Vineer Bhansali: Physics, Tail Risk Hedging, and 900% Coronavirus Returns - Manifold Episode #43

Steve and Corey talk with theoretical physicist turned hedge fund investor Vineer Bhansali. Bhansali describes his transition from physics to finance, his firm LongTail Alpha, and his recent outsize returns from the coronavirus financial crisis. Also discussed: derivatives pricing, random walks, helicopter money, and Modern Monetary Theory.

Transcript

LongTail Alpha

LongTail Alpha’s OneTail Hedgehog Fund II had 929% Return (Bloomberg)

A New Anomaly Matching Condition? (1992)
https://arxiv.org/abs/hep-ph/9211299

Added: Background on derivatives history here. AFAIK high energy physicist M.F.M. Osborne was the first to suggest the log-normal random walk model for securities prices, in the 1950s. Bachelier suggested an additive model which does not even make logical sense. See my articles in Physics World: 1 , 2


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Future vol

Hmm... pricing in a 30-50% chance of huge vol due to euro credit crisis? If you're sure it's going to happen, some 6-12 month vol swaps might be a good trade. Any experts want to comment? (Are there better instruments for this?) How much further can Merkozy kick the can down the road?

On the volatility of volatility

A pro sez to me: "Vol is totally mispriced right now. Lots of funding requirements in the new year."

Those cold and timid souls

It may be that stupid people take too much risk in their lives -- perhaps without knowing it. But my guess is that intelligent people tend to be too risk averse. Were it not the case, we'd have more startups, innovation, scientific breakthroughs, and even great art.

Theodore Roosevelt, speech at the Sorbonne 1910:

It is not the critic who counts; not the man who points out how the strong man stumbles, or where the doer of deeds could have done them better. The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood, who strives valiantly; who errs and comes short again and again; because there is not effort without error and shortcomings; but who does actually strive to do the deed; who knows the great enthusiasm, the great devotion, who spends himself in a worthy cause, who at the best knows in the end the triumph of high achievement and who at the worst, if he fails, at least he fails while daring greatly. So that his place shall never be with those cold and timid souls who know neither victory nor defeat.

I have great respect for Teddy Roosevelt's insights. He understood MMA a hundred years ago; historians of the sport will note that early UFCs didn't even have weight classes! From an earlier post, Mama said knock you out:

From a letter to son Kermit, dated 02/24/1905:

Yesterday afternoon we had Professor Yamashita up here to wrestle with Grant. It was very interesting, but of course jiu jitsu and our wrestling are so far apart that it is difficult to make any comparison between them. Wrestling is simply a sport with rules almost as conventional as those of tennis, while jiu jitsu is really meant for practice in killing or disabling our adversary. In consequence, Grant did not know what to do except to put Yamashita on his back, and Yamashita was perfectly content to be on his back. Inside of a minute Yamashita had choked Grant, and inside of two minutes more he got an elbow hold on him that would have enabled him to break his arm; so that there is no question but that he could have put Grant out. So far this made it evident that the jiu jitsu man could handle the ordinary wrestler. But Grant, in the actual wrestling and throwing was about as good as the Japanese, and he was so much stronger that he evidently hurt and wore out the Japanese. With a little practice in the art I am sure that one of our big wrestlers or boxers, simply because of his greatly superior strength, would be able to kill any of those Japanese, who though very good men for their inches and pounds are altogether too small to hold their own against big, powerful, quick men who are well trained.

"Theodore Roosevelt's Letters to His Children" edited by Joseph Bishop.

Historical vol

Worried now? Graph from maoxian. Check these out.




Too bad I don't have my vol trade on any more... I bought some vol back in 2004 or so (long-dated VIX options), which looks to have been near the bottom :-)

The quants of August

Why the rough markets in August? Why the big losses for certain quant funds? This paper claims the following:

1) many funds are pursuing the same strategies, using significant leverage

2) problems in the credit markets forced some multi-strategy funds to sell liquid equity positions in order to meet margin calls

3) positions commonly held by quant funds deteriorated in a correlated manner

Conclusion: systemic risk galore!

More discussion in the Economist.

What Happened to the Quants in August 2007?

