Jonathan Haidt is on a roll:

Consider this gem:

The fundamental rule of political analysis from the point of psychology is, follow the sacredness, and around it is a ring of motivated ignorance.

I would say that's true for scientific analysis too.

Theory vs. Data

One interesting interpretation of Freud is that he modeled his approach based on his readings of Sherlock Holmes (see Sebastiano Timpanora). In those books, Holmes would trace the faintest clues and infallibly solve a puzzle that would daunt your average person. Freud then though if he could supply a dynamic explanation for virturally every reported dream or error, the soundness of his method would be demonstrated, so Freud's case studies read a lot like a fun mystery novel. It turned out detective stories are a bad template for creating a new science because it is all post hoc rationalization, and unfalsifiable, basically the signature field Karl Popper used to explain what is not a science.

Our narrative brain theorizes and is often wrong, but of course it does the best it can. Interestingly, the left side, the language side, is the theorizer. Thus, if you show the left brain a sequence of lights that flash above the line 80% of the time, rats and pigeons and 4-year olds do better than adults because our left, theorizing side, tries to guess which one will be above or below the line, matching only the relative frequency, but wasting many choices below the line. We basically become dominated by our wacky, theorizing left side around age 5, which as any parent will tell you, is well before reasoning has been perfected.

In contrast, if you merely show the pattern to the right side of the brain, as Michael Gazzaniga has done with his studies of split-brain patients, the right side is a simple bayesian, and goes with the frequentists approach (see his book Who's in Charge?). So, half our brain is a simple bayesian looking at data without much theory, the other half a theorist trying to integrate, analyze, and generalize.

Freud was only doing what is natural, coming up with theories, but he forgot that old cliche, moderation in all things. Look at the data too. If they contradict your theory, or cannot be really contradicted by data, alter your theory. The problem seemed to be that Freud was always the smartest kid in the room growing up, so he probably thought he could simply make up anything at all, because he could argue for or against anything with complete confidence he would win as he always did. Unfortunately he learned fake thinking, the kind salesmen, lawyers and politicians are especially good at, which is reasoning and arguing without a prioritization of the truth. For him the truth was merely a tactical constraint, a concession in small facts, never for the big one.

Hedge Fund Profits Near Zero

The graph above shows the portion of hedge fund profits that go to the hedge funds, the fund-of-funds, and the investors, using total dollars from 1998-2010. This is from Simon Lack's presentation, which is derived from his book Hedge Fund Mirage. Notice 97% go to insiders, 3% to investors.



Like most strategies or asset classes, the money made on a percent basis is large because it basically grows until it can't work, at which point it loses more money than it made and then some more (see above graph, 2008 killed everything). It could be thought of as an endogenous reaction, because how else will you know at what point it stops working? Perhaps this is the essence of all financial cycles.

One good point by Lack was that fund managers inevitably argue they do not fit into clean categories; that they, unlike everyone else, is neither fish nor fowl. I suppose we all think we are unique, and don't like to be benchmarked, but on the other hand, everyone is riskier without a benchmark.

The Ineffable Intuition of Chicken Sexers

In the book Incognito by David Eagelman, the author discusses the strange nature of chicken sexing. This is the valuable process of separating female and male chicks as soon as possible, because each sex has different diets and endgames (most males are just destroyed). The mystery is that when you look at the vent in the chick’s rear, some people just know which are female. It is impossible to articulate, so the Japanese figured out how to teach this inarticulable knowledge. The student would pick up a chick, examine its rear, and toss it into a bin. The master would then say ‘yes’ or ‘no’ based on his generally correct observation. After a few weeks, the student’s brain was trained to masterful levels.

This is rather fascinating. I wonder how many things are taught this way, things related to intuitions, usually focused on relationships. I don’t think this would work in stochastic cases like stock picking because even a good stock might have succeeded in spite of itself due to some random luck, making it no more useful to generalize upon than a winning lottery number. A good mentor could really generate a first-order advantage, and perhaps that is relevant to mystery of what generates most of the intergenerational income correlation, because IQ seems only to explain 10 to 25% of it.

