288

holding your toilet paper, if

you don't mind the analogy.

:

01:23:16,733 --> 01:23:19,088

Adam Butler: So I wanna, I wanna

highlight something that you, that

:

01:23:19,088 --> 01:23:22,028

you sort of, you said, and, but you,

you kind of glossed over as though,

:

01:23:22,238 --> 01:23:23,198

as though it's sort of a given.

:

01:23:23,198 --> 01:23:25,448

But you know, you've got all

these different premia, you

:

01:23:25,538 --> 01:23:27,558

know, you talked about carry and

then you talked about FX carry.

:

01:23:27,577 --> 01:23:29,318

You talked about vol

selling and inequities.

:

01:23:29,378 --> 01:23:30,128

You talked about value.

:

01:23:30,128 --> 01:23:33,038

And most people think about value equities

but you've got all these different.

:

01:23:33,504 --> 01:23:35,531

Typically, but all these

specialists, right?

:

01:23:35,531 --> 01:23:37,661

And you've got, you know, people

who are familiar with value.

:

01:23:37,661 --> 01:23:41,561

They like buying, you know,

cheap companies or cheap credits

:

01:23:41,561 --> 01:23:42,821

or, or what have you, right?

:

01:23:43,121 --> 01:23:46,361

But the real magic for, vol

selling carry, it doesn't matter.

:

01:23:46,541 --> 01:23:52,641

The real magic is in selling all the

vol isn't getting, all the carry is

:

01:23:52,641 --> 01:23:56,871

in, arming all the value across all

the asset classes, all the different

:

01:23:56,871 --> 01:24:02,348

securities, to the extent that you can

then, you know, trade against the baskets.

:

01:24:02,373 --> 01:24:03,327

there's a whole other level there.

:

01:24:03,327 --> 01:24:08,098

But just to kind of diversify global

premium strategy, it's available, well,

:

01:24:08,098 --> 01:24:12,238

it may not be available to everybody, but

it's becoming more available every year.

:

01:24:12,598 --> 01:24:15,838

And most people just take

little pieces of it, right?

:

01:24:15,838 --> 01:24:18,083

Like, I've got a, a value

tilt in my portfolio or a

:

01:24:18,088 --> 01:24:19,373

quality tilt in my portfolio.

:

01:24:19,378 --> 01:24:22,529

But it's purely on the equity

side when, if you're just in into

:

01:24:22,529 --> 01:24:25,766

FX carry, that actually doesn't

have a very attractive profile.

:

01:24:25,766 --> 01:24:27,776

It used to have a more attractive profile.

:

01:24:28,076 --> 01:24:30,206

Now the profile isn't attractive at all,

:

01:24:30,446 --> 01:24:32,096

but global Carry is

:

01:24:32,146 --> 01:24:34,031

Chris Schindler: or five years

there where like there was no carry

:

01:24:34,031 --> 01:24:36,581

signal because the central banks

drove all the interest rates down to

:

01:24:36,861 --> 01:24:37,441

Adam Butler: That's right.

:

01:24:37,541 --> 01:24:39,731

Chris Schindler: you know, it's,

I bet you there's fat carry right

:

01:24:39,731 --> 01:24:42,550

now in a lot of places, you know,

especially em versus developed like,

:

01:24:42,550 --> 01:24:43,871

I mean, it's, it's suddenly back.

:

01:24:44,351 --> 01:24:49,311

But, but yeah, that, pillar of

value and carry and momentum is, is

:

01:24:49,316 --> 01:24:50,751

pretty powerful almost everywhere.

:

01:24:51,291 --> 01:24:52,041

Um, you know, AQR

:

01:24:52,101 --> 01:24:54,096

Adam Butler: the magic is

getting it from everywhere.

:

01:24:54,216 --> 01:24:54,576

Right.

:

01:24:54,591 --> 01:24:54,651

Chris Schindler: Yeah.

:

01:24:54,651 --> 01:24:58,278

And, and this is where I think systematic

investing is interesting because like not

:

01:24:58,282 --> 01:24:59,478

to take away from discretionary players.