AMIR KHANDANI
ANDREW W. LO
Massachusetts Institute of Technology

September 20, 2007


Abstract:

During the week of August 6, 2007, a number of high-profile and highly successful quantitative long/short equity hedge funds experienced unprecedented losses. Based on empirical results from TASS hedge-fund data as well as the simulated performance of a specific long/short equity strategy, we hypothesize that the losses were initiated by the rapid unwinding of one or more sizable quantitative equity market-neutral portfolios. Given the speed and price impact with which this occurred, it was likely the result of a sudden liquidation by a multi-strategy fund or proprietary-trading desk, possibly due to margin calls or a risk reduction. These initial losses then put pressure on a broader set of long/short and long-only equity portfolios, causing further losses on August 9th by triggering stop-loss and de-leveraging policies. A significant rebound of these strategies occurred on August 10th, which is also consistent with the sudden liquidation hypothesis. This hypothesis suggests that the quantitative nature of the losing strategies was incidental, and the main driver of the losses in August 2007 was the firesale liquidation of similar portfolios that happened to be quantitatively constructed. The fact that the source of dislocation in long/short equity portfolios seems to lie elsewhere - apparently in a completely unrelated set of markets and instruments - suggests that systemic risk in the hedge-fund industry may have increased in recent years.

Derman: How I became a quant

Emanuel Derman reviews the new book HOW I BECAME A QUANT by Richard R. Lindsey and Barry Schachter.

Nice quote on Derman's blog here:

It always seemed to me, and recent occur[r]ences seem to confirm it, that most algorithmic trading strategies are long volatility but short volatility of volatility.

A previous post from this blog: On the volatility of volatility

WSJ: In 1985, when I left academia and began putting my physics training to work on Wall Street, I talked eagerly about options theory to anyone who would listen. One lunchtime, I turned to a colleague in the elevator and began to babble about "convexity," a mathematical property of options crucial to the Black-Scholes theory used in derivatives pricing. My friend clearly understood convexity, but he shuffled his feet uncomfortably and quickly changed the subject. "Hey, futures dropped more than a handle today!" he said, imitating a genuine bond trader. It didn't take me long to recognize the source of his discomfort: I had just outed him as a fellow quant. Except back then we practitioners of quantitative finance didn't refer to ourselves as quants. That's what "real businesspeople" -- traders, investment bankers, salespeople -- called us, somewhat pejoratively.

Now the term is proudly embraced, as demonstrated by "How I Became a Quant," which collects 25 mini-memoirs of academics who successfully made the jump to Wall Street. Quantitative finance might have lost a little of its luster in recent weeks with the sub-prime mortgage meltdown and its subsequent deleterious consequences for quantitative trading strategies, but quants know -- as many of them in this book emphasize -- that however science- and math-based investment calculations might be, there is still an art to their use and plenty of room for error.

But definitions first. What is a quant, or, rather, quantitative finance? It is an interdisciplinary mix that combines math, statistics, physics-inspired models and computer science, all aimed at the valuation and management of portfolios of financial securities. In practice, for example, a quant might be presented with a convertible bond being issued by a corporation and, by extending the Black-Scholes model to convertible securities, calculate its probable value. Or he might develop a quantitative algorithm to buy theoretically cheap stocks and short theoretically rich ones.

By my reckoning, several of the 25 memoirists in "How I Became a Quant" are not true quants, and they are honest (or proud) enough to admit it. But many others are renowned in the quant community. To name just a few: Ron Kahn, co-author of the classic "Active Portfolio Management"; Peter Carr, an options expert at Bloomberg; Cliff Asness, one of the founders of AQR Capital; and Peter Muller, who ran statistical arbitrage at Morgan Stanley.

Most of the book's contributors belong to the first wave of a financial revolution that began in the 1970s, when interest rates soared, listed equity options grew popular and options traders began to rely on the mathematically sophisticated Black-Scholes model. Investment banks needed mathematical talent, and, as the academic job market dried up, physicists needed jobs. Many early quants were therefore physicists, amateurs who had happily entered a field that didn't yet have a name.

Today we are in the middle of a second wave. As markets became increasingly electronic-based, asset and hedge-fund managers began to embrace algorithmic trading strategies -- and started competing to hire quants, hoping to emulate the continuing successes of such firms founded in the 1980s as Renaissance Technologies and D.E. Shaw & Co. The establishment of the International Association of Financial Engineers, co-founded in 1992 by another contributor to this book, Jack Marshall, has further legitimized the field. Nowadays you can pay $30,000 a year or more to get a master's degree in the subject. Financial engineering has become a profession, and amateurs are sadly passé.