We all know a lot more than we can articulate, stuff that can't be translated by our conscious self, which is why we still can’t generate a robust program to distinguish between a dog and a cat, even though a 4-year old has no problem. Nonetheless, we can train our unconscious thoughts via methods like the chicken sexer, primarily by emulating others who are good.

As Oscar Wilde said, the things worth learning can't be taught, by which I think he meant taught via some schoolbook. Watching a father deal tactfully with anger, frustration, and persuasion is surely as valuable as learning the times tables. Many people have this emotional intelligence, and it is very beneficial, probably something that isn't taught via reasoning, rather simply showing.

Agent Based Models

I was recently at the FactSet Phoenix conference, and Rick Bookstaber gave one of the keynote addresses. He works for the SEC, and like all senior regulators works with the Fed, the IMF, and the whole kitchen sink of regulatory bodies out there. He seemed like a veteran speaker, and made an interesting analogy between investment markets and warfare, in that the only thing that maintains is the competition, not the means.

Then he introduced me to the cutting edge of bank regulation: agent based models. Bookstaber said these are better than value-at-risk (VAR) involves agent based models, because 'anything that works is obsolete.' Clearly this is an exageration (I hope).

So what are these models? I found a good example here, by Stefan Turner, for the OECD ("Better Policies for Better Lives" is their motto). He starts out withh 24 pages of words, telling us that this model analyzes millions of simulations of millions of interactions. He notes (p. 7), that 'the models demonstrate that such regulator measures can, under certain circumstances, lead to advese effects.' Let's hope that's a feasible scenario.

Anyway, there are a bunch of obvious economic assumptions like suppy equals demand, and that demand decreases in price, mixed with a variety of exogenous assumptions such as that noise trade demand is 'weakly mean-reverting', and informed demand is a stepwise linear function of the asset price and some constant. This is all like Stephen Wolfram's New Kind of Science, the idea that you take some simple assumptions, create some cool time series that look like or 'are homologous to' real time series.

This is so abstract, the main point is merely to generate time series that look vaguely like some asset time series, which given the number of parameters (20+) and rules is rather simple. What this implies about the current state of Bank of America is anyone's guess. A complex financial company will have hundreds of very different assets, each with their own underwriting criteria, loss curves, recovery rates, and then several different types of liabilities. VAR isn't relevant here, but neither are agent based models.

It's fine for academics to do deep research on things like dynamic programming and input-output matrices. These generated a lot of excitement, Nobel prizes, but were ultimately useless for predicting anything except tenure decisions. VAR is a very useful tool, mainly in making sure crazy rogue traders aren't operating, but mark-to-market books are not the essence of banking. When I was head of capital allocations at KeyCorp, our VAR risk was about 1% of our total economic risk capital, almost nothing. Surely it's higher for the money center banks, but it's still small compared to their balance sheets that aren't being churned.

The idea that 'agent based models' is the new focus of bank regulation strikes me as a monumental waste of time, up there with the idea that neural nets can discover interesting (as opposed to merely true) theorems. On the other hand, they are going to do something, and irrelevant is merely a waste of their time and money.

The main problem everyone sees is too big to fail, but regulators see it as something they simply have to maintain given the contagion risk. Why not keep it simple, and just say, you pay an asset tax for every dollar over $100B? Then you don't even have to force anything, just collect the extra revenue on the big, fat companies that probably would be worth more to their investors (as opposed to CEOs) if they were smaller too. Remember, Bob Rubin didn't even know Citi owned a $300B+ in mortgages, and he was getting paid $115MM to mind the store, so it's not obvious to anyone what's going on in these $1 Trillion behemoths, but we all know the Treasury will be there if they collapse. If all the banks were smaller, we wouldn't be so afraid of contagion risk (who cares if KeyCorp fails?). Banks would be better incented to be prudent investors, and do things like assume collateral can fall in value. With banks smaller, perhaps they wouldn't find lobbying government more important than coming up with better and more efficient business models.

Perhaps that is a bad idea, but it is simple, and is better than any idea that could conceivably come out of an agent based model.

Complex regulatory schemes generate the appearance of rigor and efficient regulation. Further, this way we can focus on what's really important, like which Boston-based financial conglomerate will win the Barney Frank sweepstakes this November and snag the Dodd-Frank author to their executive committee, winning them a 10 year regulatory pass and signaling to everyone on Capital Hill how the game is played.

