Real Investors Lag Indices by 6%

I recently discovered there is considerable amount of data documenting how much investors underperform indices, and it's being ignored. In the 2008 Journal of Pension Benefits, N. Scott Pritchard documented that that individual investors have done much worse than the indices that everyone assumes reflect investor returns. He looked at data from 401(k) plans, and found that from 1988 through 2007, while the S&P 500 returned 11.81 percent annually and Treasury bills returned 4.53 percent, the average investor achieved a return of only 4.48 percent.

Pritchard relied on the annual Dalbar study, which consolidates data from the Investment Company Institute, and is availble for investment advisers as a way to show them what the 'conventional wisdom' is on asset allocation and investor performance. More recent data found that over the twenty years ending in 12/31/2010, the average annual equity return for investors was only 3.27%, while the S&P500 was 9.14%.

So, this 6% investor underperformance you would think would be very interesting news, because the risk premium is one of the most important facts in all of economics, being the subject of thousands of research pieces, but instead it has had about zero impact. No one finds it interesting because it is not useful to academics or investment companies.

To put this into perspective, one of the most important research findings in twentieth century finance was when two professors at the University of Chicago, James H. Lorie and Lawrence Fisher, created what has become the preeminent database on stocks in the United States, what is now known as the Center for Research on Security Prices (CRSP) database.

The front page of the New York Times financial section heralded the pair’s findings, and their Journal of Business article reported the average of the rates of return on common stocks listed on the NYSE was 9 percent for the NYSE from January 30, 1926, to through 1960. Included in the NYT article was a flattering picture of them in a room with a big computer, emphasizing that this was very scientific. Interestingly, if you read their paper, you will see how academics bury their lede by noting that this final result is not conspicuous, highlighting that academics like to emphasize their technique, not the results.

Now, this was 3% higher than the average annual return on the Dow Jones index, but with dividends added, about the same, so why the big deal? It was important because while this old data probably still contains large amounts of survivorship bias, it meticulously corrected for all sorts of other issues and therefore added the patina of academic rigor to a fundamental financial constant: the equity risk premium.

This result stood for decades, and led to many to think the equity risk premium was on the order of 6-8% up to the internet bubble of 2001. It validated the new 'risk premium' paradigm that was being created in the early 1960s, where risk, properly measured, generates an observable return premium over time, because without higher expected returns no one would invest in risky assets. When combined with a stock's beta, it generated the expected return for each asset, making a seemingly qualitative problem one amenable to linear programming.

Much has happened since then, most importantly, the poor returns since 2000, which have reduced most estimates of the equity risk premium to around 3.5%. This excludes transaction costs, and adverse timing, which are captured in the Dalbar data. And of course this excludes taxes.

Happy Halloween!

Everyone likes to mock people who dress up their pets, but my daughter has been saying 'doggy Batman' over and over for the past few days, in pure delight over the sublime ridiculousness of combining a dog, a bat, and a man. Worth every penny. Boys have grown out of Star Wars, and are now 'scary/gross.'

Investors Underperform Indices

mistake (see above)

Shorting Leveraged ETF Pairs

ProShares offers a wildly successful array of Exchange Traded Funds (ETFs) that allows people to easily gain leverage and short targeted subsets of stocks. They trade a lot, and so clearly are satisfying consumer preferences, but probably the more delusional part of investor beliefs. Their explicit goal of targeting a daily benchmark return correlation leaves the secondary consideration less important: maximizing long term return. Thus, they tend to underperform their benchmark over longer durations, and this adds up. I suspect they end up burning money trading so much in a way that traders can anticipate and game.

If the Proshares are underperforming, there's a simple arbitrage here. Take the 'Ultras', which offer 2x leverage, and the 'UltraShorts', which offer the opposite, -2x exposure. Going short both stocks generates a very low-risk portfolio pair, because on a daily basis when one goes up 1% the other will almost surely go down about 1% by design; the positions will offset each other. But the drift for both is negative, as they burn money. Since ProShares has been very busy adding ETFs, this simulated strategy started with 23 pairs in 2008, and is now up to 45. Below is a graph of the total return to going short all the Ultra and UltraShort pairs offered by Proshares since 2008. I rebalanced every week. The annual return was 14%, and the annualized standard deviation was 12%.