Most of the early quants -- in addition to physicists, they included computer scientists, mathematicians and economists -- came to the field by force of circumstance. Even if they had been fortunate enough to find a secure academic position, they often became weary of the isolating academic grind and found that they liked working at investment banks and financial institutions. As former SAC Capital Management quant Neil Chriss notes, Wall Street is no more competitive than academia. Life in finance is often more collegial than college life itself -- and more stimulating. It is impressive how many of the contributors here cite with awe their encounters with the late economist Fischer Black (1938-95), himself a Ph.D. in applied mathematics rather than economics, who always insisted that research on Wall Street was better than research in universities.

The memoirs in this book are not quite representative. That there are only two women contributors is proportionately accurate; most quants were male. But most quants were also foreign-born. When I ran an equity quant group in the 1990s, the great majority -- all with doctorates -- were from Europe, India or China. Only two of the memoirists grew up abroad in non-English-speaking countries. Quants in the second wave are still largely foreign-born, but more are women and fewer hold doctorates.

Several contributors to "How I Became a Quant" stress an essential point: Physics and finance are only superficially similar. While theoretical physics captures the essence of the material world to an accuracy of 10 significant figures, theoretical finance is at best an untrustworthy, limited representation of the mysterious way in which financial value is determined. Yet Thomas Wilson, the chief insurance risk officer of the ING Group, wisely remarks: "A model is always wrong, but not useless." Despite the inadequacies of quantitative finance, we have nothing better. And, on the practical side, Andrew Sterge, the chief executive of AJ Sterge Investment Strategies, writes: "The greatest research in the world does no good if it cannot be implemented."

Quants do get more respect these days, because their imperfect models can generate profits when used with a knowledge of their limitations. But quants can also produce awe-inspiring disasters when they begin to idolize their man-made models. Nevertheless, most quants, unless they have their own operations, are still second-class citizens on Wall Street rather than its superstars, and many still aspire to leave behind bookish mathematics and join the ranks of the "real businesspeople" who used to look down on them.

Vol and tail risk

Some nice discussion here by financier turned internet entrepreneur Roger Ehrenberg. His blog is on my Google Reader list. See also here.

Volatility Management in a Complacent World

Volatility has a corrosive effect on returns. Two cash flow streams that generate similar average returns, where one is more volatile than the other, can result in sharply divergent IRRs with the less volatile stream yielding the superior result. Therefore, it is clear that volatility reduction has a real and calculable value, but requires a probabilistic view of the world that is often difficult to quantify and harder to pay for. Further, sometimes the pressure for short-term returns can skew rational long-term thinking, causing an increase in the willingness to accept volatility that, in turn, further depresses the value of accepting such risks. And with this the cycle of complacency begins, is reinforced, and feeds on itself until the inevitable happens: event shock. And people will throw up their hands and and say "Look at this tail risk; this is once-in-a-(decade/century/millennium) event." And those with a keen appreciation for such things will say - I told you so. "Fat tails" and "three sigma events" are now and have always been a relatively ordinary phenomenon. Tail risk is risk that can and should be priced and, depending upon your objectives and stakeholders, actively mitigated. But this requires discipline and cost, two things commonly lacking in those compensated for short-term objectives. And herein lies the issue.

The Economist has an interesting piece titled Sting in the Tail, positing whether low volatility is making the world too complacent about risk. There are some derivatives details in the article that I will address in a separate post that are either unclear or incorrect and, in my opinion, confuse the issue and muddy the picture unnecessarily. However, the questions raised by the article are spot on and important for investors and policy-makers to consider...

1. Have developments in the global financial markets - the rise of derivatives and risk dispersion, stronger, more competent central banks, and a more diversified base of economic power spread across countries, companies and currencies - conspired to reduce the "structural" level of market volatility?

I think the answer is yes. In general, diversification reduces the variability of outcomes, and with the increased diversification of both risks and economic power it must logically follow that some degree of variability has to have been stripped from the global financial markets. This doesn't mean that markets still can't get pushed out of whack or that exogenous, non-economic shocks (i.e., war, terrorism, etc.) don't have profound economic impacts that give rise to volatility. It only means that if one were to take a longitudinal view of global economic performance, that one would expect a less variable set of returns than previously generated in a world with greater concentration of risks and economic power. My only qualifier to this is: in a more complex, diversified world, does this possibly give rise to a third dimension of exposures related to the non-linear increase in the complexity of relationships managing the world's global economic resources? It was easy to navigate when you had a few economic superpowers and a few powerful financial markets. But what about now? The picture is painfully more complicated. And this might, in and of itself, effect the volatility landscape.