Evolution Not Very Settled

In The Selfish Gene, Richard Dawkins argued that it is not species that compete, not even individuals, but genes. You'd never learn it from Dawkins, but it appears selection happens at all sorts levels, not just at the gene level. In Haidt's Righteous Mind, he (a psychologist) gives the following example of group selection.

A geneticist worked with cages containing twelve hens each, and he picked the cages that produced the most eggs. Then he bred all of the hens in those cages to produce the next generation. Within just three generations, aggression levels plummeted, and within 6 generations death rates fell from 67% to 8%, and eggs produced jumped from 91 to 237. If you just picked the hens that laid the most eggs, they tended to be the meanest, and so aggressive behavior (and dead hens) went up. That is group selection working better than individual selection, and gene selection is even less relevant; there is selection of genes, but only at the level of the group.

Then there's Steven Jay Gould's famous statement that 'there's been no biological change in humans in 40k to 50k years.' Haidt notes no one believes that anymore, especially after this Russian guy, Dmitri Belyaev, turned wild foxes into harmless dogs in only 30 generations, or about 600 years in human terms. That means the invention of agriculture 8k years ago could have really changed our brains and behavior at least as significantly as how foxes differ from dogs. It follows pretty basically that human races are probably truly different at some levels (mainly similar, to be sure).

These aren't minor changes. You have to pick this stuff up on the periphery, in blogs like gnxp, or books by Cochrane and Harpending, not the mainstream evolution books, which tend to focus on refuting intelligent design and creationists.

Haidt on Moral Values

I really enjoyed Jonathan Haidt's latest book, the Righteous Mind. It is filled with many facts and ideas I wasn't aware of, and it makes me feel like I know more about myself and the world. Reading such books is one of the finer pleasures in life.

There are many things I found interesting and profound. For example, sport is to war as porn is to sex, a harmless release for a primitive urge. He notes that judgment and justification are two separate processes, and our narrative part of our brain, the voice we all hear in our head when we talk to ourselves, is just the justifier. Don't trust it! It is a partisan hack for your intuitions. IQ is a predictor of how well people argued as measured by the number of arguments they use to buttress a hypothesis, but not better than others at finding reasons for the 'other side.' So, given one of his big ideas here is that we intuit our beliefs first, then rationalize them, it seems our analytic side merely helps us better convince ourselves and others we are right, and not be right in itself.

An important point he doesn't mention is that most of our beliefs do not pertain to matters of pure logic, but more complex assertions that are based on a wide set of data and assumptions. Thus, if everything were a math problem, we could trust our reasoning, but unfortunately life isn't a math problem, so we can't trust reasoning to get us to the right answer. That seems pretty convincing with my observation that after a certain level, more smarts does not make you wiser, just able to generate a broader, more articulate, or more rigorous defense of your beliefs.

He makes a good case for trying not to form an opinion on something too quickly, and see the other side's argument using their best faith, best arguments, and really letting them stew in your brain for a while before articulating a rebuttal. This way you will actually change your mind on occasion, and hopefully fixate on correct beliefs more often. If you announce a side it is hard to change your mind because your talking side really want to convince others and yourself that you were right all along, and your biases 'blind and bind' more quickly the more you invest in them. To have strong opinions, weakly held, means you can't advocate for them too strenuously too quickly.

But let me address something I think is wrong. He says there are 6 innate values people have

1) care, compassion.
2) fairness, justice.
3) liberty, oppression
4) loyalty, group pride
5) authority, respect
6) sanctity, disgust, purity

Liberals, in Haidt's view, value care and fairness the most to the exclusion of the others; conservatives value all of these. Most non-Western cultures value all of these. He thinks liberals, of which he is one, are wrong to dismiss loyalty, respect for authority, and sanctity as backward because these are all helpful intuitions in living in complex societies where a lot of trust is needed.

Yet, I too find myself prioritizing care, fairness, and liberty, and not very interested in loyalty, authority, and sanctity, and he notes this is typical for libertarian/conservatives. To me the difference is whether 'care' in the form of welfare or affirmative action is really helpful; I find this kind of care to be counterproductive--encouraging behavior that creates dependence--thus I do seem compassionate because I do not like welfare.