Now, I am ignoring the short rebate, which for these may have been highly negative for some of these, but on average these have pretty meager short rates. As the S&P500 has a prospective Sharpe of 0.3 (excess return of 5% and standard deviation of 15%), this is a very dominant strategy. Notice that while the annualized vol is 12%, this really overestimates the risk here because most of this volatility is 'good': sometimes returns are much higher than average. It's a rather Madoff looking strategy

Another way to shade this is to notice that it works best during periods of high volatility, and among those pairs with the highest volatility. Notice that the October 2008 to March 2009 was a great time for this strategy, and so was August 2011, when markets were reeling.

Below are the returns to the various pairs I used, annualized. You can also use these pairs to simulate them yourself. Over time, I suppose these ETFs should start trading at a discount to their net asset value, but until then, it's a pretty simple strategy that seems to work.

Total Return to Short Pairs

pair1	pair2	AnnRet
AGQ	ZSL	31.8%
BIB	BIS	3.7%
DDM	DXD	9.0%
DIG	DUG	18.8%
EET	EEV	7.7%
EFO	EFU	8.0%
EZJ	EWV	6.6%
LTL	TLL	16.2%
MVV	MZZ	8.5%
QLD	QID	10.2%
ROM	REW	7.9%
RXL	RXD	5.2%
SAA	SDD	10.4%
SSO	SDS	9.6%
TQQQ	SQQQ	3.0%
UBR	BZQ	1.1%
UBT	TBT	4.8%
UCC	SCC	7.3%
UCD	CMD	6.5%
UCO	SCO	5.7%
UDOW	SDOW	5.3%
UGE	SZK	5.6%
UGL	GLL	8.1%
UKF	SFK	7.6%
UKK	SKK	12.8%
UKW	SDK	7.9%
UMDD	SMDD	5.9%
UMX	SMK	5.8%
UPRO	SPXU	4.5%
UPV	EPV	17.0%
UPW	SDP	13.8%
URE	SRS	51.8%
URTY	SRTY	13.9%
USD	SSG	10.2%
UST	PST	3.8%
UVG	SJF	10.7%
UVT	SJH	14.7%
UVU	SJL	20.1%
UWC	TWQ	2.5%
UWM	TWM	12.6%
UXI	SIJ	5.9%
UXJ	JPX	4.7%
UYG	SKF	30.8%
UYM	SMN	11.0%
XPP	FXP	7.1%

DailyKos on Good Intentions

I found this funny:

While Communists are certainly responsible for more deaths and misery than the Nazis could ever dream of, at least their intentions were good, so I'll give them a pass.

The entire article was filled with such observations, making me wonder whether the website was hacked. So, if you cause more death and misery than the Nazis, but have good intentions...it's ok? [I'm now told it was an attempt at sarcasm. If so, it's stupid sarcasm.]

Calomiris on Underwriting Problems

Charles Calomiris taught me Money and Banking in graduate school, and I thought then he was very wise. Here he is in today's WSJ:

In a painstaking forensic analysis of the sources of increased mortgage risk during the 2000s, "The Failure of Models that Predict Failure," Uday Rajan of the University of Michigan, Amit Seru of the University of Chicago and Vikrant Vig of London Business School show that more than half of the mortgage losses that occurred in excess of the rosy forecasts of expected loss at the time of mortgage origination reflected the predictable consequences of low-doc and no-doc lending. In other words, if the mortgage-underwriting standards at Fannie and Freddie circa 2003 had remained in place, nothing like the magnitude of the subprime crisis would have occurred.

Good Ideas Become Clearer over Time

Kant is known for his theory that there is a single moral obligation, which he called the "Categorical Imperative", and is derived from the concept of duty. Moral acts are those done in good will, which are done for the sake of duty. Duty is the necessity of acting out of reverence for universal law, something that you would want everyone in a situation to do.

Now, I find this reasoning rather flawed,* but my opinion on that isn't my point. In the Groundwork for the Metaphysics, of Morals Kant states that what he is saying is not the same as the Golden Rule; that the Golden Rule is derived from the categorical imperative with many important limitations. Many agree with Kant, such as radical egalitarians like Jurgen Habermas (see here), or John Rawls (see here). On the other hand, many argue that the Categorical Imperative is the same as The Golden Rule. Biologist and economist Peter Corning and game theorist Ken Binmore suggests that Kant's objection notwithstanding, the Golden rule is basically Kant's Categorical Imperative.

This seems like one of those ideas that is infinitely malleable, merely useful to give false authority to one's current pet idea. Habermas and Rawls did not want to engage in a debate on the practical issues of radical egalitarianism (its usefulness to tyrants, its impossibility, its assault on liberty), they preferred to simply defer to some famous philosopher's statement that is not evaluated merely by its consequences.

