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Speaker 1: Hello, and welcome to another episode of the All Thoughts podcast.

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Speaker 1: I'm Tracy Alloway. My co host Joe Wisenthal couldn't make

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Speaker 1: it today, So I'm looking at a chart of the

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Speaker 1: SMP five hundred, and let's see, it's almost exactly one

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Speaker 1: year post the big dip in the SMP five hundred,

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Speaker 1: the massive crash that we saw back in March, and

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Speaker 1: of course we've seen risk assets come roaring back. But

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Speaker 1: with the recovery in financial assets, we have a lot

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Speaker 1: of questions over how long can this continue? Are we

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Speaker 1: on the verge of some sort of big change in

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Speaker 1: the market as central banks unleash fiscal stimulus and interest

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Speaker 1: rates remain at or close to the zero bound. Are

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Speaker 1: we going to get inflation? Are we going to get stagflation?

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Speaker 1: Are we going to see perhaps even deflation? Is there

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Speaker 1: any way we're ever going to get out of this

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Speaker 1: regime of low inflation? And I think whenever we have

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Speaker 1: these big turning points in markets, or when we have

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Speaker 1: lots of people talking about the potential for big turning

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Speaker 1: points and markets, we also have a lot of opinions

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Speaker 1: on how those are going to go and what type

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Speaker 1: of portfolio would perform best, And of course we've seen

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Speaker 1: a lot of handwringing recently around growth versus value sixty

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Speaker 1: forty what happens when both bonds and stocks fall at

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Speaker 1: the same time. It's on today's show we're going to

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Speaker 1: be discussing exactly this idea. How do you build a

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Speaker 1: portfolio that can withstand these regime changes and basically outperform

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Speaker 1: over a really long time horizon. And I'm excited to

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Speaker 1: say our guest for this episode is Chris Cole, the

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Speaker 1: founder of Artemis Capital. He's appeared on all lots previously,

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Speaker 1: digging deep into the low volatility regime of the past years.

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Speaker 1: It's great to have him back. He publishes some excellent research. Chris,

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Speaker 1: thanks for coming on the show again. Thanks Tracy, it's

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Speaker 1: great to be back on the show. So, uh, I

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Speaker 1: guess my first question is you know the reason we're

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Speaker 1: having this discussion is you published a paper called the

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Speaker 1: Allegory of the Hawk and Serpent, How to grow and

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Speaker 1: protect wealth for a hundred years now. Most investors aren't

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Speaker 1: really looking at their portfolios on a hundred year basis.

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Speaker 1: What sparked your interest in that kind of time frame?

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Speaker 1: What's really interesting about in particular the last forty years,

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Speaker 1: is that there's a tremendous recency bias that market participants have.

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Speaker 1: The last forty years are incredibly unusual comparative to overall history,

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Speaker 1: and I believe, as I make the case in the paper,

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Speaker 1: that recency biases is now a systemic risk. The price

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Speaker 1: appreciation for a classic sixty forty portfolio over the last

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Speaker 1: ninety three years has come from just the twenty two

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Speaker 1: years between night four to two thousand seven. So what

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Speaker 1: we've had is this incredible out performance of both stocks

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Speaker 1: and bonds that has been from a reinforcing cycle, and

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Speaker 1: we use the allegory of the serpent for that, and

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Speaker 1: that's been led by falling interest rates. Rates fell from

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Speaker 1: seventeen percent to zero percent. There's been incredible favorable demographics

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Speaker 1: as baby boomers to come into the workforce, falling taxes.

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Speaker 1: Taxes have fallen to near a hundred year lows, globalization

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Speaker 1: on precedent of monetary policy, and we now have some

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Speaker 1: of the highest levels of both governments and corporate debt

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Speaker 1: in American history. So as a result of this, there's

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Speaker 1: been this incredible out performance of stocks and bonds over

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Speaker 1: the last forty years. But the trillion dollar question that

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Speaker 1: I think is important for any allocator is is this repeatable?

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Speaker 1: And I actually believe that the factors that drove this

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Speaker 1: generational boom in the stocks and bonds are are now reversing.

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Speaker 1: We're now on a framework where debts at all time highs,

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Speaker 1: the middle class hasn't seen real wage growth since the

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Speaker 1: nineteen seventies, and demographics are really poor, and interest rates

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Speaker 1: can't go any lower. So investors expecting the games in

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Speaker 1: the last four years are likely to be extremely disappointed.

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Speaker 1: And so to kind of understand what the next twenty

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Speaker 1: years are going to look like and how to build

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Speaker 1: a portfolio that will last um and can manage through

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Speaker 1: this period of secular change, what I did is I

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Speaker 1: went back through history and I recreated all of these

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Speaker 1: financial engineering strategies, UH using I think defensible assumptions over

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Speaker 1: the last years. And we know that you know, history

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Speaker 1: doesn't repeat, but it rhymes. And my my goal was

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Speaker 1: to figure out what portfolio can consistently perform to every

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Speaker 1: market cycle, whether it's secular growth, whether it's inflation, whether

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Speaker 1: it's deflation. And I think I came up with some

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Speaker 1: really interesting answers in my paper last year in the

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Speaker 1: follow up paper that I just released that really answers

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Speaker 1: the questions as to what type of portfolio really sustains

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Speaker 1: wealth and capital appreciation and limits draw downs. And the

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Speaker 1: answer that I got is radically different from the type

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Speaker 1: of portfolio that many institutions and retail investors are currently

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Speaker 1: are currently allocating too. I have so many questions already,

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Speaker 1: but one that jumps out at me is going back

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Speaker 1: a hundred years and trying to reconstruct modern portfolios against

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Speaker 1: financial assets in the nine twenties and nineteen thirties. How

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Speaker 1: exactly did you do that? Because I'm looking at the paper,

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Speaker 1: and you know, you look at things like naked call selling,

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Speaker 1: how that perform during the Great Depression? I'm just curious

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Speaker 1: how you recreated, uh, those portfolios. Absolutely, it's a It's

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Speaker 1: an incredible question. And I think one of the one

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Speaker 1: of the things that I think is very important to

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Speaker 1: understand about about this exercise is that we don't necessarily

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Speaker 1: say that these portfolios are realized performance, but they are

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Speaker 1: best effort at understanding how a given financial engineering strategy

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Speaker 1: might have performed in the past. And I think there's

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Speaker 1: a lot of defensible assumptions you know, first of all,

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Speaker 1: we start with a wealth of observable data. There is

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Speaker 1: data that we can gather off from history, namely the

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Speaker 1: composite SMP five hundred prices, from stock data the top

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Speaker 1: companies at a given point in time. There's obviously gold data,

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Speaker 1: interest rate data, there's data on commodities and that that's

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Speaker 1: a starting point um and we use that data from

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Speaker 1: the global financial database. From there, what we can do

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Speaker 1: is we can construct some UH and replicate some basic

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Speaker 1: strategies like risk parity volatility targeting UH sixty forty portfolios.

