Speaker 1: Hello, and welcome to another episode of the All Thoughts podcast.
Speaker 1: I'm Tracy Alloway. My co host Joe Wisenthal couldn't make
Speaker 1: it today, So I'm looking at a chart of the
Speaker 1: SMP five hundred, and let's see, it's almost exactly one
Speaker 1: year post the big dip in the SMP five hundred,
Speaker 1: the massive crash that we saw back in March, and
Speaker 1: of course we've seen risk assets come roaring back. But
Speaker 1: with the recovery in financial assets, we have a lot
Speaker 1: of questions over how long can this continue? Are we
Speaker 1: on the verge of some sort of big change in
Speaker 1: the market as central banks unleash fiscal stimulus and interest
Speaker 1: rates remain at or close to the zero bound. Are
Speaker 1: we going to get inflation? Are we going to get stagflation?
Speaker 1: Are we going to see perhaps even deflation? Is there
Speaker 1: any way we're ever going to get out of this
Speaker 1: regime of low inflation? And I think whenever we have
Speaker 1: these big turning points in markets, or when we have
Speaker 1: lots of people talking about the potential for big turning
Speaker 1: points and markets, we also have a lot of opinions
Speaker 1: on how those are going to go and what type
Speaker 1: of portfolio would perform best, And of course we've seen
Speaker 1: a lot of handwringing recently around growth versus value sixty
Speaker 1: forty what happens when both bonds and stocks fall at
Speaker 1: the same time. It's on today's show we're going to
Speaker 1: be discussing exactly this idea. How do you build a
Speaker 1: portfolio that can withstand these regime changes and basically outperform
Speaker 1: over a really long time horizon. And I'm excited to
Speaker 1: say our guest for this episode is Chris Cole, the
Speaker 1: founder of Artemis Capital. He's appeared on all lots previously,
Speaker 1: digging deep into the low volatility regime of the past years.
Speaker 1: It's great to have him back. He publishes some excellent research. Chris,
Speaker 1: thanks for coming on the show again. Thanks Tracy, it's
Speaker 1: great to be back on the show. So, uh, I
Speaker 1: guess my first question is you know the reason we're
Speaker 1: having this discussion is you published a paper called the
Speaker 1: Allegory of the Hawk and Serpent, How to grow and
Speaker 1: protect wealth for a hundred years now. Most investors aren't
Speaker 1: really looking at their portfolios on a hundred year basis.
Speaker 1: What sparked your interest in that kind of time frame?
Speaker 1: What's really interesting about in particular the last forty years,
Speaker 1: is that there's a tremendous recency bias that market participants have.
Speaker 1: The last forty years are incredibly unusual comparative to overall history,
Speaker 1: and I believe, as I make the case in the paper,
Speaker 1: that recency biases is now a systemic risk. The price
Speaker 1: appreciation for a classic sixty forty portfolio over the last
Speaker 1: ninety three years has come from just the twenty two
Speaker 1: years between night four to two thousand seven. So what
Speaker 1: we've had is this incredible out performance of both stocks
Speaker 1: and bonds that has been from a reinforcing cycle, and
Speaker 1: we use the allegory of the serpent for that, and
Speaker 1: that's been led by falling interest rates. Rates fell from
Speaker 1: seventeen percent to zero percent. There's been incredible favorable demographics
Speaker 1: as baby boomers to come into the workforce, falling taxes.
Speaker 1: Taxes have fallen to near a hundred year lows, globalization
Speaker 1: on precedent of monetary policy, and we now have some
Speaker 1: of the highest levels of both governments and corporate debt
Speaker 1: in American history. So as a result of this, there's
Speaker 1: been this incredible out performance of stocks and bonds over
Speaker 1: the last forty years. But the trillion dollar question that
Speaker 1: I think is important for any allocator is is this repeatable?
Speaker 1: And I actually believe that the factors that drove this
Speaker 1: generational boom in the stocks and bonds are are now reversing.
Speaker 1: We're now on a framework where debts at all time highs,
Speaker 1: the middle class hasn't seen real wage growth since the
Speaker 1: nineteen seventies, and demographics are really poor, and interest rates
Speaker 1: can't go any lower. So investors expecting the games in
Speaker 1: the last four years are likely to be extremely disappointed.