2. Are the perceptions of risk and, therefore, volatility, cyclical?

The answer is unquestionably yes. People and markets have short memories, and that is a fact. Which means that if liquidity is plentiful, spreads are tight and investors are looking everywhere for returns, spreads will continue to tighten as previously risky assets are no longer viewed as risky (i.e., high-yield debt, emerging markets debt and equities, etc.). This also means that those buying insurance are few and those selling insurance are plentiful, further depressing volatility and only amplifying the effects of a complacent market psychology. Then seemingly out of nowhere - bang! Emerging markets debt spreads move from 200 bps to 1000 bps, equity markets drop 10-20%, and risk premia magically expand to meet the heightened anxiety and uncertainty. And this will persist for a while. Until people forget about the shock and it's once again business as usual. This is how it always has been and this is how it always will be. Will the current liquidity-fueled securities-buying boozer persist indefinitely? Of course not. It is just a matter of time.

3. Are the costs of insuring against tail risk relatively expensive?

Yes. And they always will be. Selling out-of-the-money put options is a risky business, and the implied volatility that is required to buy these instruments is generally very high. In fact, broker/dealers are not the ones best positioned to sell such instruments. While the implied volatility charged the buyer is relatively high the cost of the option is absolutely cheap, due to its out-of-the-moneyness and the low probability of its being exercised. Therefore, the broker/dealer selling the option is not making a whole lot of money even when charging high implied volatility, and the dynamic hedging (usually "delta hedging" - the probability-weighted amount of the hedge underlying that needs to be held based upon the spot price of the underlying and the remaining time to maturity) that needs to take place is subject to "gap risk." This basically means that when the dealer most needs to sell to adjust its hedge it will be forced to sell at progressively less attractive prices in a market meltdown. This is how dealers can lose hundreds of millions of dollars very, very quickly. However, insurance companies and others with durable, ultra-long dated asset portfolios can sell these options as a vehicle for enhancing returns (the flip side of covered call writing) without the need for dynamic hedging. Bottom line, implied volatility will always be high for these types of instruments, and necessarily so.

4. Can one generate seemingly superior short-term returns by avoiding the costs of insuring long-term risk?

Absolutely. Whether the investor is buying risky assets at progressively tighter spreads or selling optionality as a vehicle for collecting premium it hopes never to have to pay back (and then some), these activities generate returns that are relatively attractive when compared to common benchmarks. However, Mr. Market ensures that investors don't get something for nothing, so when that "unexpected" shock occurs - spreads blow out, markets drop and margin calls come knocking - the benefits associated with making short-term numbers look good are generally far outweighed by the costs associated with the unwinding of these risky asset/short-option positions. Messrs. Meriwether and Niederhoffer know all about this. So let's just say that investors should look pretty carefully at fund documents before investing, because often these documents give managers tremendous amounts of latitude, and one will need to dig pretty deep to properly analyze the quality of a fund's earnings. Is it due to good securities selection or an increase in portfolio risk? This is the question the needs to be answered.

5. Has complacency driven this historical tightening of risk premia across markets, to the point where it is poised to explode in the face of said tail events?

Oh, yes. I think liquidity is a great thing, except when it causes investors to make irrational decisions. Chasing returns. Getting away from a fund's mission. Assuming risks that are properly absorbed by those better able (and more appropriately positioned) to take them. And when the time comes, no amount of liqudity is going to buttress what looks like an inexorably declining market. Changes in market psychology can be abrupt and harsh. People and governments will move to the sidelines until the detritus is cleared, and this will take exactly how long? Who knows.

So where we are today is at a time when the costs of insurance are both relatively and absolutely low yet the urge is for investors to sell it, not buy it. Because short-term performance considerations (which directly drive most fund managers' compensation, as well as the ability to gather additional assets to manage) can often drive sub-optimal portfolio decisions. And this is certainly not good for fund investors. And it is at times like these when the smart, savvy, long-term oriented managers with an appreciation for history take a contrarian position. And I might wager that this is precisely what is happening. We'll see the wheat separated from the chaff in short order. Just wait and see.