Further, liberals may score low on loyalty, but they love group politics, noting various demographics underperform and thus need affirmative action. For liberty Haidt notes that conservatives are concerned about liberty vis-a-vis the state, liberal vis-a-vis corporations. For purity, liberals think about organic foods and a clean environment, conservatives a more chaste sex life. For fairness, liberal think about equality of results, conservatives equality in opportunity. So, I don't think his 6 foundations are that different between liberals and conservatives, they are just applied differently, because of different factual beliefs about the how these things actually work.

Haidt ends this book where he notes he read a book by Jerry Muller titled Conservatism, and the author noted that conservatism was not based on mere orthodoxy, but rather, the idea that encouraging respect, self-reliance, and loyalty were actually a reasoned method to help communities prosper, and their individuals to obtain more satisfactory lives. This reasoned defense of conservative values floored him, because he saw it was, at the least, intellectually defensible and could be argued in good faith. That he came to this conclusion in 2008 highlights the bubble the poor guy was in.

I don't doubt for a second the good intentions, at some base level, of everyone but psychopaths. This book just confirms that at some point we decide we know the right intuitive policies, and then we become partisan confabulators.

Having a bog allows me to articulate my intuitions, evaluate them, note the ill-tempered but sometimes trenchant rebuttal comments. Academics, politicians, and journalists really don't have that luxury because they become part of a team, and if you want to work up in those status hierarchies you have to be consistent and loyal, which means our most prominent rhetoricians aren't really thinking out loud, rather just rationalizing their team's prejudices (what they call, reasoned principles).

Haidt ends his book with a great line: 'We're all stuck here for a while, so let's try to work it out.' This is an attempt to get us to bridge political differences based on ideas discussed in his book. Unfortunately, given our desire to rationalize, the internet allows us to quickly google 'why global warming is true/false' very quickly, and we can then easily become satisfied with our assumptions because on virtually any issue there's some well written brief for any argument, and a well-written rebuttal for any argument. Thus, as it is now easier than every to rationalize our prejudices, so it is ever more important to understand why we do this, and how to mitigate it.

Derman Rambles on Risk

I generally find Emmanuel Derman to be a very thoughtful, but this interview with Russ Roberts made little sense. They were talking about Derman's latest book Models Behaving Badly, and they had these little riff on financial theory:

Derman: But I think Black-Scholes is much better than CAPM. Although it is based on the same idea. Because different stocks really have such different risk characteristics that the assumptions of geometric Brownian motion and the assumptions in CAPM don't hold very well for individual stocks.

He seems to be suggesting that geometric Brownian motion is essential to Black-Scholes or the CAPM. I don't see how this assumption is essential to the arguments of the CAPM or Black-Scholes, which follow in a two-period model even more easily than using stochastic calculus.

Derman: I know Burton Malkiel reviewed my book in the Wall Street Journal, and he liked it generally, he was complimentary, but he claims in one paragraph that I was putting too much weight--he sort of claimed that all the efficient market model says is, I don't know what's going to happen next, as opposed to saying that current prices are right.
Russ: The first claim is a modest claim.
Derman: Yes, it is a modest claim. And I think maybe he is technically correct, but I think in everyday parlance people strive for a stronger version of it.
Russ: Yeah; I think the way you wrote it in the book is that prices reflect all publically available information.
Derman: Yes.

I think Derman is wrong here, and this is important. Malkiel was arguing against Derman's conflation of a post hoc wrong price (ie, one that recently moved a lot), with an efficient price. According to this conception of efficient markets, every time anything significant is not foreseen, markets are inefficient. Fine, but I don't know any researchers who think markets are that prescient, so it's a straw man argument that doesn't help the debate. You can say that's the common conception among your colleagues, but that just means your colleagues like beating up straw men arguments in this domain.

Interestingly, even Eugene Fama chirped in the comment section to say, 'great interview [throat clearing!], but he doesn't understand these points.'