Speaker 1: And so to kind of understand what the next twenty
Speaker 1: years are going to look like and how to build
Speaker 1: a portfolio that will last um and can manage through
Speaker 1: this period of secular change, what I did is I
Speaker 1: went back through history and I recreated all of these
Speaker 1: financial engineering strategies, UH using I think defensible assumptions over
Speaker 1: the last years. And we know that you know, history
Speaker 1: doesn't repeat, but it rhymes. And my my goal was
Speaker 1: to figure out what portfolio can consistently perform to every
Speaker 1: market cycle, whether it's secular growth, whether it's inflation, whether
Speaker 1: it's deflation. And I think I came up with some
Speaker 1: really interesting answers in my paper last year in the
Speaker 1: follow up paper that I just released that really answers
Speaker 1: the questions as to what type of portfolio really sustains
Speaker 1: wealth and capital appreciation and limits draw downs. And the
Speaker 1: answer that I got is radically different from the type
Speaker 1: of portfolio that many institutions and retail investors are currently
Speaker 1: are currently allocating too. I have so many questions already,
Speaker 1: but one that jumps out at me is going back
Speaker 1: a hundred years and trying to reconstruct modern portfolios against
Speaker 1: financial assets in the nine twenties and nineteen thirties. How
Speaker 1: exactly did you do that? Because I'm looking at the paper,
Speaker 1: and you know, you look at things like naked call selling,
Speaker 1: how that perform during the Great Depression? I'm just curious
Speaker 1: how you recreated, uh, those portfolios. Absolutely, it's a It's
Speaker 1: an incredible question. And I think one of the one
Speaker 1: of the things that I think is very important to
Speaker 1: understand about about this exercise is that we don't necessarily
Speaker 1: say that these portfolios are realized performance, but they are
Speaker 1: best effort at understanding how a given financial engineering strategy
Speaker 1: might have performed in the past. And I think there's
Speaker 1: a lot of defensible assumptions you know, first of all,
Speaker 1: we start with a wealth of observable data. There is
Speaker 1: data that we can gather off from history, namely the
Speaker 1: composite SMP five hundred prices, from stock data the top
Speaker 1: companies at a given point in time. There's obviously gold data,
Speaker 1: interest rate data, there's data on commodities and that that's
Speaker 1: a starting point um and we use that data from
Speaker 1: the global financial database. From there, what we can do
Speaker 1: is we can construct some UH and replicate some basic
Speaker 1: strategies like risk parity volatility targeting UH sixty forty portfolios.
Speaker 1: Those are relatively easy to replicate using that that kind
Speaker 1: of base level data. Now, Artemis is a long volatility
Speaker 1: trading shop. We what we do is we we provide volatility,
Speaker 1: long volatility and defensive solutions for our investors. So one
Speaker 1: of the most type of popular strategies that has been
Speaker 1: employed by many institutions are volatility overwriting strategies, either for
Speaker 1: income or defensive purposes. And what we wanted to do
Speaker 1: is to test these going back ninety three years. Of course,
Speaker 1: how do you test a volatility strategy prior to the
Speaker 1: existence of the options market, And that's that's not necessarily
Speaker 1: something that's easy to do. So obviously you have to
Speaker 1: make some assumptions and it becomes a bit of an
Speaker 1: intellectual exercise, but I think the assumptions are very defensible
Speaker 1: if one understands them. What we first did is we
Speaker 1: we took options data that exists from the President. We're
Speaker 1: able to solve for a volatility service. Volatility surface describes
Speaker 1: the pricing of volatility at various out of the money points,
Speaker 1: both for calls inputs. So that's the realized data, the
Speaker 1: real data that we have. Now we don't have that
Speaker 1: data going back obviously in the nineteen thirties or the
Speaker 1: nineteen seventies, but we do have data on how equity
Speaker 1: markets performed. We can calculate, for example, realized volatility on
Speaker 1: ten thirty sixty day time frames. We can calculate the
Speaker 1: rolling performance and next draw downs of equity markets over
Speaker 1: those times, so those are observable inputs. So using our
Speaker 1: arbitrage SBI ball surface that we solve for from real data,
Speaker 1: we then were able to run a multi multi variable
Speaker 1: regression to actually look at the last years and fit
Speaker 1: a volatility surface based on observable market data. And then
Speaker 1: what we did is we used that fitted data to
Speaker 1: an essence, run various option trading strategies using a theoretical
Speaker 1: volatility fit, and then we looked and compared that to
Speaker 1: some of the most popular CBO vol indices, like the
Speaker 1: buy right index and the put right index. And what
Speaker 1: we were able to do is we were able to
Speaker 1: replicate those indices using our theoretical volatility indications to generally
Speaker 1: over a point eight five correlation and almost exacting performance.
Speaker 1: So from there, what we're able to do now that
Speaker 1: we have this kind of in sample history, we were
Speaker 1: then able to apply that methodology to create a theoretical
Speaker 1: volatility imply volatility service going all the way back. Now,
Speaker 1: there are limitations in this because what you're naturally assuming
Speaker 1: is that the way market participants price volatility over the
Speaker 1: last thirty years would be very similar, would would be
Speaker 1: similar to the way they would price it in the
Speaker 1: thirties and the seventies and the fifties. Now we don't
Speaker 1: know that for certain, right we don't. We're willing to
Speaker 1: make that assumption to an essence, give give ourselves a
Speaker 1: fairly realistic assessment on how strategies like UH put writing
Speaker 1: or strategies like naked call selling would perform during those
Speaker 1: time periods, and we received some very interesting results that
Speaker 1: really give allocators a a sense on how these strategies
Speaker 1: would perform outside of the incredible regime of the last
Speaker 1: forty years. So you replicate the volatility performance from you know,
Speaker 1: over a hundred years ago or ninety three years ago,
Speaker 1: as you mentioned, you find that a technique that a
Speaker 1: lot of investors who have been using in recent years
Speaker 1: to pump up returns um again going short volatility doesn't
Speaker 1: perform as well, or hasn't performed as well way back then, Like,
Speaker 1: why exactly did that happen? What were the market conditions
Speaker 1: in place that you think allowed for the under performance
Speaker 1: of short fall. Well, you know, obviously over the many years,
Speaker 1: I've been a critic of short volatility and that strategy,
Speaker 1: and I also believe that long volatility is one of
Speaker 1: the one of the most under allocated assets that is
Speaker 1: out there today, and I think this paper and some
Speaker 1: more analysis that we provided give support to that. So
Speaker 1: I think saying short volatility strategies and what I mean
Speaker 1: by that these are strategies that sell put options, or
Speaker 1: maybe they sell call options, might be call overwriting by
Speaker 1: right programs. These are strategies that that institutions have employed
Speaker 1: in many ways to generate excess yield. Over the last
Speaker 1: four years, they performed exceptionally well, largely because we've been
Speaker 1: in an environment that has emphasized stability. Every single time
Speaker 1: equity markets draw down, central banks are able to respond,
Speaker 1: and that has produced an extremely mean reverting environment. That's
Speaker 1: not always been the case. And let me kind of
Speaker 1: explain why. Let's look at a period like the nine
Speaker 1: over the entire decade of the nineteen thirties, volatility realized
Speaker 1: at about that's incredible. So you know, Vaul was realizing
Speaker 1: two thousand eight. Imagine two thousand eight for an entire decade. Obviously,
Speaker 1: that does terrible things. Two portfolio that's continuously selling options meality.