:

01:24:59,483 --> 01:25:01,941

Like they, they have, like, they,

you know, I think there's a really

:

01:25:01,946 --> 01:25:04,101

interesting marriage between

discretionary and systematic.

:

01:25:04,101 --> 01:25:06,321

And because, you know, at difficult

turning points are when the

:

01:25:06,326 --> 01:25:07,491

world hasn't looked the same.

:

01:25:07,731 --> 01:25:10,101

Discretionary people have a

chance to, to see into the future.

:

01:25:10,101 --> 01:25:12,368

And, if they're good at that, they

can add a ton of value where, where

:

01:25:12,368 --> 01:25:14,618

the systematic players may get

caught in those structural shifts.

:

01:25:15,128 --> 01:25:17,827

But in a world of more stability,

the systematic player and the breadth

:

01:25:17,827 --> 01:25:20,063

that just can't be beaten and,

and, and can really do quite well.

:

01:25:20,063 --> 01:25:23,613

And so those two, like, they, they really

do diversify at, at, at difficult times.

:

01:25:23,856 --> 01:25:28,716

but the expertise in systematic

investing is in the systematic investing.

:

01:25:28,716 --> 01:25:33,186

And so you'll see that like, if you do

carry an FX or fixed income or equities

:

01:25:33,186 --> 01:25:38,823

or vol or credit, it rhymes so much across

those that the expertise is in building

:

01:25:38,823 --> 01:25:42,333

the models as opposed to the asset class

expertise required to go capture it.

:

01:25:42,333 --> 01:25:43,743

And it's the same for almost everything.

:

01:25:43,743 --> 01:25:46,803

I mean, I say if you're building

a systematic model or, or, or

:

01:25:46,803 --> 01:25:50,523

management, you would never

have a commodity carry expert.

:

01:25:50,523 --> 01:25:51,513

It makes no sense.

:

01:25:51,518 --> 01:25:53,763

And, and, and you might, you might

wanna talk to a discussion I call

:

01:25:53,763 --> 01:25:56,223

my commodity trader to make sure

that you got all the pieces right.

:

01:25:56,243 --> 01:25:58,966

but at the end of the day, the,

the, the, the commodity carry model

:

01:25:58,971 --> 01:26:03,136

is going be 99% resonant to the FX

carry and to the fixed income carry.

:

01:26:03,136 --> 01:26:05,566

And, and there's obviously gonna be a

little bit of like asset class specifics

:

01:26:05,566 --> 01:26:06,675

that you have to understand and know.

:

01:26:07,321 --> 01:26:10,768

But the, but once you're past that,

the, the model building piece of

:

01:26:10,768 --> 01:26:14,368

it, and like the signal generation,

the risk calculation, the portfolio

:

01:26:14,368 --> 01:26:18,281

construction, the putting all the

pieces together and like, it should

:

01:26:18,281 --> 01:26:21,971

be, the expertise is in the model

building as opposed to in the asset

:

01:26:21,976 --> 01:26:23,981

classes is, is needed to capture that.

:

01:26:23,981 --> 01:26:26,381

And, and, and there's a little bit of

expertise that the asset class required,

:

01:26:26,381 --> 01:26:28,931

but they, I think, quite a bit less.

:

01:26:28,946 --> 01:26:32,261

And, and so, the systematic

trader can capture all of those.

:

01:26:32,261 --> 01:26:34,601

In fact, I would say a small number of

traders could probably capture all of

:

01:26:34,601 --> 01:26:36,581

those strategies all at once, pretty well.

:

01:26:37,001 --> 01:26:39,492

And, and then you say like a discretionary

investor could probably go in and,

:

01:26:39,497 --> 01:26:42,911

and really clean up on the, around the

edges and, and, and those two could

:

01:26:42,911 --> 01:26:44,231

be, could be quite helpful together.

:

01:26:44,504 --> 01:26:47,894

but the, like, say like how do

you collect all those things?

:

01:26:48,401 --> 01:26:51,001

You know, it's, it's actually

not as difficult as it sounds.