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Speaker 1: Those are relatively easy to replicate using that that kind

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Speaker 1: of base level data. Now, Artemis is a long volatility

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Speaker 1: trading shop. We what we do is we we provide volatility,

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Speaker 1: long volatility and defensive solutions for our investors. So one

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Speaker 1: of the most type of popular strategies that has been

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Speaker 1: employed by many institutions are volatility overwriting strategies, either for

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Speaker 1: income or defensive purposes. And what we wanted to do

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Speaker 1: is to test these going back ninety three years. Of course,

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Speaker 1: how do you test a volatility strategy prior to the

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Speaker 1: existence of the options market, And that's that's not necessarily

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Speaker 1: something that's easy to do. So obviously you have to

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Speaker 1: make some assumptions and it becomes a bit of an

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Speaker 1: intellectual exercise, but I think the assumptions are very defensible

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Speaker 1: if one understands them. What we first did is we

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Speaker 1: we took options data that exists from the President. We're

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Speaker 1: able to solve for a volatility service. Volatility surface describes

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Speaker 1: the pricing of volatility at various out of the money points,

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Speaker 1: both for calls inputs. So that's the realized data, the

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Speaker 1: real data that we have. Now we don't have that

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Speaker 1: data going back obviously in the nineteen thirties or the

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Speaker 1: nineteen seventies, but we do have data on how equity

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Speaker 1: markets performed. We can calculate, for example, realized volatility on

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Speaker 1: ten thirty sixty day time frames. We can calculate the

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Speaker 1: rolling performance and next draw downs of equity markets over

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Speaker 1: those times, so those are observable inputs. So using our

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Speaker 1: arbitrage SBI ball surface that we solve for from real data,

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Speaker 1: we then were able to run a multi multi variable

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Speaker 1: regression to actually look at the last years and fit

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Speaker 1: a volatility surface based on observable market data. And then

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Speaker 1: what we did is we used that fitted data to

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Speaker 1: an essence, run various option trading strategies using a theoretical

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Speaker 1: volatility fit, and then we looked and compared that to

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Speaker 1: some of the most popular CBO vol indices, like the

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Speaker 1: buy right index and the put right index. And what

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Speaker 1: we were able to do is we were able to

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Speaker 1: replicate those indices using our theoretical volatility indications to generally

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Speaker 1: over a point eight five correlation and almost exacting performance.

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Speaker 1: So from there, what we're able to do now that

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Speaker 1: we have this kind of in sample history, we were

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Speaker 1: then able to apply that methodology to create a theoretical

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Speaker 1: volatility imply volatility service going all the way back. Now,

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Speaker 1: there are limitations in this because what you're naturally assuming

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Speaker 1: is that the way market participants price volatility over the

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Speaker 1: last thirty years would be very similar, would would be

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Speaker 1: similar to the way they would price it in the

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Speaker 1: thirties and the seventies and the fifties. Now we don't

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Speaker 1: know that for certain, right we don't. We're willing to

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Speaker 1: make that assumption to an essence, give give ourselves a

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Speaker 1: fairly realistic assessment on how strategies like UH put writing

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Speaker 1: or strategies like naked call selling would perform during those

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Speaker 1: time periods, and we received some very interesting results that

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Speaker 1: really give allocators a a sense on how these strategies

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Speaker 1: would perform outside of the incredible regime of the last

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Speaker 1: forty years. So you replicate the volatility performance from you know,

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Speaker 1: over a hundred years ago or ninety three years ago,

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Speaker 1: as you mentioned, you find that a technique that a

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Speaker 1: lot of investors who have been using in recent years

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Speaker 1: to pump up returns um again going short volatility doesn't

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Speaker 1: perform as well, or hasn't performed as well way back then, Like,

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Speaker 1: why exactly did that happen? What were the market conditions

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Speaker 1: in place that you think allowed for the under performance

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Speaker 1: of short fall. Well, you know, obviously over the many years,

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Speaker 1: I've been a critic of short volatility and that strategy,

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Speaker 1: and I also believe that long volatility is one of

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Speaker 1: the one of the most under allocated assets that is

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Speaker 1: out there today, and I think this paper and some

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Speaker 1: more analysis that we provided give support to that. So

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Speaker 1: I think saying short volatility strategies and what I mean

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Speaker 1: by that these are strategies that sell put options, or

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Speaker 1: maybe they sell call options, might be call overwriting by

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Speaker 1: right programs. These are strategies that that institutions have employed

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Speaker 1: in many ways to generate excess yield. Over the last

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Speaker 1: four years, they performed exceptionally well, largely because we've been

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Speaker 1: in an environment that has emphasized stability. Every single time

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Speaker 1: equity markets draw down, central banks are able to respond,

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Speaker 1: and that has produced an extremely mean reverting environment. That's

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Speaker 1: not always been the case. And let me kind of

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Speaker 1: explain why. Let's look at a period like the nine

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Speaker 1: over the entire decade of the nineteen thirties, volatility realized

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Speaker 1: at about that's incredible. So you know, Vaul was realizing

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Speaker 1: two thousand eight. Imagine two thousand eight for an entire decade. Obviously,

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Speaker 1: that does terrible things. Two portfolio that's continuously selling options meality.

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Speaker 1: But one of the surprise takeaways and I think people

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Speaker 1: would would appreciate appreciate this after the last year. You know,

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Speaker 1: like the original paper came out before the COVID crisis

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Speaker 1: and in many ways kind of predicted a lot of

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Speaker 1: the problems that we're experienced in the COVID crisis. Uh

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Speaker 1: in the in the reflation afterwards, Well naked call selling

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Speaker 1: was among the worst strategies that we looked at you

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Speaker 1: would think naked put selling would be or put put

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Speaker 1: writing would be the worst strategy. Naked call selling was terrible.

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Speaker 1: Why was naked call selling so bad? Well, if we

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Speaker 1: go back to the Great Depression, you have these incredible

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Speaker 1: drawdowns and equity markets. Central banks responded either by cutting rates,

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Speaker 1: by implementing programs, or by devaluing goal and you had

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Speaker 1: equally insane rallies in the market that were as violent

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Speaker 1: as the draw downs. So that that's something I think

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Speaker 1: that's so important for people to understand and really was

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Speaker 1: foreshadowing the We have this huge drop in March two

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Speaker 1: thousand twenty, we had this big explosion in April. Well,

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Speaker 1: if we look at the Great Depression, you know, after

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Speaker 1: a brutal three year decline of the market, rallied seventy

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Speaker 1: two percent in just one point five months in ninety two,

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Speaker 1: and that was after the signing of the Banking Act.