Speaker 1: But one of the surprise takeaways and I think people
Speaker 1: would would appreciate appreciate this after the last year. You know,
Speaker 1: like the original paper came out before the COVID crisis
Speaker 1: and in many ways kind of predicted a lot of
Speaker 1: the problems that we're experienced in the COVID crisis. Uh
Speaker 1: in the in the reflation afterwards, Well naked call selling
Speaker 1: was among the worst strategies that we looked at you
Speaker 1: would think naked put selling would be or put put
Speaker 1: writing would be the worst strategy. Naked call selling was terrible.
Speaker 1: Why was naked call selling so bad? Well, if we
Speaker 1: go back to the Great Depression, you have these incredible
Speaker 1: drawdowns and equity markets. Central banks responded either by cutting rates,
Speaker 1: by implementing programs, or by devaluing goal and you had
Speaker 1: equally insane rallies in the market that were as violent
Speaker 1: as the draw downs. So that that's something I think
Speaker 1: that's so important for people to understand and really was
Speaker 1: foreshadowing the We have this huge drop in March two
Speaker 1: thousand twenty, we had this big explosion in April. Well,
Speaker 1: if we look at the Great Depression, you know, after
Speaker 1: a brutal three year decline of the market, rallied seventy
Speaker 1: two percent in just one point five months in ninety two,
Speaker 1: and that was after the signing of the Banking Act.
Speaker 1: In nineteen thirty three, the market had an eight percent
Speaker 1: rebound in just four point five months after Roosevelt devalued
Speaker 1: the dollar. So you have these violent rallies that occur
Speaker 1: during these periods of deflationary crises, and if you're selling
Speaker 1: call options into those violent rallies. You can clearly understand
Speaker 1: how bad that is. If you're doing covered call over writing,
Speaker 1: it's clear how bad that is. Another period that was
Speaker 1: really violent was the seventies where you had this kind
Speaker 1: of right tail skew realization. Now, what does that mean.
Speaker 1: Prior to the devaluation of gold in markets, markets used
Speaker 1: to trend. Equity markets used to trend. They were auto correlated.
Speaker 1: And what that meant is that if yesterday was up,
Speaker 1: today it was likely to be up, and the next
Speaker 1: day was likely to be up. So we reached this
Speaker 1: kind of secular peak in trending of equity markets in
Speaker 1: the nine seventies, and after the devaluation of gold, which
Speaker 1: empowered central banks to be reactive, we began a multi
Speaker 1: decade period where mean reversion ruled and last year represented
Speaker 1: the highest peak in mean reversion. Another way of saying
Speaker 1: that is nega voutle correlation. But really it's like if
Speaker 1: yesterday was up, today was likely to be down, and
Speaker 1: vice versa. The mean reversion and markets reached all time
Speaker 1: highs in over a hundred years of history in trending markets.
Speaker 1: That's really bad for short vault selling strategies because volatility
Speaker 1: is comprised of well, naturally vall. You have the vega,
Speaker 1: that's the volatility. But there's another component to options, which
Speaker 1: is the gamma. In another way of saying, gammas trend.
Speaker 1: So in for the greater part of seventy years, option
Speaker 1: buyers would have profited from trend. But over the last
Speaker 1: forty years, mean reversion has ruled, and that's largely been
Speaker 1: been connected to the decline and interest rates and the
Speaker 1: proactivity of central banks. So that's another reason why some
Speaker 1: of these short volatility strategies dramatically underperformed. And we're incredible, uh,
Speaker 1: I mean not only underperformed, I mean resulted in complete
Speaker 1: and cataclismic loss of capital for about seventy years. I'd
Speaker 1: love to get your take on how the volatility strategy
Speaker 1: is actually performed last year, like in March, and whether
Speaker 1: or not we've seen them build back up in the
Speaker 1: months since, because I think that might help us get
Speaker 1: a sense of like the direction that we're going in now.
Speaker 1: There's a question as to what portfolio is most robust
Speaker 1: and how do you build a robust portfolio. And one
Speaker 1: of the conclusions that we had doing this ninety years
Speaker 1: study of history was that to achieve a portfolio that
Speaker 1: is optimal, what investors should do is that they should
Speaker 1: prioritize long term correlations between asset classes over access returns.