A good idea becomes clearer and more useful over time, while bad ideas become more subtle. Black-Scholes and Feynman diagrams are useful tools, taught to every beginner in finance and physics, because they explain things very parsimoniously, and because they are so clear can be extended or modified, which is the goal of every active mind. The invisible hand, the idea that inflation is ultimately a monetary phenomenon, that free markets decentralize knowledge and incentives, all simple, powerful, ideas. An idea's objective and quick decipherment enables us to avoid the systematic errors which invariably arise from prolonged entanglement. The longer we look at something vague and well-known, the more we qualify it to make it more sympatico with our prejudices.

In finance the risk premium started as volatility, became beta (covariance with the stock market divided by the variance of the market), and is now a covariance with some undefined set of proxies for our happiness (too be uncovered by powerful econometric techniques really soon). The 'risk premium' is a bad idea. Taleb's 'Black Swan' applies to anything unexpected, and as every specific outcome is in some sense unexpected, it applies to everything (except finance, says Taleb, which is ironic because presumably his 'buying cheap options' strategy supposedly reflects the profundity of his approach). He now says 'Ideas come and go, stories stay,' which makes about as much sense as anything else he says.

* I agree with Nietzsche that duty is not obvious, and often some self-serving platitude for some powerful interest, so it isn't helpful to state that something that is a duty is best. Further, it makes no sense to ignore context when applying a universal law, as when you should lie to keep Nazis from finding Jews in your basement, or when you kill a dangerous burglar, and so universal law is not obvious. Lastly, as Ayn Rand noted, ignoring the consequences of actions, and just focusing on the duty, is irrational, because we act to make things in a real world that we might as well believe really is real. Finally, I should note it is rather circular in practice, because in the end the 'universal law' is defended on utilitarian grounds anyway (eg, it will make society happier).

Haidt on the Moral Foundations of Occupy Wall Street

Happiness author Jonathan Haidt on the Occupy Wall Street/Tea Party difference:

We really hate cheaters, slackers, and exploiters. By far the most common message I saw at OWS was that the rich (“the 1 percent”) got rich by taking without giving. They cheated and exploited their way to the top. As if that wasn’t bad enough, we the taxpayers then had to bail them out after they crashed the economy, and so now they really owe us for saving their necks. It’s high time that they started giving back, paying what they owe.

As a point of comparison, a similar look at signs found at the Tea Party rallies suggests that protesters there are also chiefly concerned with fairness. The key to understanding Tea Partiers' morality, though, is that they want to restore the law of karma. They want laziness and cheating to be punished, and they see liberalism and liberal government as an assault on that project. The liberal fairness of OWS diverges from conservative and libertarian fairness in that liberals often think that equality of outcomes is evidence of fairness.

Those who think the market is generally fair and rewards virtue, who think that unequal ability is primarily from effort, discipline, and finding one's niche, believe in markets; those who think the market is generally a rigged game that rewards vice, that people are basically equal and become unequal mainly through forces beyond their control, believe in greater government control. Equality of outcomes is justice in one case, injustice in the other. Given these different assumptions are responsible for the most pressing political disagreements we have, and these are rather factual statements, the nice thing is that someday there may be more agreement on politics.

Bank Lending Dilemma

In the Financial Times, Larry Summers argues lenders should pay more for past bad loans, and also make more now:

First, and perhaps most fundamentally, credit standards for those seeking to buy homes are too high and rigorous.
...
Surely there is a strong case for experimentation with principal reduction strategies at the local level.
...
Fifth, there were substantial abuses by financial institutions and almost everyone in the mortgage industry during the bubble. Just compensation to the victims is a legitimate objective of public policy. But allowing negotiation over the past to dominate present policy creates overhangs of uncertainty that impose huge costs on the financial system and inhibits lending.
...
Bank regulators could facilitate inevitable restructuring of underwater mortgages by requiring banks to treat second mortgages and home equity loans in realistic ways.

Summers seems to recognize that punishing banks hurts new lending, but he also thinks some form of bank punishment would be just. Until they get over this and let the banks alone, lending will remain weak because banks are wary of the lookback option being giving to borrowers who 'bought' houses without the means or willingness to pay it back. In the US, loans are already 'non-recourse', meaning borrowers can walk away and let the lender eat most of the loss, but people want 'just compensation', which is a code word for an expropriation from banks to NINJA borrowers.