:

01:26:51,001 --> 01:26:53,221

I mean, I think if you started to

build these processes and models

:

01:26:53,221 --> 01:26:56,221

like bit by bit then like the, the

advantage of systematic investing is.

:

01:26:56,488 --> 01:26:59,548

Once you've built a model and built

it well, it just goes off and runs.

:

01:26:59,548 --> 01:27:02,098

It's like an annuity, and you can start to

build the next one and build the next one.

:

01:27:02,098 --> 01:27:04,438

And, you know, you build

five, 10 models a year.

:

01:27:04,438 --> 01:27:06,418

After two or three years,

you've got a really interesting

:

01:27:06,423 --> 01:27:08,038

diversified suite of processes.

:

01:27:08,308 --> 01:27:10,258

And some of these can be built

much quicker because, because

:

01:27:10,258 --> 01:27:13,484

like I said, they rhyme in such

significant and obvious ways.

:

01:27:13,664 --> 01:27:16,334

And, and so, you know, and, and,

and this is not a news story.

:

01:27:16,334 --> 01:27:20,858

I mean, there's, there's been a, you know,

a number of very successful multi-Strat

:

01:27:20,858 --> 01:27:22,748

risk premium collectors over the years.

:

01:27:22,803 --> 01:27:25,478

And, and, like anything, they're

gonna have good years and bad years.

:

01:27:25,523 --> 01:27:27,924

and, and the space gets more or

less crowded as the space gets

:

01:27:27,924 --> 01:27:29,154

crowded, returns get driven down.

:

01:27:29,154 --> 01:27:33,564

But, but I'm a solid believer that

the space will never get so crowded

:

01:27:33,564 --> 01:27:34,644

that it will never make any money.

:

01:27:34,644 --> 01:27:39,441

Because like on one side you've got people

with actual demands who are like always

:

01:27:39,441 --> 01:27:40,671

gonna have the constrained investors.

:

01:27:40,675 --> 01:27:42,321

You're always gonna be

investors who are in the spot.

:

01:27:42,321 --> 01:27:43,791

There's always gonna be a flow of wealth.

:

01:27:44,391 --> 01:27:45,621

They're there and they're naturally there.

:

01:27:45,621 --> 01:27:46,971

You're gonna have the

demands for insurance.

:

01:27:46,971 --> 01:27:50,004

Like, like, you're gonna have the players

creating the risk premiums and if you've

:

01:27:50,004 --> 01:27:52,523

got other players collecting it, when

too many people come in and collect Yeah.

:

01:27:52,738 --> 01:27:54,928

for a while it can get driven

very low or even negative.

:

01:27:55,198 --> 01:27:58,048

And then most players will leave,

or the size will fix or you know,

:

01:27:58,048 --> 01:27:59,788

like, like all that're normalized.

:

01:28:00,061 --> 01:28:03,541

And at the end of the day, because its

natural demand is there, these players

:

01:28:03,541 --> 01:28:08,101

will, there will be an equilibrium

where a correct equilibrium risk

:

01:28:08,101 --> 01:28:12,091

premium collection process will and

can exist on, on average over time.

:

01:28:12,421 --> 01:28:14,958

And the only question is you know,

what is, what is the expected sharp

:

01:28:14,958 --> 01:28:16,218

ratio of that process long term?

:

01:28:16,278 --> 01:28:18,768

You know, it's never gonna, uh, we talked

about this four or five years ago, it's

:

01:28:18,768 --> 01:28:21,738

never gonna be as good as it was in the

early two thousands because it was just

:

01:28:21,738 --> 01:28:24,198

too unknown at that point and there

just weren't enough people doing it.

:

01:28:24,438 --> 01:28:27,048

It's never gonna go to zero

because, because naturally these

:

01:28:27,048 --> 01:28:28,398

players will leave if it does.

:

01:28:28,698 --> 01:28:32,534

And so there's the, what is the sharp

ratio that will keep players interested?

:

01:28:32,729 --> 01:28:33,874

And where does that balance to?