The Emergent Nature of Doing Good

Ex-Goldman employee Greg Smith wrote a New York Times editorial on the standard lament that his company doesn't care about the customer any more:

Today, many of these leaders display a Goldman Sachs culture quotient of exactly zero percent. I attend derivatives sales meetings where not one single minute is spent asking questions about how we can help clients. It’s purely about how we can make the most possible money off of them.

He sees the problem that his company maximizes profits, not helping the customer. This is a common refrain, one made by Einstein, who noted that socialism was better than capitalism because one system produces for everyone, the other for profit.

People serve others in modern society in very nonintuitive ways. In small tribes we are pretty aware of who is part of the team and who is a loafer, and how our stuff gets there. In modern society, by contrast, we have things as simple as pencils that we simply could not make even if we knew how to make it. We all rely on a vast number of things we have no way of making ourselves, from our iPad to our breakfast, and it isn't possible for everyone to go back to being a hunter-gatherer even if we wanted to, our productivity would be insufficient to feed everyone.

Adam Smith presented the argument on the invisible hand, how the self-interest of the butcher and blacksmith incented them to create goods and services that, in a competitive market, lead to specialization, cost minimization, and gains from trade. As a businessman, profit is one of the better signals of value out there simply because everyone else likes profit too, so you have identified an area where you are literally creating value. This is a highly counterintuitive point, and so most people simply don't believe self-interest is consistent with a good society, because that's not how their family works.

The problem is, altruism is very specialized in focus, whereas self-interest is not. Altruism is centered on people related to us, where I would sacrifice myself for my two siblings, or 8 cousins, thus, unconditional charity does not generalize from kin to non-kin very well. However, there is reciprocal altruism, basically helping other who can help you regardless of genome, and this is where it truly pays to understand how to service a customer--but only for the end-result of making money! It happens all over the animal world, as you see animals expending valuable resources towards another, yet only if there's some quid pro quo (eg, flower and bee, plover and alligator).

Recent support for this comes from a variety of sources, and the latest is a paper in Science--Markets, Religion, Community Size and the Evolution of Fairness and Punishment--by Joe Henrich et al, who administer fairness experiments across 15 diverse populationsand found that more commercial societies tended to be fairer. That is, people are nicer the more commercial they are, because being nice is good business. It took McDonald's to get Muscovites to smile.

The world is not filled with people like your mom and dad who showered you with love and resources merely for being you. It is filled with people totally indifferent to you except in so far as you can help them. If that makes you sad you really haven't thought about it, because a society of that much love would be really oppressive--even just one mom can be smothering, imagine thousands of her.

Smith then ends with a riff that really underscores the weakness of his point:

My proudest moments in life — getting a full scholarship to go from South Africa to Stanford University, being selected as a Rhodes Scholar national finalist, winning a bronze medal for table tennis at the Maccabiah Games in Israel, known as the Jewish Olympics — have all come through hard work, with no shortcuts.

Talk about selfish, such accomplishments didn't help anyone but him! There is no customer that will pay for self-indulgent status climbing in irrelevant hierarchies, regardless of how much we encourage our kids to play such games. That is, ping pong is a fabulous avocation, a pathetic vocation. We all want our children to play and engage in poetry, and when they excel at these things we are rightfully proud. Yet these are things kids do to develop skills like discipline, creativity, courage, that ultimately are valuable because of what they can do for others. They are not good in themselves, at least to society at large.

A similar quandary comes up in other domains such as science. The objectivity of science is not primarily from the integrity of scientists, but by scientists competing with others about how to explain the real world. As the left-brain is constantly rationalizing beliefs and data it receives from the right side, rationalization is the default method of reasoning whether we like to admit it or not. It helps to be on the side of truth because it's a lot easier and more fruitful, but it is not essential, and generally we make some base assumptions off our intuitions and then apply an 'anything goes' rhetorical style. It is naive to present your side of some scientific debate as being better because it is filled with people of integrity, as all sides in any large debate involve omitting inconvenient data and exaggerating the consistent data. They key is being on the right side, having the right biases, prejudices, assumptions, because confabulation is hard-wired into the human mind.