Until regulators, legislators, and the experts that advise them stop hounding banks for their old home loans, new home loans won't be forthcoming. It's all good and well to say we should just nationalize home lending, but if public housing is any guide that's a disastrous endgame.

Obama's latest housing effort seems like the last iterations (Hope Now, Hope for Homeowners, the Home Affordable Mortgage Program, the Home Affordable Refinancing Program, the Hardest Hit Funds), but until things like the Department of Justice's lawsuit against banks gets cleared up, banks won't consider homelending anything but toxic.

Short Powerful CEOs

A recently published article in the Journal of Finance by Morse, Nanda, and Seru argues that if you generate a metric of CEO overreach, their stocks underperform. They define CEO malfeasoance using the example of Home Depot CEO Robert Nardelli, who in 2005 changed his incentive pay to be based on average diluted earnings per share, from the tota return to shareholders over the prior 3-years compared to their peers. This was very convenient to Nardelli, because he did much better on the new comparison over the old, and it abrogated the prior performance contract; a lookback option, as it were. Nardelli presided over a 6-year period (2001-07) where the S&P500 was up 12%, Home Depot lost 17%, and Nardelli pocketed a $240MM for his stewardship.

The researchers construct three different metrics of CEO power. One is whether he is also President or Chairman of the Board. Secondly,they uses insider ownership, the amount of stock owned by the directors. Lastly they capture the percent of the board appointed by the CEO. They use regression analysis to find that firms with high CEO power face a 4.8% decrease in firm value going forward.

It would have been nice if they put this into a long-short portfolio and showed the portfolio return characteristics. As the data covered the infamous tech bubble (1992-2003), a lot could be explained by the rather singular 2001-2 tech bubble, which while interesting, is much less interesting than if this result was more persistent across time periods. In any case, another reason to read proxy statement footnotes, and hopefully people will invest on this information which would be the best way to regulate it. Home Depot got what they deserved, those responsible, shareholders, suffered most.

.

Aggregate Supply and Demand Nonsense

One characteristic of Keynesian thinking is to think the problem currently is with inadequate Aggregate Demand, as if this is some simple analytical construct that is just as meaningful as the demand for apples. This is nonsense. Aggregate Demand and Aggregate Supply are incoherent constructs that require heroic assumptions. You might as well talk about the current law of motion on the Hegelian Dialectic, which for decades was discussed as if it were real. Things exist before people know they exist (eg, nations, atoms), and things also don't exist even when many are certain they do (eg, anthropomorphic God, aether, phlogiston). About what one can not speak, one should remain silent, and you can't talk about something that is as logically vacuous as aggregate supply and demand.



In partial equilibrium, a good exists and its price represents its output relative to innumerable other consumer wants. This is why the demand curve slopes downward, because the more it costs, the more you have to forgo of other stuff. Demand curves are driven by consumer utility (which decreases as one consumes more of a specific good), and income (which shifts it about). For supply curves, the correlate to utility curves are cost curves. One generally produces where marginal cost equals price, and so marginal cost is increasing (if it were decreasing, you could increase supply and lower costs for a 'given' price). Thus, you only raise your output if the price rises.

You can assume demand and supply move separately, as when seasonal harvests of perishable goods arise in supply, or demand for cranberries increases before Thanksgiving. The logic of supply and demand curves in markets is firmly based on utility and cost functions, and is a very useful way to think about things.

Now consider Aggregate Demand. Here the 'price' on the vertical axis is not a relative price, but rather an absolute price level, which by itself is meaningless. If there was only one good in any economy people cared about, what would its 'price' even mean? So, right off the bat, something's fishy. Supposedly, in normal times the AD curve slopes down, we think, because other things equal a higher price level increases the demand for money, which drives up interest rates, which reduces investment and spending. But how does one increase the price level and leave 'other things equal?' One can imagine doing this in partial equilibrium, but it's a strange thing to contemplate over all goods. Further, at interest rate levels like today, it's not as if lowering interest rates is having any effect on investment (the liquidity trap, which is occurs always in real time for Keynesians, who always say this is why government spending is necessary now).

Then there's the 'Pigou's wealth effect', which affects wealth by changing people's real balances, because presumably their cash levels are constant but magically prices move, affecting real wealth, CashValue/Price. However, offsetting that is the 'Fisher real balance effect', where one's debts change in real value. These debt effects are generally thought of as more important, and why most macroeconomists believe a little inflation would be good right now, and perhaps always: it reduces the legacy debt in real terms.