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Speaker 1: In nineteen thirty three, the market had an eight percent

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Speaker 1: rebound in just four point five months after Roosevelt devalued

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Speaker 1: the dollar. So you have these violent rallies that occur

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Speaker 1: during these periods of deflationary crises, and if you're selling

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Speaker 1: call options into those violent rallies. You can clearly understand

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Speaker 1: how bad that is. If you're doing covered call over writing,

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Speaker 1: it's clear how bad that is. Another period that was

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Speaker 1: really violent was the seventies where you had this kind

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Speaker 1: of right tail skew realization. Now, what does that mean.

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Speaker 1: Prior to the devaluation of gold in markets, markets used

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Speaker 1: to trend. Equity markets used to trend. They were auto correlated.

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Speaker 1: And what that meant is that if yesterday was up,

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Speaker 1: today it was likely to be up, and the next

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Speaker 1: day was likely to be up. So we reached this

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Speaker 1: kind of secular peak in trending of equity markets in

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Speaker 1: the nine seventies, and after the devaluation of gold, which

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Speaker 1: empowered central banks to be reactive, we began a multi

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Speaker 1: decade period where mean reversion ruled and last year represented

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Speaker 1: the highest peak in mean reversion. Another way of saying

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Speaker 1: that is nega voutle correlation. But really it's like if

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Speaker 1: yesterday was up, today was likely to be down, and

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Speaker 1: vice versa. The mean reversion and markets reached all time

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Speaker 1: highs in over a hundred years of history in trending markets.

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Speaker 1: That's really bad for short vault selling strategies because volatility

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Speaker 1: is comprised of well, naturally vall. You have the vega,

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Speaker 1: that's the volatility. But there's another component to options, which

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Speaker 1: is the gamma. In another way of saying, gammas trend.

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Speaker 1: So in for the greater part of seventy years, option

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Speaker 1: buyers would have profited from trend. But over the last

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Speaker 1: forty years, mean reversion has ruled, and that's largely been

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Speaker 1: been connected to the decline and interest rates and the

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Speaker 1: proactivity of central banks. So that's another reason why some

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Speaker 1: of these short volatility strategies dramatically underperformed. And we're incredible, uh,

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Speaker 1: I mean not only underperformed, I mean resulted in complete

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Speaker 1: and cataclismic loss of capital for about seventy years. I'd

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Speaker 1: love to get your take on how the volatility strategy

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Speaker 1: is actually performed last year, like in March, and whether

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Speaker 1: or not we've seen them build back up in the

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Speaker 1: months since, because I think that might help us get

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Speaker 1: a sense of like the direction that we're going in now.

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Speaker 1: There's a question as to what portfolio is most robust

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Speaker 1: and how do you build a robust portfolio. And one

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Speaker 1: of the conclusions that we had doing this ninety years

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Speaker 1: study of history was that to achieve a portfolio that

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Speaker 1: is optimal, what investors should do is that they should

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Speaker 1: prioritize long term correlations between asset classes over access returns.

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Speaker 1: And so we devised a portfolio that's radically different than

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Speaker 1: what many institutional portfolios have. That what this portfolio does

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Speaker 1: is it diversifies assets based on market regimes. And by

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Speaker 1: market regime, I mean regimes like inflation, deflation, and growth.

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Speaker 1: It diversifies assets based on market regime rather than asset classes.

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Speaker 1: So is an asset class diversification tool. Or the other

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Speaker 1: diversification diversification tool used by many investors is trailing volatility

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Speaker 1: and correlations. That's what's used by the strategies like risk Perry.

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Speaker 1: So the portfolio that we really recommended to perform consistently

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Speaker 1: over over ninety three years is obviously about about equity,

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Speaker 1: about high quality bonds, and this is where it gets

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Speaker 1: interesting approximately gold and precious metals. And I'll call that

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Speaker 1: feat alternative. Some people might actually put crypto in that today.

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Speaker 1: Obviously you can't test crypto going back trend and momentum strategies.

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Speaker 1: These would be managed future strategies that profit off trends

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Speaker 1: and commodities or currencies, and then finally long volatility and

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Speaker 1: defensive hedgie. What ends up happening in these different asset classes. Obviously,

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Speaker 1: obviously equities performed during periods of secular growth. Fixed income

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Speaker 1: performs during periods of relatively stable inflation and UH and deflation.

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Speaker 1: But you have a limit on fixed income at zero

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Speaker 1: bound obviously, and that that that's occurred in the history

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Speaker 1: before it happened kind of in the nine Now, long

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Speaker 1: volatility and trend and momentum perform in periods of deflation,

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Speaker 1: tremendous deflation, and tremendous inflation, So deflation like the thirties,

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Speaker 1: inflation like the seventies, and obviously fat alternatives like precious

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Speaker 1: metal perform in periods like the nineteen seventies where you

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Speaker 1: have tremendous stagflation and negative real rates. So you have

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Speaker 1: you're diversifying based on these market regimes. Now, we published

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Speaker 1: this paper at the beginning of last year. We didn't

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Speaker 1: have the opportunity to see in the future about what

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Speaker 1: would happen throughout two thousand twenty. I released a new

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Speaker 1: paper that talked about how this recommended portfolio performed through

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Speaker 1: two thousand twenty. It was exceptional performance, because, as you know,

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Speaker 1: two thousand twenty was like an entire business cycle condensed

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Speaker 1: into twelve months. The whole business cycle from January to

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Speaker 1: March that was like a nineteen thirties deflation. Then from

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Speaker 1: April to about August, we had this incredible fiat devaluation

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Speaker 1: with ten trillion dollars in global stimulus and this speculative

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Speaker 1: asset growth. That's that's uh, you know, some almost kind

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Speaker 1: of similar to type of scenario. As we entered the

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Speaker 1: the wintertime, we went into a reflationary scenario that began

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Speaker 1: to resemble kind of the onset of stagflation in the

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Speaker 1: late sixties. I mean that's where you have struggles and

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Speaker 1: interest rates. Interest rates began to rise at perform, but

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Speaker 1: then you have this expectation of a reset deepening of

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Speaker 1: the yield curve, and commodities began to perform. I mean,

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Speaker 1: lumber reached all time highs copper was exploding. So if

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Speaker 1: we look at how this portfolio that we call the

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Speaker 1: Dragon portfolio formed in that deflationary period in the first

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Speaker 1: part of the year, well, long volatility strategies were the

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Speaker 1: huge winners. They actually we're able to fill the gap

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Speaker 1: where equities drew down. So actually for this portfolio, that

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Speaker 1: first quarter gained about where sixty portfolios and risk parity

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Speaker 1: portfolios had huge underperformance because they were overreliant on bonds

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Speaker 1: as their defensive protection. So long volatility strategies is so

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Speaker 1: well and protected and helped you make money during that quarter.