:

01:28:33,874 --> 01:28:36,588

And I, you know, and, and, like

it comes down to the, everyone,

:

01:28:36,618 --> 01:28:37,698

everyone always throws out a numbers.

:

01:28:37,698 --> 01:28:39,521

Like what's, what's the

Sharpe ratio per strategy?

:

01:28:39,521 --> 01:28:42,851

Is it, is it gonna be 0.25

or 0.35, or 0.4 or 0.5?

:

01:28:43,331 --> 01:28:45,234

And what is the Sharpe ratio at

the, at the aggregate process?

:

01:28:45,234 --> 01:28:47,604

Is it gonna be 0.5 or

one or one and a half?

:

01:28:47,604 --> 01:28:48,954

And, and I don't know where that settles.

:

01:28:48,954 --> 01:28:51,864

Like I would probably guess these

things each come in at like a 0.25

:

01:28:51,864 --> 01:28:55,841

and this thing comes in at a one, but

that's a extraordinarily helpful, you

:

01:28:55,841 --> 01:28:58,901

know, and I think people have been so

spoiled by the equities over the last,

:

01:28:58,901 --> 01:29:01,721

you know, 10 or 15 years and go one

Like, I can get that from equities.

:

01:29:01,721 --> 01:29:04,331

And it's like, yeah, the

equities are a 0.5 long term.

:

01:29:04,331 --> 01:29:06,491

and you just have to be careful

with equities because like, they

:

01:29:06,491 --> 01:29:09,041

make, very, very high Sharpe ratios

for a while and they make very

:

01:29:09,041 --> 01:29:10,451

low Sharpe ratios for a while.

:

01:29:10,751 --> 01:29:14,081

if you could find a, like a proper

one that you could put next to the

:

01:29:14,081 --> 01:29:18,321

0.5 of equities in the 0.4 or whatever

of bonds you'd be so happy long term.

:

01:29:18,821 --> 01:29:19,061

Adam Butler: Yeah.

:

01:29:19,351 --> 01:29:21,151

Chris Schindler: but, but it's just

a, it is just one of those things

:

01:29:21,151 --> 01:29:22,981

where, and you have to buy into it.

:

01:29:22,981 --> 01:29:25,651

You have to understand it, and you

have to trust over, over long term

:

01:29:25,651 --> 01:29:28,731

that it will be there, And, and I

find that that's probably the biggest

:

01:29:28,736 --> 01:29:32,991

challenge with systematic investing

is because people don't, intuitively

:

01:29:33,356 --> 01:29:36,556

it doesn't resonate with many people

is intuitively, let's say, like, I buy

:

01:29:36,556 --> 01:29:40,316

cheap companies, I I, something really,

really obvious and simple sounding.

:

01:29:40,316 --> 01:29:42,626

It's like I, I buy things when

they're cheap and, and they're on

:

01:29:42,626 --> 01:29:45,716

their way up, or I buy Exactly.

:

01:29:45,716 --> 01:29:48,026

you know, and you have to, you're

trying to explain a little bit more,

:

01:29:48,026 --> 01:29:51,416

something a little bit more complicated

that when it doesn't go well, people

:

01:29:51,421 --> 01:29:52,796

lose faith in it much quicker.

:

01:29:52,886 --> 01:29:55,496

And, and you can have a value

investor who's just being crushed

:

01:29:55,496 --> 01:29:57,956

for a year, and they'll come back

and say, it's worth even more.

:

01:29:58,016 --> 01:29:58,616

Just trust me.

:

01:29:58,616 --> 01:29:58,856

You know?

:

01:29:58,961 --> 01:29:59,616

Mike Philbrick: It's even better.

:

01:29:59,881 --> 01:30:02,306

Chris Schindler: It's,

it's even better now.

:

01:30:02,311 --> 01:30:02,425

And.

:

01:30:02,716 --> 01:30:06,766

if the S&P falls 20, 30%, people don't

go, it's never gonna make money again.

:

01:30:07,246 --> 01:30:09,256

They say, we should

pile in and buy it here.