Lastly there are Mundell-Fleming effects, which operate though capital inflows caused by changes in real rates from changing the price level. Supposedly lower interest rates lead to capital account deficit, which a trade surplus, which implies higher GDP. The data on this are mixed, but generally international trade is the tail, not the dog, for large countries like the USA.

Now consider aggregate supply, which classically is horizontal, and then in the Keynesian world vertical. It supposedly becomes positively sloped because 'prices' refers to outputs, not inputs. Why prices supposedly effect finished goods rather than wages or intermediate goods is strictly ad hoc.

This is why general equilibrium models, like those of Edward Prescott and Finn Kydland, whose Nobel Prize winning research emphasized shocks to utility or production functions, because one has to put in some ad hoc structure to get these aggregate demand and supply curves to work in the Keynesian paradigm. Now, I don't think Prescott/Kydland models work either, but most policy debates aren't predicated on these models (I don't know anyone to really believe our problems are currently a technology shock, or preferences for more leisure).

The result of this flawed paradigm is to continually assert that simply spending more on X increases aggregate demand via their spending, because one becomes inured to extrapolating partial equilibrium analysis into general equilibrium results. Consider this AFL-CIO press release, which conflates more spending on union jobs with greater prosperity. If only everyone worked for a government protected industry with market power, presumably, we could all work 9-4 with negotiated, predictable wage increases.

So, like discussions in Marxist economics, which often involves very learned, earnest, and prolix researchers, it's best just not to go there, because it's gibberish. Don't say Aggregate Demand, say, subsidies to investment of some kind, or more government spending, because that's more meaningful, and then ask, should we be subsidizing these investments, or having more government spending? The indirect effects are so speculative you might as well ignore them, and just ask if the direct effects are worthwhile.

Do Academics Overfit?

Yes. Academics are just as susceptible to this bias as anyone else. On one hand they have extra discipline from having to put their ideas out there, while on the other hand they often don't pay the price for creating overfit models in the way a poorly performing asset manager would. The big difference between academic overfitting and that from your average quant is that when academics do it they are much better at rationalizing such models.

I've worked with finance professors on consulting projects, and cherry-picking data recent data and pointing to something 'out of sample' when it is used iteratively is quite common. An important postulate to remember is that there are no true out-of-sample backtests, just tests of subsample stability. Invariably researchers know about the entire dataset in question, so out-of-sample results are really models that when fit on a subsample and applied to its complement generate the best fit. That is, quants try models sequentially until they find one that works well 'out of sample,' which means the data is not really out of sample.

That's not to say out-of-sample tests are meaningless, just that it takes a lot of self-discipline because a lot of this is done outside the box, and the easiest person to fool is often oneself because it's very tempting to believe things when they imply many self-serving benefits. This is why integrity is a virtue, because it's hard, uncommon, and helpful. It's tempting to over-promote your own pet idea as tendentious advocacy can seem necessary in the real world where 'everybody does it.' But, the biggest problem knowledge-workers make is not making a logical error or not being able to solve a complicated problem, but working on something that is a dead-end, because that implies you've just wasted a large part of your career: an expert on input-output models, Keynesian macro models, dynamic programming isn't valuable for making decisions. Fooling yourself into believing in a false model simply wastes your time.

Consider John Cochrane and Monika Piazzesi's Bond Risk Premia paper that purports a model that forecasts one year bond excess returns with a 44% R2. Both are competent academics who I generally respect, as I think they are smart, careful and do research with good faith. Their model suggests that if you look at the current forward rates from the US Treasury yield curve, the first five forwards predict year-ahead bond returns very well (to be precise, these are 'excess' returns, so they subtract the 1-year bond yields).

What is this model? Basically, if you run an ordinary least squares of the 10yr bond return over the next year (minus the 1yr yield), on the forwards. They looked at the 1964-2004 period, which has 467 monthly datapoints, but because these are year-ahead returns, we really only have 39 totally independent datapoints, which is not a very large sample (most year-ahead returns being highly correlated because they share much of the same data). So the basic pattern they found was

year ahead 10yrBondReturn-1yr Bond Yield=a+b1*f1+b2*f2+b3*f3+b4*f4+b5*f5

*here f1-f5 are the 1 through 5 year forwards.