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Speaker 1: Then during the FIATA valuation and the kind of growth

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Speaker 1: period after Central Bank stepped in, gold took its turn

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Speaker 1: performing in the summer, along with definitely crypto and other

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Speaker 1: assets like that, and then we had a huge outperformance

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Speaker 1: and equities. Then by the fall, we began to see

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Speaker 1: gold began to sell off, and we began to see

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Speaker 1: equities continued their upward trajectory. Fixed income began to sell off,

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Speaker 1: but trending commodities managed futures began to outperform, profiting from

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Speaker 1: the trends in commodities markets and the trends in these

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Speaker 1: other asset classes. So we had an entire business cycle

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Speaker 1: condensed into twelve months, and at each point these assets,

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Speaker 1: these market regime diversification benefits of the portfolio became really clear.

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Speaker 1: And this concept of this dragon portfolio that we introduced

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Speaker 1: actually would have returned close to last year where the

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Speaker 1: portfolio and risk parity portfolios only returned about on average

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Speaker 1: with over three times the max draw down. For people

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Speaker 1: who read our paper, this should not be a surprise.

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Speaker 1: It should not be a surprise because we saw this

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Speaker 1: happen in previous market cycles. But you have to look

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Speaker 1: at the periods outside the last forty years to understand that.

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Speaker 1: So I get the contention that if you're building a

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Speaker 1: portfolio that's going to outperform in these big regime changes,

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Speaker 1: then in when you basically had a compressed business cycle,

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Speaker 1: as you mentioned, it would do phenomenally well. But most

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Speaker 1: people would agree that was an extremely unusual year, and

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Speaker 1: I think most investment professionals are probably more used to

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Speaker 1: trying to pinpoint the regime changes as they come, rather

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Speaker 1: than build a portfolio that's going to outperform all types

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Speaker 1: of regimes for a hundred years. Right Like, there outlook

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Speaker 1: is always going to be you know, ten, twenty, maybe

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Speaker 1: thirty or forty years, but it's going to be much

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Speaker 1: much shorter than what you're talking about. So I guess

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Speaker 1: my question is like, how useful is this for your

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Speaker 1: average financial advisor or investor, and how do you encourage

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Speaker 1: people to think on a longer term horizon, or think

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Speaker 1: about diversification across regime changes rather than just trying to

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Speaker 1: pinpoint when a particular change is taking place in markets. Yeah,

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Speaker 1: I think one of the one of the phrases that

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Speaker 1: we say is do not fear, do not predict, prepare.

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Speaker 1: So if you are able to perfectly time and predict

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Speaker 1: the regime changes, and I tell you I can't, you know,

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Speaker 1: but if you're able to do that, you're Stanley Druckon Miller,

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Speaker 1: You're George Soros, and you should be a billionaire, right. Um,

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Speaker 1: The average retail investor, the average institutional investor, is not

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Speaker 1: able to necessarily time those changes perfectly. And even if

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Speaker 1: they're able to do so, if you're managing a fifty

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Speaker 1: billion dollar portfolio, if you're an institution, or a ten

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Speaker 1: billion dollar portfolio. I you're an institution, it's difficult to

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Speaker 1: tilt the portfolio. You have to choose some portfolio allocation.

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Speaker 1: And you know, my point is that the average pension

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Speaker 1: fund in America is approximately equity linked investments and approximately

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Speaker 1: in kind of fixed income and alternatives in cash. What

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Speaker 1: many of these institutions have done is they've crowded in

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Speaker 1: two assets like private equity kind of pretending that they're diversifiers.

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Speaker 1: But if you look at some of the Cambridge studies,

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Speaker 1: private equity has tremendous correlation to the business cycle. It's

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Speaker 1: not a diversifying asset by market regime. No, they've jumped

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Speaker 1: into vcs' is the same thing you jump into real estate.

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Speaker 1: It's the same problem. These are all asset classes that

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Speaker 1: are correlated to business cycles. Their long GDP asset classes

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Speaker 1: that are correlated to one growth regime. Now, in the past,

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Speaker 1: you could rely on fixed income to provide diversification, but

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Speaker 1: when fixed incomes at the zero bound, it fails to

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Speaker 1: provide great diversification. And anyone who studies the nineties would

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Speaker 1: have seen that problem. When we recreated risk parity portfolios

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Speaker 1: which rely heavily on fix income and lever the fixed income.

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Speaker 1: There's tremendous underperformance in the nineties when rates were near

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Speaker 1: the zero bound. So these institutions are assuming the last

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Speaker 1: forty years will repeat, and they're in essence levering equity linked,

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Speaker 1: not levering, but they're they're relying on this expectation of

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Speaker 1: equity link performance and these kind of false diversifiers to

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Speaker 1: reach their seven point to five percent return targets. I

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Speaker 1: think this is a huge mistake because if you remove

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Speaker 1: the last forty years, their performance is closer to to

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Speaker 1: five percent annualized abysmal, you know, using the allocations that

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Speaker 1: they have. So if they're not able to mate that

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Speaker 1: seven point five percent return target, you know, recency bias

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Speaker 1: becomes a problem that all of us are going to

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Speaker 1: pay for. And the reason being there's about one point

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Speaker 1: four trillion dollar US state and local pension deficit right now,

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Speaker 1: and that's assuming that they are able to hit their

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Speaker 1: return targets. If there's under performance, as one would expect

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Speaker 1: given current valuations and the current correlation mix of their investments,

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Speaker 1: you can expect that deficit to rise to anywhere between

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Speaker 1: three trillion dollars all the way to up to nine

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Speaker 1: trillion dollars. So in the last stimulus bill, there's a

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Speaker 1: lot of controversy over eighty five billion dollars in bailouts

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Speaker 1: for union pensions. And I'm not going to get another

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Speaker 1: politics on that, but if you can imagine that there's

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Speaker 1: a lot of tension over billion dollars, what's going to

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Speaker 1: happen when when the government's going to need to step

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Speaker 1: in and bail out PBOC and stay in the local

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Speaker 1: pension systems to the tune of three trillion dollars. It's

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Speaker 1: a big problem. Recency bias is a big, big issue.

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Speaker 1: The problem with many of these institutions that they bought

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Speaker 1: into the sharp ratio myth, the sharp ratio. They look

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Speaker 1: at these investments, be at private equity and these other

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Speaker 1: investments and they say, okay, what's the sharp ratio? We

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Speaker 1: want to we want to put together all of these

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Speaker 1: investments that have high sharp ratios. Well, the sharp ratio

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Speaker 1: if you go back and you read the original paper

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Speaker 1: that William Sharp wrote, you know, capital asset Prices, that

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Speaker 1: was the paper they wrote when it is thirty years

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Speaker 1: or old in nine four, it's clear that a sharp

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Speaker 1: ratio is not intended for components of the portfolio. The

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Speaker 1: sharp ratio should only be used for the aggregated portfolio.