Being a good businessman is like being a good scientist. The most important thing is having the correct foresight to see the long-run, as in the long run the truth or value will win out. Having empathy for the customer or a respect for the truth in science is helpful in achieving those ends because you are better able to correct yourself before becoming too tied to bad causes via sunk costs and golden handcuffs. Day-to-day a simple focus on profits cuts through a lot of confused thinking about vague concepts like 'serving our customers', a subject that has produced its share of tiresome essays. Alternatively, nonprofits do this all the time if you really enjoy that kind of focus, or you can go off Jerry Maguire-like and start your own thing if really inspired, many people do.

That Which Doesn't Kill Us Makes Us Stonger

Yesterday the Fed announced most of the big banks passed their stress tests, and so there was a huge bank rally at the end of the day. What was amusing was this little line from those sneaky anti-capitalist news reporters at the WSJ:

The stress-test results—together with signs that bank lending is perking up in the U.S.—suggest the unpopular bailouts of 2008 and 2009 helped to stabilize the banking system during the financial crisis and put the economy on the path for recovery.

This is the worst banking crisis since the Great Depression in terms of the cumulative depth of contraction from the onset of the recession. Four years later, when the economy finally starts to show some strength, it is supposedly due to our savvy governmental intervention. Talk about grading on a curve.

The Philosophy of the Ultra Wealthy

At the MIT Conference last Friday, our lunchtime keynote address was from Donald Sussman, the founder and chairman of Paloma Partners. He's a very rich guy and surely has made many savvy business decisions. For example, he mentioned that around 1992 he was invited with about 200 businessmen to hear a pitch by the Chinese government on investing in China. He not only paid his own way unlike everyone else, he stayed in a nice hotel rather than the free (but very modest) accommodations provided. The government was so impressed, they presented him with a unique opportunity that turned out to be quite profitable. Clearly, this was fortuitous signalling.

Another interesting point he made was that it is useful to exit a trader when he's had a super year, and a super amount of investor inflows. Invariably, these people are going to discover their limits of scale, and it will end badly.

On the other hand, Sussman was pretty bad at articulating some unified set of principles, and spent a lot of time discussing his childhood, which is pretty narcissistic and extremely boring. It reminded me a bit of Bridgewater Capital billionaire Ray Dalio's manifesto, which set a new standard. He first lays out 210(!) principles--be extremely open, don't tolerate dishonesty--and then notes: "What follows is the Meat..." and then 200 more (eg, 'don't try to please everyone'). The earnestness and lack of focus reminded me of my childhood, when visiting my grandparents in a small town and I was forced to listen to very unpersuasive didactic Lutheran sermons.

I think it's admirable for people to try to articulate their philosophy on life, but they should be aware that being very successful at business or politics in no way implies they can explain that success. As Michael Gazzaniga has shown, the part of the brain (usually on the left hemisphere) that narrates our thoughts in our own head does not have access to all the reasons why we feel the way we do, or why we did some things, and it is engaged in post hoc rationalization all the time (this is why you should switch your date's decaf with a a caffeinated coffee, or take her to a scary not sleepy movie, because when her heart races her interpretative left-brain will put some more weight on the possible explanation that her right-brain must find you attractive for some reason). We know a lot more than what we can say. I don't presume that having a redundant and trite Weltanschauung means these people aren't good investors or managers, merely, their ability to pontificate on a general life-strategy is not the core of their alpha.

Stick to what you know. And don't talk about your childhood to a captive audience.

Are High Beta Assets Really Low Risk?

At Friday's conference, Sam Wildeman of GMO articulated his diagnosis of the low volatility anomaly: high beta stocks are low risk. He seems like a good guy, merely confused, so as a public service I'll try to explain why this makes about as much sense as the qwerty keyboard.

His basic idea comes from the finding that high beta stocks tend to have higher betas in bull markets (good!) and lower betas in bear markets (also good!). In that sense, they are less risky than a simple high beta asset. True enough. A 1.5 beta portfolio probably has less risk than the SPY levered 1.5 times due to this effect. But the higher beta portfolio is still considerable riskier than average by any definition.

Here's a histogram of monthly returns from 1962-2011


Here's the same thing in months where the S&P500 Index return was negative


So, the lower tail is proportionately larger for high beta stocks for both the total sample, and the truncated sample when the S&P500 falls. I don't think the 'long put' idea is really at work. Now, it is true that prospective betas are closer to 1.0 than measured historically, and this has been well-known for decades. The initial two-pass sorts in Fama and MacBeth in 1973 was created to correct for the fact that high beta stocks, in general, are over-estimated, and low beta stocks are underestimated. This is also accounted for in beta estimates that incorporate a bayesian prior, as is the default assumption for Bloomberg betas.