You can download his data here. Now, the first problem I found is that his bond data is a bit fishy. He used bond data from CRSP, and 2 and 4 year USTreasury datapoints are pretty uncommon. His 4 and 5 year forwards yield changes have a suspiciously low correlation. In anycase, I took the H15 data using their 1, 3 and 5 year monthly bond yields, and generated pretty much the same result: tent-shaped set of coefficients on the forwards (approximately equal and negative for 1 and 5 year forwards, positive and larger for the 3 year forward), and my R2 for the 1964-03 period was a large 31%. My results look like this for the same sample period Cochran and Piazzesi use:



The coefficients suggest that there are higher returns the more concave the forwards are, and lower returns the more convex. This doesn't really make any sense, in that there's no intuition as to why this 'tent-structure' of coefficients is related to risk, or utility, it just comes out of a best fit of the data.

If we look at the subsequent 7 years, that same set of coefficients that worked so well in-sample for 64-03, don't work at all for 2004-2010 (last datapoint was for the return from 9/2010 through 9/2011). See below.


So, it seems a classic overfitting of the data. Sure, the pattern could have just stopped, but given the model had no intuition, no causal mechanism, just some unlikely set of coefficients, it almost surely was an overfit. Such results, prior to Freakonomics and Behavioral Finance, were considered rubbish for a while, as the development of CRSP into a data source led to a lot of stupid correlation papers in the 1980s and 70s, but the success of other atheoretical findings (momentum) has unleashed non-intutive correlations into top tier journals.

As an academic, this will always be a plus on Cochrane and Piazzesi's vitas because it made a top tier journal (AEA 2005), but as a practioner this would have gotten them fired. Thus for academics, overfit theories that generate publications have little downside compared to a practioner.

Zero-Sum Game

A while back I got a copy of Zero-Sum Game by Erika Olson. She worked for the CBOT when there was a merger battle with CME and the ICE exchanges, so it's basically a lot of inside baseball on the corporate politics of acquisitions. It sat on my bookshelf hidden for a while, because it didn't really leap up at me. But eventually I found time to read it, and it reminded me of the old saw that everyone has a story to tell.

What's most telling is that any large institutional realignment involves a lot of little issues, and various stakeholders all have different interests and power, and making them all happy involves a lot of politics that is difficult to do publicly. The idea that merely passing a law will change things is pretty naive because any explicit, complicated process invites its circumvention. You need to align incentives, and in the private market this is by giving various people carefully delineated property rights (shares, seats), often via having them buy-in explicitly in some way. When you involve 'stakeholders' who don't have any investment in the process, they just have some vague sense of a better structure, these people just create more anachronisms and complexities that lower transparency and help insiders.

One of the more telling anecdotes was about how when Amaranth Advisers was still alive, it was breaking various position limits in energy on the NYMEX, and the CFTC which regulates the NYMEX took 7 months to actually enforce these rules. Yet Amaranth merely moved its positions to another exchange, the ICE, whose natural gas swaps were not subject to position limits at that time. One should anticipate that any regulation that mandates certain positions must be in a certain contract on a particular set of exchanges, will simply move to highly correlated positions in different venues.

Partying with Actuaries

As they say, what happens at the Society of Actuaries annual meeting, stays there. It was a pretty good conference, one with literally a dozen streams, so it's pretty easy to find some talk that's interesting at any time (it's actually continuing until Thursday). My talk (see pdf of presentation here), was pretty well received. That is, I had a lot of people telling me it's interesting, thoughtful questions, etc. This is in contrast to academics, who either tell me I'm stupid or crazy, though usually just ignoring me. I have not met an active finance professor who thinks my 'no risk premium due to relative status' is interesting, let alone true.

As mentioned, some professors have even been quite defensive, which is understandable. It doesn't bother me because it's fun to have the facts on your side. They'll come around, as they did on the low return to high volatility stocks and distressed stocks.

Bernie Sanders Clueless on the Fed

Patron saint of Liberal radio and websites, Socialist senator Bernie Sanders, questioned Bernanke this week, and he asked one reasonable question, namely, why not break up the top 6 banks if they are all 'too-big-to-fail'. Bernanke said he thought incentives in Dodd-Frank would better address the incentive problems. I'm not so sure. I would prefer the simplicity of having a maximum asset size than the open-ended regulatory gibberish in Dodd-Frank.

Then Sanders asked why the Fed does not provide low-interest loans to small businesses, to help kick-start the economy (see video here). He even threw out a number, $15 Trillion. Bernanke noted that the Fed has no structure to underwrite or service general loans to businesses. Sanders thought that this would be no different than offering back-stop liquidity to banks, oblivious to the insanely large amount of infrastructure needed for that to work.