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Speaker 1: You can't use a sharp ratio too to make judgments

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Speaker 1: on individual managers. Well, why why is that? Well, I'd

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Speaker 1: like to use this analogy to sports. When you're looking

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Speaker 1: at evaluating players to add to your favorite sports team.

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Speaker 1: If you're a general manager, you want to add players

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Speaker 1: that help you win. That's what you want what we

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Speaker 1: all know, whether your favorite sports basketball or whether it's soccer,

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Speaker 1: there are players on mediocre to bad teams with gaudy

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Speaker 1: statistics and maybe they have really good scoring averages or

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Speaker 1: goals averages, but they their statistics are padded and they

431
00:29:41,320 --> 00:29:43,720
Speaker 1: don't help their team win. And the reason is maybe

432
00:29:43,760 --> 00:29:46,320
Speaker 1: they don't play good defense, or maybe they dominate the ball,

433
00:29:46,840 --> 00:29:49,720
Speaker 1: maybe they have high turnovers, and maybe they're not making

434
00:29:49,760 --> 00:29:52,680
Speaker 1: hustle players that help their team win. So as a

435
00:29:52,680 --> 00:29:56,080
Speaker 1: result of that, sports management has gotten really smart about

436
00:29:56,560 --> 00:30:00,320
Speaker 1: selecting players and advanced statistics that measure or how a

437
00:30:00,360 --> 00:30:02,520
Speaker 1: player helps the team win. These are things like winds

438
00:30:02,560 --> 00:30:05,959
Speaker 1: over replacement value and plus minus ratios. Well, we have

439
00:30:06,040 --> 00:30:11,320
Speaker 1: no metric for that in the investment industry. So what

440
00:30:11,480 --> 00:30:14,600
Speaker 1: ends up happening is that these institutions by into this

441
00:30:14,760 --> 00:30:18,480
Speaker 1: myth of sharp ratios and they keep layering on investments

442
00:30:18,480 --> 00:30:21,600
Speaker 1: that have high sharp ratios. But what ends up happening

443
00:30:21,720 --> 00:30:24,440
Speaker 1: is that when you can put together a bunch of

444
00:30:24,440 --> 00:30:27,840
Speaker 1: investments that have high sharp ratio, but your portfolio will

445
00:30:27,880 --> 00:30:33,040
Speaker 1: have lower risk adjusted returns and higher drawdowns, it's really amazing.

446
00:30:33,440 --> 00:30:37,120
Speaker 1: And the reason is is that the sharp ratio doesn't

447
00:30:37,120 --> 00:30:40,960
Speaker 1: take into account the skew or the extreme right or

448
00:30:41,040 --> 00:30:44,760
Speaker 1: left hils of the investment. It doesn't take into the

449
00:30:44,760 --> 00:30:47,400
Speaker 1: account the correlations of that investment versus the rest of

450
00:30:47,440 --> 00:30:51,840
Speaker 1: your portfolio. So what happens here is that people have

451
00:30:51,880 --> 00:30:55,400
Speaker 1: bought into this myth that layering on top these managers

452
00:30:55,400 --> 00:30:58,040
Speaker 1: that have high sharp ratios will help them. It actually

453
00:30:58,120 --> 00:31:01,840
Speaker 1: is hurting your portfolio. And likewise, just like in sports,

454
00:31:01,840 --> 00:31:05,800
Speaker 1: there's some players with less impressive statistics. They may not

455
00:31:05,880 --> 00:31:09,240
Speaker 1: look good on paper, they're sharp, their their their point

456
00:31:09,280 --> 00:31:14,040
Speaker 1: averages might be lower, but they're doing things like playing vests.

457
00:31:14,120 --> 00:31:16,560
Speaker 1: They're helping the team win and that shows up in

458
00:31:16,600 --> 00:31:20,400
Speaker 1: the advanced metrics. Is this the moneyball theory for market investment?

459
00:31:20,960 --> 00:31:23,320
Speaker 1: It is? It is, and we are working on a

460
00:31:23,360 --> 00:31:25,400
Speaker 1: new paper that will develop this will come out in

461
00:31:25,440 --> 00:31:28,040
Speaker 1: the next couple of weeks that actually develops some of

462
00:31:28,040 --> 00:31:31,680
Speaker 1: these advanced metrics for institutions. But my point being is

463
00:31:31,760 --> 00:31:36,560
Speaker 1: that investments like long volatility, which don't look that good

464
00:31:36,560 --> 00:31:40,880
Speaker 1: on paper, you know, don't They don't have great sharp ratios,

465
00:31:40,920 --> 00:31:44,560
Speaker 1: but when you add them to your portfolio, they push

466
00:31:44,640 --> 00:31:47,840
Speaker 1: your portfolio out on the efficient frontier and result in

467
00:31:47,840 --> 00:31:53,040
Speaker 1: a better risk adjusted return for your portfolio. Assets like gold,

468
00:31:54,000 --> 00:31:59,040
Speaker 1: commodity trend advisors, and long volatility and defensive hedging, even

469
00:31:59,080 --> 00:32:02,080
Speaker 1: though they don't look a great on a sharp ratio basis,

470
00:32:02,520 --> 00:32:05,480
Speaker 1: you put them into the portfolio and they help your

471
00:32:05,520 --> 00:32:10,400
Speaker 1: portfolio win. That's what you really care about, and that's

472
00:32:10,440 --> 00:32:15,320
Speaker 1: what the average US pension institution and the average retail

473
00:32:15,360 --> 00:32:19,800
Speaker 1: investor fails I think to fully comprehend. And this is

474
00:32:19,840 --> 00:32:25,040
Speaker 1: so important because this sharp ratio problem is a social

475
00:32:25,120 --> 00:32:29,640
Speaker 1: problem because if we don't fix this, we are all

476
00:32:29,680 --> 00:32:32,320
Speaker 1: going to end up paying for it. So I really

477
00:32:32,360 --> 00:32:34,400
Speaker 1: am passionate about this. I really believe this. I think

478
00:32:34,440 --> 00:32:38,360
Speaker 1: the math proves this out, the history proves this out,

479
00:32:39,120 --> 00:32:41,440
Speaker 1: and I think these are some of the most undervalued

480
00:32:41,520 --> 00:32:44,880
Speaker 1: assets that one could put in the portfolio, even though

481
00:32:44,920 --> 00:32:46,960
Speaker 1: they may not look at that good on paper. We

482
00:32:47,040 --> 00:32:50,520
Speaker 1: need to stop evaluating the player and we need to

483
00:32:50,560 --> 00:32:54,000
Speaker 1: start evaluating the team. Now, that's how that's the secret

484
00:32:54,000 --> 00:32:57,640
Speaker 1: to building better portfolios. Right. So the idea is that

485
00:32:57,920 --> 00:33:01,239
Speaker 1: the whole of the portfolio can be stronger than the

486
00:33:01,280 --> 00:33:06,080
Speaker 1: individual components. Right, that's absolutely right. You know, paper, we

487
00:33:06,080 --> 00:33:09,760
Speaker 1: talked about this idea where you can choose two assets.