Speaker 1: And so we devised a portfolio that's radically different than
Speaker 1: what many institutional portfolios have. That what this portfolio does
Speaker 1: is it diversifies assets based on market regimes. And by
Speaker 1: market regime, I mean regimes like inflation, deflation, and growth.
Speaker 1: It diversifies assets based on market regime rather than asset classes.
Speaker 1: So is an asset class diversification tool. Or the other
Speaker 1: diversification diversification tool used by many investors is trailing volatility
Speaker 1: and correlations. That's what's used by the strategies like risk Perry.
Speaker 1: So the portfolio that we really recommended to perform consistently
Speaker 1: over over ninety three years is obviously about about equity,
Speaker 1: about high quality bonds, and this is where it gets
Speaker 1: interesting approximately gold and precious metals. And I'll call that
Speaker 1: feat alternative. Some people might actually put crypto in that today.
Speaker 1: Obviously you can't test crypto going back trend and momentum strategies.
Speaker 1: These would be managed future strategies that profit off trends
Speaker 1: and commodities or currencies, and then finally long volatility and
Speaker 1: defensive hedgie. What ends up happening in these different asset classes. Obviously,
Speaker 1: obviously equities performed during periods of secular growth. Fixed income
Speaker 1: performs during periods of relatively stable inflation and UH and deflation.
Speaker 1: But you have a limit on fixed income at zero
Speaker 1: bound obviously, and that that that's occurred in the history
Speaker 1: before it happened kind of in the nine Now, long
Speaker 1: volatility and trend and momentum perform in periods of deflation,
Speaker 1: tremendous deflation, and tremendous inflation, So deflation like the thirties,
Speaker 1: inflation like the seventies, and obviously fat alternatives like precious
Speaker 1: metal perform in periods like the nineteen seventies where you
Speaker 1: have tremendous stagflation and negative real rates. So you have
Speaker 1: you're diversifying based on these market regimes. Now, we published
Speaker 1: this paper at the beginning of last year. We didn't
Speaker 1: have the opportunity to see in the future about what
Speaker 1: would happen throughout two thousand twenty. I released a new
Speaker 1: paper that talked about how this recommended portfolio performed through
Speaker 1: two thousand twenty. It was exceptional performance, because, as you know,
Speaker 1: two thousand twenty was like an entire business cycle condensed
Speaker 1: into twelve months. The whole business cycle from January to
Speaker 1: March that was like a nineteen thirties deflation. Then from
Speaker 1: April to about August, we had this incredible fiat devaluation
Speaker 1: with ten trillion dollars in global stimulus and this speculative
Speaker 1: asset growth. That's that's uh, you know, some almost kind
Speaker 1: of similar to type of scenario. As we entered the
Speaker 1: the wintertime, we went into a reflationary scenario that began
Speaker 1: to resemble kind of the onset of stagflation in the
Speaker 1: late sixties. I mean that's where you have struggles and
Speaker 1: interest rates. Interest rates began to rise at perform, but
Speaker 1: then you have this expectation of a reset deepening of
Speaker 1: the yield curve, and commodities began to perform. I mean,
Speaker 1: lumber reached all time highs copper was exploding. So if
Speaker 1: we look at how this portfolio that we call the
Speaker 1: Dragon portfolio formed in that deflationary period in the first
Speaker 1: part of the year, well, long volatility strategies were the
Speaker 1: huge winners. They actually we're able to fill the gap
Speaker 1: where equities drew down. So actually for this portfolio, that
Speaker 1: first quarter gained about where sixty portfolios and risk parity
Speaker 1: portfolios had huge underperformance because they were overreliant on bonds
Speaker 1: as their defensive protection. So long volatility strategies is so
Speaker 1: well and protected and helped you make money during that quarter.
Speaker 1: Then during the FIATA valuation and the kind of growth
Speaker 1: period after Central Bank stepped in, gold took its turn
Speaker 1: performing in the summer, along with definitely crypto and other
Speaker 1: assets like that, and then we had a huge outperformance
Speaker 1: and equities. Then by the fall, we began to see
Speaker 1: gold began to sell off, and we began to see
Speaker 1: equities continued their upward trajectory. Fixed income began to sell off,
Speaker 1: but trending commodities managed futures began to outperform, profiting from
Speaker 1: the trends in commodities markets and the trends in these
Speaker 1: other asset classes. So we had an entire business cycle
Speaker 1: condensed into twelve months, and at each point these assets,
Speaker 1: these market regime diversification benefits of the portfolio became really clear.
Speaker 1: And this concept of this dragon portfolio that we introduced
Speaker 1: actually would have returned close to last year where the
Speaker 1: portfolio and risk parity portfolios only returned about on average
Speaker 1: with over three times the max draw down. For people
Speaker 1: who read our paper, this should not be a surprise.
Speaker 1: It should not be a surprise because we saw this
Speaker 1: happen in previous market cycles. But you have to look
Speaker 1: at the periods outside the last forty years to understand that.