If it could be shown that high beta stocks are really low risk stocks, that would be a neat trick. I don't see any evidence for that.

Do Low Vol Tactics Matter?

An important question for any strategy is how important tactics are. That is, for some strategies, tactics are unimportant because the algorithm has a 'flat maximum', where lots of parameters generate outputs very nearly as good as the optimal parameters. Debt models have this characteristic, as a handful of inputs generate the optimal metric pretty well with a variety of weightings and transformations.

What about low volatility investing, where one can invest several ways. In the first, you take stocks with the lowest variance over the past N days, and form a portfolio. That's the route the SPLV etf takes. Or you could take the stocks with the lowest beta. Then, there's the factor approach, which applies mean-variance optimization to a set of latent factors drawn from the cross-section of stocks. Standard constrained-optimization algorithms can be applied to this problem. There are other ways, such as how the LVOL etf chooses stocks that closely fit a low-vol portfolio proxy, but I find that a bit too complicated.

In any case, I took 1500 non-etf US stocks, and applied the beta, volatility, and factor approach using daily data through Feb 2011, and then looked at the resulting porfolios over the next year. Each portfolio had about 100 stocks, and they overlapped by about 65 stocks. Volatility was reduced by about 45% relative to the equal-weighted benchmark that it was drawn from. In contrast, value and growth strategies had very different trajectories. This suggests the specific algorithm doesn't matter much if you are merely targeting low volatility.

VXX Expensive Again

Looking at the SPX index, actual annualized volatility has been below 10 for the past couple months, which is very low historically. Funny you don't hear about Taleb or Spitznagel when vol crashes, only when it spikes (talk about a convex payoff!). See below for a chart.


The VIX futures, which are closely related, show that not only is the VIX spot relatively high, but the future volatilities are even higher. The slope of the futures curve is very high. As the VXX and TVIX are hedged via riding down the futures curve, this suggests above-average costs of using the VXX to hedge one's equity exposures.


Now, the betas formed by regressing against the SPX vs those formed against the VXX form an almost perfect linear relationship (this was done using 5-minute returns for 800 non-ETF stocks). Note the higher the SPX (aka regular) beta, the more negative the VXX beta, so one can translate a position into VXX pretty easily, and by going long (plus, you can use the TVIX, which gives twice the exposure per dollar).


Many people hedge equity positions by going long volatility, and this does make sense because the VXX beta is around 2.3, so you seem to get a lot of bang for your buck. But the current contango suggests you are going to lose way more than 10% more than the VIX over the next year, so, that's a tax worth rethinking. Last year, this trade wasn't so expensive, as the futures curve had about one fifth the slope, but this year's slope is ridiculously steep.

If you want less equity exposure you should lower your beta or volatility by adopting a low volatility tilt. Alternatively, allocate less money to equities. It doesn't make sense to pay insurance that costs more than anyone's equity return premium.

Great Riff on Coming of Age

from Michael Oakeshott's essay On Being Conservative:

Everybody’s young days are a dream, a delightful insanity, a sweet solipsism. Nothing in them has a fixed shape, nothing a fixed price; everything is a possibility, and we live happily on credit. There are no obligations to be observed; there are no accounts to be kept. Nothing is specified in advance; everything is what can be made of it. The world is a mirror in which we seek the reflection of our own desires. The allure of violent emotions is irresistible. When we are young we are not disposed to make concessions to the world; we never feel the balance of a thing in our hands—unless it be a cricket bat. … Since life is a dream, we argue (with plausible but erroneous logic) that politics must be an encounter of dreams, in which we hope to impose our own.

To rein in one's own beliefs and desires, to acknowledge the current shape of things, to feel the balance of things in one's hands...these are difficult achievements; and they are achievments not to be looked for in the young.

That's rather touching, but I do think he neglects the fact that there is also a lot of insecurity in youth, when one does not know if one is on the right track.