488
00:33:10,160 --> 00:33:12,120
Speaker 1: There are two assets that have high sharp ratios, but

489
00:33:12,120 --> 00:33:14,960
Speaker 1: they're highly correlated with another. There's another asset that is

490
00:33:14,960 --> 00:33:18,200
Speaker 1: a negative sharp ratio, but it's anti correlated. Actually, you'd

491
00:33:18,360 --> 00:33:21,680
Speaker 1: rather put together the negative sharp ratio that's anti correlated

492
00:33:21,720 --> 00:33:24,440
Speaker 1: with the with the one that there is a positive

493
00:33:24,440 --> 00:33:26,720
Speaker 1: sharp ratio, then the two sharp ratio the too high

494
00:33:26,720 --> 00:33:30,960
Speaker 1: sharp racial investment investments together. That results in a better portfolio.

495
00:33:31,200 --> 00:33:33,840
Speaker 1: And it's just mathematically true. But for some reason we

496
00:33:33,920 --> 00:33:39,320
Speaker 1: don't seem to see this. But sports, oddly, general managers

497
00:33:39,520 --> 00:33:43,480
Speaker 1: like Daryl Morey and you know, the h the managers

498
00:33:43,520 --> 00:33:47,280
Speaker 1: the Warriors understand this, this principle as applied to sports,

499
00:33:47,280 --> 00:34:05,960
Speaker 1: even though we're lacking it in investment management. There's one

500
00:34:05,960 --> 00:34:08,880
Speaker 1: other thing I want to ask you. You mentioned um

501
00:34:08,920 --> 00:34:12,319
Speaker 1: social value just then, and this idea that if we're

502
00:34:12,320 --> 00:34:15,600
Speaker 1: going to solve things like massive underfunding of pensions, then

503
00:34:15,680 --> 00:34:19,120
Speaker 1: people should grasp this concept of building a sort of

504
00:34:19,160 --> 00:34:22,560
Speaker 1: total portfolio versus just going after high returns in the

505
00:34:22,600 --> 00:34:26,120
Speaker 1: short term. There's one other thing that that kind of

506
00:34:26,120 --> 00:34:28,400
Speaker 1: caught my interest in the paper where you talk about

507
00:34:29,480 --> 00:34:33,680
Speaker 1: the potential for wealth distribution in some regimes. So this

508
00:34:33,760 --> 00:34:37,200
Speaker 1: idea that, um, you can get a backlash to a

509
00:34:37,280 --> 00:34:41,719
Speaker 1: market crash, you can get sort of populist pressures on

510
00:34:41,800 --> 00:34:47,200
Speaker 1: politicians that result in wealth redistribution, higher tax rates, things

511
00:34:47,239 --> 00:34:48,680
Speaker 1: like that, And I think a lot of people would

512
00:34:48,760 --> 00:34:52,279
Speaker 1: argue that maybe that's where we're heading. Now, how do

513
00:34:52,320 --> 00:34:56,280
Speaker 1: you actually protect a portfolio from wealth re distribution and

514
00:34:56,560 --> 00:35:00,799
Speaker 1: what does your dragon portfolio do it or perform in

515
00:35:00,800 --> 00:35:04,960
Speaker 1: that scenario. Well, it's it's really interesting and complex question,

516
00:35:05,320 --> 00:35:08,520
Speaker 1: and it really delves into a detailed analysis on the

517
00:35:08,600 --> 00:35:13,520
Speaker 1: individual components. So people have to realize that how this

518
00:35:13,560 --> 00:35:16,160
Speaker 1: ties in the last forty years because it's not just

519
00:35:16,239 --> 00:35:18,160
Speaker 1: been rates that have been going lower, but it's been

520
00:35:18,200 --> 00:35:21,080
Speaker 1: taxes that have been going lower. So a huge tax

521
00:35:21,160 --> 00:35:26,360
Speaker 1: cuts starting in the nine So that combination of low taxes, globalization,

522
00:35:27,080 --> 00:35:29,440
Speaker 1: lower and lower taxes, and lower interest rates has resulted

523
00:35:29,440 --> 00:35:32,960
Speaker 1: in this huge build up of debt and tremendous outperformance

524
00:35:33,160 --> 00:35:36,319
Speaker 1: in in in equity linked assets, private equity and all

525
00:35:36,320 --> 00:35:38,920
Speaker 1: these other long GDP assetss we'll call them because that's

526
00:35:38,920 --> 00:35:41,520
Speaker 1: what they are. Well, as we moved to an income

527
00:35:41,560 --> 00:35:45,120
Speaker 1: rey just distribution type of world that presents a heavy,

528
00:35:45,640 --> 00:35:51,000
Speaker 1: heavy burden on equities, on real estate, on private equity.

529
00:35:51,480 --> 00:35:54,120
Speaker 1: It's a big issue for two reasons. First of all,

530
00:35:54,200 --> 00:35:56,880
Speaker 1: you know, excessive regulation is going to cause problems in

531
00:35:56,920 --> 00:36:00,480
Speaker 1: those asset classes. Obviously, if you're allocated seventy percent in

532
00:36:00,520 --> 00:36:03,920
Speaker 1: those assets, that's that's a huge issue. Um. The second

533
00:36:04,040 --> 00:36:07,960
Speaker 1: driver is that, look, we have the highest fiscal deficits

534
00:36:08,200 --> 00:36:10,960
Speaker 1: since World War Two, and they're likely only only to

535
00:36:11,040 --> 00:36:14,480
Speaker 1: be going up. We have unprecedented monetary policy, and we

536
00:36:14,520 --> 00:36:17,120
Speaker 1: have the highest levels of corporate debt in American history

537
00:36:17,160 --> 00:36:20,280
Speaker 1: as a percentage to GDP. These are all true facts.

538
00:36:20,320 --> 00:36:23,560
Speaker 1: So the problem with keeping interest rates so low is

539
00:36:23,600 --> 00:36:27,120
Speaker 1: that it exacerbates the wealth divide. In addition to all

540
00:36:27,160 --> 00:36:30,120
Speaker 1: of these extreme factors on the excessive debt, we also

541
00:36:30,200 --> 00:36:35,360
Speaker 1: have the highest income disparity in American history that is

542
00:36:35,400 --> 00:36:38,400
Speaker 1: equaled only by the Great Depression prior to the Great Depression.