Speaker 1: So I get the contention that if you're building a
Speaker 1: portfolio that's going to outperform in these big regime changes,
Speaker 1: then in when you basically had a compressed business cycle,
Speaker 1: as you mentioned, it would do phenomenally well. But most
Speaker 1: people would agree that was an extremely unusual year, and
Speaker 1: I think most investment professionals are probably more used to
Speaker 1: trying to pinpoint the regime changes as they come, rather
Speaker 1: than build a portfolio that's going to outperform all types
Speaker 1: of regimes for a hundred years. Right Like, there outlook
Speaker 1: is always going to be you know, ten, twenty, maybe
Speaker 1: thirty or forty years, but it's going to be much
Speaker 1: much shorter than what you're talking about. So I guess
Speaker 1: my question is like, how useful is this for your
Speaker 1: average financial advisor or investor, and how do you encourage
Speaker 1: people to think on a longer term horizon, or think
Speaker 1: about diversification across regime changes rather than just trying to
Speaker 1: pinpoint when a particular change is taking place in markets. Yeah,
Speaker 1: I think one of the one of the phrases that
Speaker 1: we say is do not fear, do not predict, prepare.
Speaker 1: So if you are able to perfectly time and predict
Speaker 1: the regime changes, and I tell you I can't, you know,
Speaker 1: but if you're able to do that, you're Stanley Druckon Miller,
Speaker 1: You're George Soros, and you should be a billionaire, right. Um,
Speaker 1: The average retail investor, the average institutional investor, is not
Speaker 1: able to necessarily time those changes perfectly. And even if
Speaker 1: they're able to do so, if you're managing a fifty
Speaker 1: billion dollar portfolio, if you're an institution, or a ten
Speaker 1: billion dollar portfolio. I you're an institution, it's difficult to
Speaker 1: tilt the portfolio. You have to choose some portfolio allocation.
Speaker 1: And you know, my point is that the average pension
Speaker 1: fund in America is approximately equity linked investments and approximately
Speaker 1: in kind of fixed income and alternatives in cash. What
Speaker 1: many of these institutions have done is they've crowded in
Speaker 1: two assets like private equity kind of pretending that they're diversifiers.
Speaker 1: But if you look at some of the Cambridge studies,
Speaker 1: private equity has tremendous correlation to the business cycle. It's
Speaker 1: not a diversifying asset by market regime. No, they've jumped
Speaker 1: into vcs' is the same thing you jump into real estate.
Speaker 1: It's the same problem. These are all asset classes that
Speaker 1: are correlated to business cycles. Their long GDP asset classes
Speaker 1: that are correlated to one growth regime. Now, in the past,
Speaker 1: you could rely on fixed income to provide diversification, but
Speaker 1: when fixed incomes at the zero bound, it fails to
Speaker 1: provide great diversification. And anyone who studies the nineties would
Speaker 1: have seen that problem. When we recreated risk parity portfolios
Speaker 1: which rely heavily on fix income and lever the fixed income.
Speaker 1: There's tremendous underperformance in the nineties when rates were near
Speaker 1: the zero bound. So these institutions are assuming the last
Speaker 1: forty years will repeat, and they're in essence levering equity linked,
Speaker 1: not levering, but they're they're relying on this expectation of
Speaker 1: equity link performance and these kind of false diversifiers to
Speaker 1: reach their seven point to five percent return targets. I
Speaker 1: think this is a huge mistake because if you remove
Speaker 1: the last forty years, their performance is closer to to
Speaker 1: five percent annualized abysmal, you know, using the allocations that
Speaker 1: they have. So if they're not able to mate that
Speaker 1: seven point five percent return target, you know, recency bias
Speaker 1: becomes a problem that all of us are going to
Speaker 1: pay for. And the reason being there's about one point
Speaker 1: four trillion dollar US state and local pension deficit right now,
Speaker 1: and that's assuming that they are able to hit their
Speaker 1: return targets. If there's under performance, as one would expect
Speaker 1: given current valuations and the current correlation mix of their investments,
Speaker 1: you can expect that deficit to rise to anywhere between
Speaker 1: three trillion dollars all the way to up to nine
Speaker 1: trillion dollars. So in the last stimulus bill, there's a
Speaker 1: lot of controversy over eighty five billion dollars in bailouts
Speaker 1: for union pensions. And I'm not going to get another
Speaker 1: politics on that, but if you can imagine that there's
Speaker 1: a lot of tension over billion dollars, what's going to
Speaker 1: happen when when the government's going to need to step
Speaker 1: in and bail out PBOC and stay in the local
Speaker 1: pension systems to the tune of three trillion dollars. It's
Speaker 1: a big problem. Recency bias is a big, big issue.
Speaker 1: The problem with many of these institutions that they bought
Speaker 1: into the sharp ratio myth, the sharp ratio. They look
Speaker 1: at these investments, be at private equity and these other
Speaker 1: investments and they say, okay, what's the sharp ratio? We
Speaker 1: want to we want to put together all of these
Speaker 1: investments that have high sharp ratios. Well, the sharp ratio
Speaker 1: if you go back and you read the original paper
Speaker 1: that William Sharp wrote, you know, capital asset Prices, that
Speaker 1: was the paper they wrote when it is thirty years
Speaker 1: or old in nine four, it's clear that a sharp
Speaker 1: ratio is not intended for components of the portfolio. The
Speaker 1: sharp ratio should only be used for the aggregated portfolio.