:

01:30:09,436 --> 01:30:13,096

but there's a whole bunch of people who,

you know, if this strategy has a bad

:

01:30:13,101 --> 01:30:16,266

run, think, ah, maybe it was never a

thing, or maybe it never will be a thing.

:

01:30:16,266 --> 01:30:17,106

Or maybe it's,

:

01:30:17,766 --> 01:30:17,887

you know,

:

01:30:19,071 --> 01:30:21,591

Mike Philbrick: Well, it, it

comes down to that, that decision.

:

01:30:21,726 --> 01:30:23,946

Chris Schindler: like, like you can

argue that like, like, yeah, the expected

:

01:30:23,946 --> 01:30:28,743

return of the S&P has been driven down

by, until it finds the level at which

:

01:30:28,743 --> 01:30:30,273

it's expected return is positive.

:

01:30:30,359 --> 01:30:33,479

that's what any risk premium is doing

on any given day is like the person

:

01:30:33,479 --> 01:30:37,469

lending to it is trying to, is trying

to find the marginal price where the on

:

01:30:37,469 --> 01:30:41,039

expectation, their, their expected return

is, is proper for the risk they're taking.

:

01:30:41,398 --> 01:30:43,318

Like they, you know, the marginal

price center is trying to determine the

:

01:30:43,318 --> 01:30:47,219

price at which their expected return

meets some required return on risk.

:

01:30:47,519 --> 01:30:49,039

It should be the same for everything.

:

01:30:49,429 --> 01:30:53,364

and so there's no reason, except if

you have too many people trying to

:

01:30:53,364 --> 01:30:55,314

sell at the same time or two people

trying to buy at the same time,

:

01:30:55,314 --> 01:30:58,074

the price will adjust and move and

those players will come in and out.

:

01:30:58,434 --> 01:31:02,184

That should be a natural expectation

of what this process is gonna be and,

:

01:31:02,184 --> 01:31:03,654

and it has a fairly long life to it.

:

01:31:04,114 --> 01:31:04,744

But that's fine.

:

01:31:04,744 --> 01:31:07,174

If your portfolio construction in the long

term, you should be totally fine with it.

:

01:31:07,999 --> 01:31:08,289

Mike Philbrick: yeah.

:

01:31:08,404 --> 01:31:11,494

You, you hit on something that

we, struggle with, or like the

:

01:31:11,494 --> 01:31:16,144

intuition of the strategy and the

ability to stick to the intuition.

:

01:31:16,148 --> 01:31:20,164

So providing the extra underlying

insights is incredibly.

:

01:31:20,548 --> 01:31:23,608

Useful, but sometimes

still falls short when

:

01:31:23,758 --> 01:31:25,558

you know, and, and their

friends aren't doing it right.

:

01:31:25,558 --> 01:31:28,228

So you've got a little bit less

intuition than you'd expect.

:

01:31:28,228 --> 01:31:31,874

You have a little less crowding

from a cohort of, of those who, uh,

:

01:31:31,874 --> 01:31:33,434

you're, maybe benchmarked against.

:

01:31:33,434 --> 01:31:34,693

It leads to some pretty,

:

01:31:35,264 --> 01:31:36,284

pretty significant

:

01:31:36,404 --> 01:31:39,044

Chris Schindler: Well, why aren't

you just buying Nvidia, I think is

:

01:31:39,044 --> 01:31:40,784

the, uh, is to come full circle.

:

01:31:41,729 --> 01:31:47,869

Uh, so, and, and look I think what you

guys have done, with your, what do you

:

01:31:47,869 --> 01:31:51,139

call it, your, like when you're laying in

your alpha and your beta together, your

:

01:31:51,364 --> 01:31:52,744

Mike Philbrick: Oh, return stacking their

:

01:31:52,849 --> 01:31:53,089

Chris Schindler: yeah.

:

01:31:53,089 --> 01:31:57,353

I think like, like everything old is new

again, but like, like a portable alpha.

:

01:31:57,353 --> 01:32:00,483

it makes a ton of sense because

there's an investor out there who goes

:

01:32:00,656 --> 01:32:03,866

I can't face the benchmark loss of

this underperforming the benchmark.