543
00:36:38,840 --> 00:36:42,200
Speaker 1: This puts tremendous political pressure. You can't just keep rates

544
00:36:42,320 --> 00:36:44,880
Speaker 1: low and do the Japan experiment because you're gonna have

545
00:36:44,880 --> 00:36:48,680
Speaker 1: a social social explosion. And you know, I talked about

546
00:36:48,680 --> 00:36:50,800
Speaker 1: this in the New York Times. I gave an article

547
00:36:50,840 --> 00:36:53,360
Speaker 1: back in two thousand seventeen that was prior to my

548
00:36:53,400 --> 00:36:56,000
Speaker 1: Orables paper where I talked about the blow up involved,

549
00:36:56,400 --> 00:36:57,680
Speaker 1: and I said, well, you know, if the if the

550
00:36:57,680 --> 00:37:03,240
Speaker 1: FED wants to suppress volatility indefinitely, well that's something that

551
00:37:03,280 --> 00:37:05,399
Speaker 1: you know, they can do that, But volatility can never

552
00:37:05,480 --> 00:37:08,360
Speaker 1: be destroyed. It can only be transmuted in form and time.

553
00:37:08,960 --> 00:37:12,000
Speaker 1: So if you're going to suppress asset price volatility using

554
00:37:12,000 --> 00:37:15,799
Speaker 1: monetary policy, that volatility is going to come out in

555
00:37:15,840 --> 00:37:19,319
Speaker 1: a different way, and that way is through social instability.

556
00:37:19,400 --> 00:37:21,080
Speaker 1: And I said, hey, my, you know my hedge fund,

557
00:37:21,360 --> 00:37:24,919
Speaker 1: which seeks to protect against market crashes. Now that's something

558
00:37:24,920 --> 00:37:27,960
Speaker 1: I feel pretty confident about being able to protect against.

559
00:37:28,360 --> 00:37:31,680
Speaker 1: But what you can never protect against is a social revolution,

560
00:37:31,680 --> 00:37:33,600
Speaker 1: and I think we're starting to see the seeds of that.

561
00:37:34,160 --> 00:37:36,960
Speaker 1: Of course, one of the ways that governments can stem

562
00:37:37,000 --> 00:37:40,799
Speaker 1: that off is by fiscal stimulus giving on money. But

563
00:37:40,880 --> 00:37:46,319
Speaker 1: that's stagflationary, that's tremendously stagflationary, and so I think that's

564
00:37:46,360 --> 00:37:48,920
Speaker 1: the that's the route that maybe is the path at

565
00:37:49,000 --> 00:37:51,840
Speaker 1: least resistance, where you know you have you can destroy

566
00:37:51,880 --> 00:37:53,600
Speaker 1: debt in two ways. You can default on the debt

567
00:37:54,280 --> 00:37:57,120
Speaker 1: or you can print money, and you can do tremendous

568
00:37:57,160 --> 00:37:59,359
Speaker 1: stimulus and you can inflate your way out of the debt,

569
00:37:59,480 --> 00:38:02,920
Speaker 1: and we maybe choosing the inflation route. Well, that's going

570
00:38:02,960 --> 00:38:07,919
Speaker 1: to rereak havoc on the institutional portfolio because people don't

571
00:38:07,960 --> 00:38:10,279
Speaker 1: realize this. Equities, what is in the seventies were in

572
00:38:10,280 --> 00:38:13,920
Speaker 1: a great depression on a real adjusted basis. So the

573
00:38:14,120 --> 00:38:18,440
Speaker 1: draw down on a real basis after inflation was was

574
00:38:18,560 --> 00:38:22,440
Speaker 1: as bad as the draw down in the es. But

575
00:38:23,320 --> 00:38:26,719
Speaker 1: the reason that people didn't feel it that that that

576
00:38:26,800 --> 00:38:30,719
Speaker 1: was that bad was because we were inflating away the problems.

577
00:38:31,239 --> 00:38:33,279
Speaker 1: Of course that led to you know, rent control and

578
00:38:33,320 --> 00:38:37,920
Speaker 1: all these other issues. So if we go the inflation

579
00:38:38,000 --> 00:38:42,279
Speaker 1: stagflation route, you're going to see equities destroyed on a

580
00:38:42,320 --> 00:38:45,840
Speaker 1: real adjusted basis, and you're going to see bonds obviously

581
00:38:45,920 --> 00:38:50,239
Speaker 1: destroyed because rates go up. Well, guess what performs that

582
00:38:50,360 --> 00:38:55,000
Speaker 1: environment if we go back to our Dragon portfolio. Well,

583
00:38:55,280 --> 00:38:57,600
Speaker 1: at any point in the Dragon portfolio has two out

584
00:38:57,680 --> 00:39:02,160
Speaker 1: of the five thematic regime classes me so what performs

585
00:39:02,239 --> 00:39:05,719
Speaker 1: really well in a stagflationary environment, Well, precious metals and gold.

586
00:39:05,960 --> 00:39:09,920
Speaker 1: You had a price increase in gold, we'd presume that

587
00:39:09,960 --> 00:39:12,239
Speaker 1: crypto would be part of that um but there's a

588
00:39:12,239 --> 00:39:14,400
Speaker 1: lot of questions on crypto. The other thing that performs

589
00:39:14,400 --> 00:39:19,960
Speaker 1: extra extremely well is commodity trend and trending trending commodities,

590
00:39:19,960 --> 00:39:22,719
Speaker 1: So the ct A Sleep portfolio performs really well. So

591
00:39:22,719 --> 00:39:25,440
Speaker 1: those are strategies that take into account momentum. And so

592
00:39:25,480 --> 00:39:28,480
Speaker 1: we're seeing that this year, you know where lumber prices

593
00:39:28,480 --> 00:39:31,200
Speaker 1: are exploding d all time highest coppers up, all these

594
00:39:31,200 --> 00:39:36,359
Speaker 1: commodities are trending tremendously higher. So in this sense, if

595
00:39:36,400 --> 00:39:41,040
Speaker 1: you have of your portfolio allocated two assets that can

596
00:39:41,239 --> 00:39:44,440
Speaker 1: play off of the stagflation, you're gonna be okay, You're

597
00:39:44,440 --> 00:39:46,920
Speaker 1: gonna do well. That will make up for your suffering

598
00:39:47,680 --> 00:39:51,680
Speaker 1: stock and bond exposure. In addition, long volatility can make

599
00:39:51,719 --> 00:39:54,879
Speaker 1: money in right tail events and stagflation as well. If

600
00:39:54,920 --> 00:39:58,279
Speaker 1: we go into kind of a Japan environment, well, you

601
00:39:58,280 --> 00:40:01,920
Speaker 1: know that that's a scenario where long volatility tends to outperform,

602
00:40:01,960 --> 00:40:04,719
Speaker 1: and you know you have stability and fixed income and

603
00:40:04,760 --> 00:40:08,040
Speaker 1: it kind of has stable returns in in inequities. So

604
00:40:08,360 --> 00:40:10,680
Speaker 1: I think you can't necessarily. It goes back to that idea,

605
00:40:10,800 --> 00:40:15,440
Speaker 1: don't predict, prepare, and and thrive from change. And and

606
00:40:15,480 --> 00:40:19,080
Speaker 1: that's when we look at risk in terms of thematic baskets.