Speaker 1: You can't use a sharp ratio too to make judgments
Speaker 1: on individual managers. Well, why why is that? Well, I'd
Speaker 1: like to use this analogy to sports. When you're looking
Speaker 1: at evaluating players to add to your favorite sports team.
Speaker 1: If you're a general manager, you want to add players
Speaker 1: that help you win. That's what you want what we
Speaker 1: all know, whether your favorite sports basketball or whether it's soccer,
Speaker 1: there are players on mediocre to bad teams with gaudy
Speaker 1: statistics and maybe they have really good scoring averages or
Speaker 1: goals averages, but they their statistics are padded and they
Speaker 1: don't help their team win. And the reason is maybe
Speaker 1: they don't play good defense, or maybe they dominate the ball,
Speaker 1: maybe they have high turnovers, and maybe they're not making
Speaker 1: hustle players that help their team win. So as a
Speaker 1: result of that, sports management has gotten really smart about
Speaker 1: selecting players and advanced statistics that measure or how a
Speaker 1: player helps the team win. These are things like winds
Speaker 1: over replacement value and plus minus ratios. Well, we have
Speaker 1: no metric for that in the investment industry. So what
Speaker 1: ends up happening is that these institutions by into this
Speaker 1: myth of sharp ratios and they keep layering on investments
Speaker 1: that have high sharp ratios. But what ends up happening
Speaker 1: is that when you can put together a bunch of
Speaker 1: investments that have high sharp ratio, but your portfolio will
Speaker 1: have lower risk adjusted returns and higher drawdowns, it's really amazing.
Speaker 1: And the reason is is that the sharp ratio doesn't
Speaker 1: take into account the skew or the extreme right or
Speaker 1: left hils of the investment. It doesn't take into the
Speaker 1: account the correlations of that investment versus the rest of
Speaker 1: your portfolio. So what happens here is that people have
Speaker 1: bought into this myth that layering on top these managers
Speaker 1: that have high sharp ratios will help them. It actually
Speaker 1: is hurting your portfolio. And likewise, just like in sports,
Speaker 1: there's some players with less impressive statistics. They may not
Speaker 1: look good on paper, they're sharp, their their their point
Speaker 1: averages might be lower, but they're doing things like playing vests.
Speaker 1: They're helping the team win and that shows up in
Speaker 1: the advanced metrics. Is this the moneyball theory for market investment?
Speaker 1: It is? It is, and we are working on a
Speaker 1: new paper that will develop this will come out in
Speaker 1: the next couple of weeks that actually develops some of
Speaker 1: these advanced metrics for institutions. But my point being is
Speaker 1: that investments like long volatility, which don't look that good
Speaker 1: on paper, you know, don't They don't have great sharp ratios,
Speaker 1: but when you add them to your portfolio, they push
Speaker 1: your portfolio out on the efficient frontier and result in
Speaker 1: a better risk adjusted return for your portfolio. Assets like gold,
Speaker 1: commodity trend advisors, and long volatility and defensive hedging, even
Speaker 1: though they don't look a great on a sharp ratio basis,
Speaker 1: you put them into the portfolio and they help your
Speaker 1: portfolio win. That's what you really care about, and that's
Speaker 1: what the average US pension institution and the average retail
Speaker 1: investor fails I think to fully comprehend. And this is
Speaker 1: so important because this sharp ratio problem is a social
Speaker 1: problem because if we don't fix this, we are all
Speaker 1: going to end up paying for it. So I really
Speaker 1: am passionate about this. I really believe this. I think
Speaker 1: the math proves this out, the history proves this out,
Speaker 1: and I think these are some of the most undervalued
Speaker 1: assets that one could put in the portfolio, even though
Speaker 1: they may not look at that good on paper. We
Speaker 1: need to stop evaluating the player and we need to
Speaker 1: start evaluating the team. Now, that's how that's the secret
Speaker 1: to building better portfolios. Right. So the idea is that
Speaker 1: the whole of the portfolio can be stronger than the
Speaker 1: individual components. Right, that's absolutely right. You know, paper, we
Speaker 1: talked about this idea where you can choose two assets.
Speaker 1: There are two assets that have high sharp ratios, but
Speaker 1: they're highly correlated with another. There's another asset that is
Speaker 1: a negative sharp ratio, but it's anti correlated. Actually, you'd
Speaker 1: rather put together the negative sharp ratio that's anti correlated
Speaker 1: with the with the one that there is a positive
Speaker 1: sharp ratio, then the two sharp ratio the too high
Speaker 1: sharp racial investment investments together. That results in a better portfolio.