That's just insanely ignorant, and highlights how the socialist mindset fails to appreciate the reasons why markets, and the firms that comprise them, are more efficient than government. It reminds me of Lenin's assumption that nationalizing industry would be trivial because business was strictly accounting, or more recently, the faith in shovel-ready projects. There are many stupid Republicans, but this really sets a new bar.

We are the 99%!

Egalitarians may be a majority, but they aren't close to 99%. This reminds me of the False Consensus Effect, which states that individuals view their own preferences, behaviours and judgements as being typical, normal and common within a broader context; it also suggests we find alternative characteristics as being more deviant and atypical than they actually are.

The blogger Psycasm did a survey, and asked them about their phobias, and compared them to what they supposed the percent of people shared these specific phobias, and got these results:


So, people who are afraid of spiders, dogs, and heights, vastly overestimate the prevalence of their specific phobia. Sort of like how economists, who have no alpha and are inclined to statistical optimization, assume all investors would invest as they would: presuming no alpha, optimizing mean-variance preferences. It's not a problem limited to proles.

I feel pretty calibrated, in that I'm pretty aware of my many beliefs that are a distinct minority. It doesn't bother me too much because I believe in meritocracy, which is inherently elitist. This not only is a minority view (at least in public), but it by definition considers 'common' to mean 'crappy' in most cases. As Aristotle noted, just because people are equal in some respects does not imply they are equal all respects; men are equally free, but not absolutely equal

We are a democracy, which means majorities elect the lawmakers, so it is important to have a majority opinion, especially if you want to pass laws that make people do what they would otherwise not (eg, pay more to strangers in Washington, not marry their partner, not own a gun). But there's no reason to brag about it, because it's merely a sign you can be a bully, not that you are somehow more enlightened:

The fact that an opinion is widely held is no evidence whatever that it is not utterly absurd; indeed in view of the silliness of the majority of mankind, a widespread belief is more likely to be foolish than sensible.
~Bertrand Russel

To disagree with three-fourths of the British public is one of the first requisites of sanity.
~Oscar Wilde

Interest Rates, Risk, and Macro Foundations

Tom Sargent, recent Nobel laureate, reminds us of the asset pricing-macro connection:

To put it technically, the “new Keynesian IS [investment-savings] curve” is an asset pricing equation, one of a form very close to those exposed as empirically deficient by Hansen and Singleton. Efforts to repair the asset pricing theory are part and parcel of the important project of building an econometric model suitable for providing quantitative guidance to monetary and fiscal policymakers.

I don't think this approach will work because I don't think standard asset pricing theory is near correct, and I'm not a fan of Keynesian macro models either. But here's an asset class that highlights why macro is in such a futz, why such different macro views can be held simultaneous by smart researchers: you can't reject their different priors.

Interest rates are probably the oldest and most liquid prices we have, and there are several facts associated with the basic risk-free yield curve:

1. The real term structure is fairly flat, but rises and peaks at around a 3-year maturity
2. Real rates are much more variable at the short than long end of the curve.
3. The nominal yield curve was flat prior to abandoning the gold standard in the 1930s
4. Inflation expectations explain the majority of nominal rate fluctuations
5. Interest rates have been pretty stationary over the past 100 years.

This latter point is especially important, because it seems the short term real rates is small (<1% and positive), over the past 100 years, though it varies quite a bit decade to decade. Most researchers think this series is not trending. This is inconsistent with any utility function other than those with 'constant relative risk aversion', a special set of preferences that imply 10% risk to one's wealth feels the same regardless of wealth. As real gdp per capita in the US rose 760% since 1900 through 2011, this seems the only logical conclusion. The most important thing to understand with yield curves is that the high quality of US bond data since 1953 makes this sample very prominent in research, and it has a very particular pattern, rising up to 1980, then falling, in concert with inflation.

US Interest Rates and Inflation: 1953-11

As bond returns are a function of their current yield, and the price appreciation from changes in market rates, the rising interest rate environment had low bond returns, the falling had rising ones. This leaves a tale of two regimes, and it isn’t clear whether the low real returns by maturity prior to 1980, and subsequent reversal subsequently, was an ‘expected’ return, or both period were unexpected.