607
00:40:19,719 --> 00:40:22,319
Speaker 1: Regardless of what regime you're in, at least two to

608
00:40:22,400 --> 00:40:25,200
Speaker 1: three of the thematic baskets or market regime baskets are

609
00:40:25,239 --> 00:40:29,399
Speaker 1: outperforming and that saves your portfolio, and that that way

610
00:40:29,440 --> 00:40:32,320
Speaker 1: you don't necessarily need to predict the winds of political change.

611
00:40:32,719 --> 00:40:35,000
Speaker 1: All you need to do is to have a balanced

612
00:40:35,040 --> 00:40:38,320
Speaker 1: allocation so you're prepared throughout any regime. I really stressed

613
00:40:38,360 --> 00:40:43,319
Speaker 1: that this is something that the investment allocation problem, the

614
00:40:43,360 --> 00:40:48,000
Speaker 1: portfolio allocation problem, is a social problem. We have a

615
00:40:48,040 --> 00:40:51,800
Speaker 1: window of opportunity. This is both on a pension systems

616
00:40:51,800 --> 00:40:56,160
Speaker 1: institutional investors and for individual investors. There's a window of

617
00:40:56,200 --> 00:41:00,680
Speaker 1: opportunity to create portfolios that are rebut dust and are

618
00:41:00,719 --> 00:41:03,960
Speaker 1: able to thrive through these different regimes. You know, my

619
00:41:03,960 --> 00:41:06,759
Speaker 1: paper of the allegory, the Hawk Conserpent released last year

620
00:41:06,760 --> 00:41:09,480
Speaker 1: in January, and the follow up to that paper that

621
00:41:09,680 --> 00:41:12,759
Speaker 1: chronicled how those ideas performed in two thou twenty that

622
00:41:12,880 --> 00:41:15,879
Speaker 1: was just released, really make the case, and I think

623
00:41:16,239 --> 00:41:19,839
Speaker 1: a very important case that this is. This is this

624
00:41:19,920 --> 00:41:23,120
Speaker 1: is vital if you want to profit and be able

625
00:41:23,160 --> 00:41:26,200
Speaker 1: to survive periods of secular change. And this is not

626
00:41:26,280 --> 00:41:30,680
Speaker 1: just an intellectual argument about portfolio construction. It is a

627
00:41:30,760 --> 00:41:33,680
Speaker 1: social problem if we don't address this, because the pension

628
00:41:33,760 --> 00:41:37,839
Speaker 1: underfunding is going to get massive and we are going

629
00:41:37,880 --> 00:41:40,440
Speaker 1: to pay for that. Now, we could pay for it

630
00:41:40,480 --> 00:41:43,480
Speaker 1: through government bailouts, or we could pay for it through

631
00:41:43,560 --> 00:41:49,279
Speaker 1: loss of purchasing power from inflation. But the asset allocation

632
00:41:49,360 --> 00:41:54,000
Speaker 1: problem is a social problem, and I think institutions and

633
00:41:54,000 --> 00:41:59,280
Speaker 1: retirees really need to strongly look at diversifiers that profit

634
00:41:59,680 --> 00:42:02,600
Speaker 1: from left and right tail events and profit from trend

635
00:42:03,160 --> 00:42:06,839
Speaker 1: and those are asset classes underlooked asset classes like long volatility,

636
00:42:07,080 --> 00:42:12,879
Speaker 1: commodity trend and precious metals and fiat alternatives, and those

637
00:42:12,920 --> 00:42:16,719
Speaker 1: are just as important as equities in the portfolio. Chris,

638
00:42:16,719 --> 00:42:19,240
Speaker 1: what's the name of the new paper? The new paper

639
00:42:19,239 --> 00:42:21,600
Speaker 1: which is available on our website. It's called Rise of

640
00:42:21,600 --> 00:42:26,640
Speaker 1: the Dragon. I I love these UH metaphors and visuals, UM,

641
00:42:26,719 --> 00:42:29,920
Speaker 1: but I really encourage people to do deep dives into

642
00:42:29,920 --> 00:42:33,319
Speaker 1: the papers because I think there's a lot of quantitative analytics. UM.

643
00:42:33,360 --> 00:42:36,040
Speaker 1: Everyone read the first paper. People didn't. Actually, not a

644
00:42:36,040 --> 00:42:39,080
Speaker 1: lot of people read the appendix, which was twice as

645
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Speaker 1: long as the paper and contained much more detailed quantitative notes. Um.

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Speaker 1: So you know, both of those papers are available on

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Speaker 1: our website www. Artemus cm dot com, and occasionally tweet

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Speaker 1: about these things too. Yeah, I'll mention your handle at

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Speaker 1: the end of this. But in the meantime, everyone has

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Speaker 1: some you know, light weekend reading in the form of

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Speaker 1: a twenty page appendix from your paper. So that's sorry,

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Speaker 1: a detailed twenty page abendonment talks about a ball surface

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Speaker 1: and and rispirity replication to the thirties. So all right, Chris,

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Speaker 1: it's lovely having you on as always. That was Chris Cole,

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Speaker 1: the founder of Artemis Capital. Thank you so much. Thank you, Tracy.

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Speaker 1: Great to be back. So I'm going to avoid recording

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Speaker 1: a monologue here because I think it would be weird

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Speaker 1: for me to talk to myself about what I found

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Speaker 1: interesting in that conversation. But I do encourage you to

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Speaker 1: take a look at Chris's paper. It's not very often

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Speaker 1: that you get to see someone modeling volatility surfaces from

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Speaker 1: the Great Depression, so whenever you get that chance, you

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Speaker 1: should seize it. All right, this has been another episode

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Speaker 1: of the All Thoughts podcast. I'm Tracy Alloway. You can

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Speaker 1: follow me on Twitter at Tracy Alloway. You can also

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Speaker 1: follow our guest Chris Cole. He is at vall under

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Speaker 1: Dash Christopher, and you should also follow all of the

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00:44:16,239 --> 00:44:20,839
Speaker 1: Bloomberg Podcast. You can find them on Twitter at podcast.

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Speaker 1: You should definitely follow our producer Laura Carlson. She is

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Speaker 1: on Twitter at Laura M Carlson. And you should follow

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Speaker 1: Bloomberg's head of podcast, francesco Leavie. She is at Francesca Today.

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Speaker 1: Thanks for listening, t