:

01:32:03,866 --> 01:32:05,036

And it's like, that's great.

:

01:32:05,066 --> 01:32:08,066

Here's a process that that gives you

the benchmark return plus this alpha,

:

01:32:08,173 --> 01:32:09,403

it just seems really smart to me.

:

01:32:09,403 --> 01:32:13,063

So I, I, I, think that's a great product

and I, and I hope that it has some uptake.

:

01:32:13,288 --> 01:32:14,068

Mike Philbrick: Nice plug.

:

01:32:14,458 --> 01:32:14,748

Adam Butler: Yeah.

:

01:32:15,327 --> 01:32:15,988

Mike Philbrick: We'll take it.

:

01:32:16,318 --> 01:32:18,508

We'll take now we are, we

are coming up on the end.

:

01:32:18,508 --> 01:32:21,898

And so are there any thoughts that you had

that we haven't covered that you wanted

:

01:32:21,898 --> 01:32:25,907

to put out there for investors to think

about, things that you're contemplating

:

01:32:25,907 --> 01:32:28,577

that are hot on your plate right now

that, uh, that we haven't talked about?

:

01:32:29,278 --> 01:32:31,233

Chris Schindler: I mean I I

think we've covered a lot.

:

01:32:31,238 --> 01:32:33,933

I mean like, obviously I always

have lots of to, to talk about.

:

01:32:33,938 --> 01:32:37,053

But, but, from the topics we've covered,

I think we've covered them pretty well.

:

01:32:37,058 --> 01:32:39,993

And, and I feel like I apologize to people

'cause I know I say the same things that

:

01:32:39,993 --> 01:32:43,053

we've, we've two or three times in, I'm

probably repeating myself quite a lot

:

01:32:43,053 --> 01:32:45,659

now, but yeah, look, I'm happy to do this.

:

01:32:45,659 --> 01:32:46,289

I love doing this.

:

01:32:46,289 --> 01:32:47,099

I love the conversation.

:

01:32:47,099 --> 01:32:48,449

I think you guys ask great questions.

:

01:32:48,449 --> 01:32:49,949

and I'd love to come back and

do it again at some point.

:

01:32:50,489 --> 01:32:50,834

Mike Philbrick: Love it.

:

01:32:51,974 --> 01:32:54,044

Adam Butler: you're, you're a

great guy to bookend the, the

:

01:32:54,049 --> 01:32:55,214

beginning or the end of a season.

:

01:32:55,214 --> 01:32:57,943

I can tell you that there's, whatever

we have you on, they're clamoring

:

01:32:57,943 --> 01:33:01,544

for more, man, so we gotta keep 'em

starved for, for more Schindler.

:

01:33:01,544 --> 01:33:01,844

But,

:

01:33:01,859 --> 01:33:03,389

Chris Schindler: Exactly, exactly.

:

01:33:03,389 --> 01:33:04,409

Save some for the next time.

:

01:33:04,979 --> 01:33:06,419

Okay, listen, thanks a lot guys.

Next Episode All Episodes Previous Episode

Listen for free

Show artwork for Resolve Riffs Investment Podcast

About the Podcast

Resolve Riffs Investment Podcast
Welcome to ReSolve Riffs Investment Podcast, hosted by the team at ReSolve Global*, where evidence inspires confidence.
These podcasts will dig deep to uncover investment truths and life hacks you won’t find in the mainstream media, covering topics that appeal to left-brained robots, right-brained poets and everyone in between. In this show we interview deep thinkers in the world of quantitative finance such as Larry Swedroe, Meb Faber and many more, all with the goal of helping you reach excellence. Welcome to the journey.


*ReSolve Global refers to ReSolve Asset Management SEZC (Cayman) which is registered with the Commodity Futures Trading Commission as a commodity trading advisor and commodity pool operator. This registration is administered through the National Futures Association (“NFA”). Further, ReSolve Global is a registered person with the Cayman Islands Monetary Authority.