Speaker 1: And it's just mathematically true. But for some reason we
Speaker 1: don't seem to see this. But sports, oddly, general managers
Speaker 1: like Daryl Morey and you know, the h the managers
Speaker 1: the Warriors understand this, this principle as applied to sports,
Speaker 1: even though we're lacking it in investment management. There's one
Speaker 1: other thing I want to ask you. You mentioned um
Speaker 1: social value just then, and this idea that if we're
Speaker 1: going to solve things like massive underfunding of pensions, then
Speaker 1: people should grasp this concept of building a sort of
Speaker 1: total portfolio versus just going after high returns in the
Speaker 1: short term. There's one other thing that that kind of
Speaker 1: caught my interest in the paper where you talk about
Speaker 1: the potential for wealth distribution in some regimes. So this
Speaker 1: idea that, um, you can get a backlash to a
Speaker 1: market crash, you can get sort of populist pressures on
Speaker 1: politicians that result in wealth redistribution, higher tax rates, things
Speaker 1: like that, And I think a lot of people would
Speaker 1: argue that maybe that's where we're heading. Now, how do
Speaker 1: you actually protect a portfolio from wealth re distribution and
Speaker 1: what does your dragon portfolio do it or perform in
Speaker 1: that scenario. Well, it's it's really interesting and complex question,
Speaker 1: and it really delves into a detailed analysis on the
Speaker 1: individual components. So people have to realize that how this
Speaker 1: ties in the last forty years because it's not just
Speaker 1: been rates that have been going lower, but it's been
Speaker 1: taxes that have been going lower. So a huge tax
Speaker 1: cuts starting in the nine So that combination of low taxes, globalization,
Speaker 1: lower and lower taxes, and lower interest rates has resulted
Speaker 1: in this huge build up of debt and tremendous outperformance
Speaker 1: in in in equity linked assets, private equity and all
Speaker 1: these other long GDP assetss we'll call them because that's
Speaker 1: what they are. Well, as we moved to an income
Speaker 1: rey just distribution type of world that presents a heavy,
Speaker 1: heavy burden on equities, on real estate, on private equity.
Speaker 1: It's a big issue for two reasons. First of all,
Speaker 1: you know, excessive regulation is going to cause problems in
Speaker 1: those asset classes. Obviously, if you're allocated seventy percent in
Speaker 1: those assets, that's that's a huge issue. Um. The second
Speaker 1: driver is that, look, we have the highest fiscal deficits
Speaker 1: since World War Two, and they're likely only only to
Speaker 1: be going up. We have unprecedented monetary policy, and we
Speaker 1: have the highest levels of corporate debt in American history
Speaker 1: as a percentage to GDP. These are all true facts.
Speaker 1: So the problem with keeping interest rates so low is
Speaker 1: that it exacerbates the wealth divide. In addition to all
Speaker 1: of these extreme factors on the excessive debt, we also
Speaker 1: have the highest income disparity in American history that is
Speaker 1: equaled only by the Great Depression prior to the Great Depression.
Speaker 1: This puts tremendous political pressure. You can't just keep rates
Speaker 1: low and do the Japan experiment because you're gonna have
Speaker 1: a social social explosion. And you know, I talked about
Speaker 1: this in the New York Times. I gave an article
Speaker 1: back in two thousand seventeen that was prior to my
Speaker 1: Orables paper where I talked about the blow up involved,
Speaker 1: and I said, well, you know, if the if the
Speaker 1: FED wants to suppress volatility indefinitely, well that's something that
Speaker 1: you know, they can do that, But volatility can never
Speaker 1: be destroyed. It can only be transmuted in form and time.
Speaker 1: So if you're going to suppress asset price volatility using
Speaker 1: monetary policy, that volatility is going to come out in
Speaker 1: a different way, and that way is through social instability.
Speaker 1: And I said, hey, my, you know my hedge fund,
Speaker 1: which seeks to protect against market crashes. Now that's something
Speaker 1: I feel pretty confident about being able to protect against.
Speaker 1: But what you can never protect against is a social revolution,
Speaker 1: and I think we're starting to see the seeds of that.
Speaker 1: Of course, one of the ways that governments can stem
Speaker 1: that off is by fiscal stimulus giving on money. But
Speaker 1: that's stagflationary, that's tremendously stagflationary, and so I think that's
Speaker 1: the that's the route that maybe is the path at
Speaker 1: least resistance, where you know you have you can destroy
Speaker 1: debt in two ways. You can default on the debt
Speaker 1: or you can print money, and you can do tremendous
Speaker 1: stimulus and you can inflate your way out of the debt,
Speaker 1: and we maybe choosing the inflation route. Well, that's going
Speaker 1: to rereak havoc on the institutional portfolio because people don't
Speaker 1: realize this. Equities, what is in the seventies were in
Speaker 1: a great depression on a real adjusted basis. So the
Speaker 1: draw down on a real basis after inflation was was
Speaker 1: as bad as the draw down in the es. But
Speaker 1: the reason that people didn't feel it that that that
Speaker 1: was that bad was because we were inflating away the problems.
Speaker 1: Of course that led to you know, rent control and
Speaker 1: all these other issues. So if we go the inflation
Speaker 1: stagflation route, you're going to see equities destroyed on a
Speaker 1: real adjusted basis, and you're going to see bonds obviously
Speaker 1: destroyed because rates go up. Well, guess what performs that
Speaker 1: environment if we go back to our Dragon portfolio. Well,
Speaker 1: at any point in the Dragon portfolio has two out
Speaker 1: of the five thematic regime classes me so what performs
Speaker 1: really well in a stagflationary environment, Well, precious metals and gold.
Speaker 1: You had a price increase in gold, we'd presume that
Speaker 1: crypto would be part of that um but there's a
Speaker 1: lot of questions on crypto. The other thing that performs
Speaker 1: extra extremely well is commodity trend and trending trending commodities,
Speaker 1: So the ct A Sleep portfolio performs really well. So
Speaker 1: those are strategies that take into account momentum. And so
Speaker 1: we're seeing that this year, you know where lumber prices
Speaker 1: are exploding d all time highest coppers up, all these
Speaker 1: commodities are trending tremendously higher. So in this sense, if
Speaker 1: you have of your portfolio allocated two assets that can
Speaker 1: play off of the stagflation, you're gonna be okay, You're
Speaker 1: gonna do well. That will make up for your suffering
Speaker 1: stock and bond exposure. In addition, long volatility can make
Speaker 1: money in right tail events and stagflation as well. If
Speaker 1: we go into kind of a Japan environment, well, you
Speaker 1: know that that's a scenario where long volatility tends to outperform,
Speaker 1: and you know you have stability and fixed income and
Speaker 1: it kind of has stable returns in in inequities. So
Speaker 1: I think you can't necessarily. It goes back to that idea,
Speaker 1: don't predict, prepare, and and thrive from change. And and
Speaker 1: that's when we look at risk in terms of thematic baskets.
Speaker 1: Regardless of what regime you're in, at least two to
Speaker 1: three of the thematic baskets or market regime baskets are
Speaker 1: outperforming and that saves your portfolio, and that that way
Speaker 1: you don't necessarily need to predict the winds of political change.
Speaker 1: All you need to do is to have a balanced
Speaker 1: allocation so you're prepared throughout any regime. I really stressed
Speaker 1: that this is something that the investment allocation problem, the
Speaker 1: portfolio allocation problem, is a social problem. We have a
Speaker 1: window of opportunity. This is both on a pension systems
Speaker 1: institutional investors and for individual investors. There's a window of
Speaker 1: opportunity to create portfolios that are rebut dust and are
Speaker 1: able to thrive through these different regimes. You know, my
Speaker 1: paper of the allegory, the Hawk Conserpent released last year
Speaker 1: in January, and the follow up to that paper that
Speaker 1: chronicled how those ideas performed in two thou twenty that
Speaker 1: was just released, really make the case, and I think
Speaker 1: a very important case that this is. This is this
Speaker 1: is vital if you want to profit and be able
Speaker 1: to survive periods of secular change. And this is not
Speaker 1: just an intellectual argument about portfolio construction. It is a
Speaker 1: social problem if we don't address this, because the pension
Speaker 1: underfunding is going to get massive and we are going
Speaker 1: to pay for that. Now, we could pay for it
Speaker 1: through government bailouts, or we could pay for it through
Speaker 1: loss of purchasing power from inflation. But the asset allocation
Speaker 1: problem is a social problem, and I think institutions and
Speaker 1: retirees really need to strongly look at diversifiers that profit
Speaker 1: from left and right tail events and profit from trend
Speaker 1: and those are asset classes underlooked asset classes like long volatility,
Speaker 1: commodity trend and precious metals and fiat alternatives, and those
Speaker 1: are just as important as equities in the portfolio. Chris,
Speaker 1: what's the name of the new paper? The new paper
Speaker 1: which is available on our website. It's called Rise of
Speaker 1: the Dragon. I I love these UH metaphors and visuals, UM,
Speaker 1: but I really encourage people to do deep dives into
Speaker 1: the papers because I think there's a lot of quantitative analytics. UM.
Speaker 1: Everyone read the first paper. People didn't. Actually, not a
Speaker 1: lot of people read the appendix, which was twice as
Speaker 1: long as the paper and contained much more detailed quantitative notes. Um.
Speaker 1: So you know, both of those papers are available on
Speaker 1: our website www. Artemus cm dot com, and occasionally tweet
Speaker 1: about these things too. Yeah, I'll mention your handle at
Speaker 1: the end of this. But in the meantime, everyone has
Speaker 1: some you know, light weekend reading in the form of
Speaker 1: a twenty page appendix from your paper. So that's sorry,
Speaker 1: a detailed twenty page abendonment talks about a ball surface
Speaker 1: and and rispirity replication to the thirties. So all right, Chris,
Speaker 1: it's lovely having you on as always. That was Chris Cole,
Speaker 1: the founder of Artemis Capital. Thank you so much. Thank you, Tracy.
Speaker 1: Great to be back. So I'm going to avoid recording
Speaker 1: a monologue here because I think it would be weird
Speaker 1: for me to talk to myself about what I found
Speaker 1: interesting in that conversation. But I do encourage you to
Speaker 1: take a look at Chris's paper. It's not very often
Speaker 1: that you get to see someone modeling volatility surfaces from
Speaker 1: the Great Depression, so whenever you get that chance, you
Speaker 1: should seize it. All right, this has been another episode
Speaker 1: of the All Thoughts podcast. I'm Tracy Alloway. You can
Speaker 1: follow me on Twitter at Tracy Alloway. You can also
Speaker 1: follow our guest Chris Cole. He is at vall under
Speaker 1: Dash Christopher, and you should also follow all of the
Speaker 1: Bloomberg Podcast. You can find them on Twitter at podcast.
Speaker 1: You should definitely follow our producer Laura Carlson. She is
Speaker 1: on Twitter at Laura M Carlson. And you should follow
Speaker 1: Bloomberg's head of podcast, francesco Leavie. She is at Francesca Today.
Speaker 1: Thanks for listening, t