Total Return Regimes to US Treasury Yield Curve: 1954-2011

Economists were just as surprised by the movements in yields over the past 40 years as anyone. I worked in a bank economics department from 1987-9, and can tell you we had no clue we were in a period of secular interest rate reduction, and that those same economists lamented their poor forecasts throughout the 1960’s and 70’s. In the 1990’s, 10-year inflation-indexed yields average about 3.5% in te UK, and exceeded 4% in the US around2000, and declined until a spike in 2008, and currently (2011) are below 1%. These movements are, in the words of Campbell, Shiller, and Vaciera (2009, Understanding Inflation-Indexed Bond Markets), a puzzle.

Keynes’s (1930, Treatise on Money) argued that the yield curve should rise due to a risk premium, Modigliani and Sutch (1966, Innovations in Interest Rate Policy) argue that there’s a habitat preference for interest rate investors, so that some prefer longer bonds, but most shorter durations. With the development of the stochastic discount rate factor, risk premium were supposed to be a function of covariances.

To test the yield curve then, we can look and see if we can explain the pattern across maturities or time, of the real return (the nominal return being trivially higher in higher inflation environments). The standard covariance factors are consumption, and the stock market. Consider the following 'betas' with the S&P500 and Real Consumption Growth range from -0.1 to 0.1, with an average of 0.05, depending on what periods (53-80 vs. 81-11), time horizon (daily vs. 60 month investment horizons), real vs. nominal returns, whether we are regressing against consumption vs. S&P500 returns. The point is, the data here are too noisy to confidently say that short, or long term Treasuries are 'risky': there's always a different view that says something different.

Looking at this over time perhaps shows the problem more clearly:

10 year US Treasury Slope with S&P500 vs. 10 year Total Return

Slope from rolling 85 month monthly returns

The lower returning early period, and the higher returning later period, do not show a clear distinction in the bond's S&P500 factor loading, and so it is with all the various permutations of these data.

The bottom line is that inflationary periods have lower bond returns than disinflationary periods, though it is not clear whether these are expected, and thus true risk premium. There is no obvious risk premium explanation of the 'default free' spectrum of bonds across maturities or time, and any statistical analysis that purports to say it all makes complete sense is clearly torturing the data (eg, see Bansal's 'long run risks' model that adds a bunch of parameters to explain more datapoints).

This is especially relevant to macroeconomics because in the standard New Keynesian models, a representative agent’s Euler equation that links a one-period real interest rate to the consumption growth rate is the IS curve central to the policy transmission mechanism. A long list of empirical failures come from applying the stochastic discount factor implied by that Euler equation. Until someone succeeds in getting some kind of consumption-based asset pricing model that works well, the New Keynesian IS curve is empirically vacuous.

The Brain's Permanent Income Hypothesis

The Keynesian consumption function assumes consumption is entirely based on current income, and is the basis for the multiplier, which magically translates investment in alien defense systems into greater prosperity. Milton Friedman's permanent income hypothesis is a theory of consumption whereby consumption is determined not by current income but by one's longer-term income expectations. The key conclusion of this theory is that transitory, short-term changes in income have little effect on consumer spending behavior. Federal stimulus plans, for example, are intrinsically temporary.

It seems are brains are intrinsically forward looking, more focused on anticipation of rewards than the rewards themselves. In studies with monkeys, where the monkey sees the light, pushes the button, and gets a treat, very quickly the monkey figures it out. Interestingly, the dopamine response fires not when he eats or receives the treat, but rather when he sees the light. The brain present values the stimulus, so that by the time the treat is tasted it has already been figuratively consumed. A short video on the dopamine effect is here.

It's a lot harder for the government to redistribute wealth than income, because wealth is primarily ability as opposed to cash. If you have a niche, a role where you feel valued, you are wealthy. The government can create only so many post-office jobs that grant sinecures arbitrarily, and all those temporary job incentives are seen as the transitory, ephemeral things that they are. To create real wealth, which is what really matters, you need to allow individuals to find their niches, which is best done indirectly.

Sims and Sargent

Minnesota Rules (that's where I live)! My favorite Sargent paper shows a model where even when inflation is a strictly monetary phenomenon, inflation it is really, in the long run, a fiscal phenomenon.

Chris Sims--who I've mentioned several times on this blog--is here. He basically destroyed interest in large-scale-macro-models, at least for anyone graduating subsequent to his seminal papers.

They will certainly help increase the Nobel Laureate signal/noise ratio, which currently is on par with those 'anarchists for big government' protesters. Though Sargent is, fundamentally, a macroeconomist, which means he says many silly things.

Another Reason to Dislike Habermas

I'm no fan of abstruse Marxist philosopher/sociologists, so I found this point rather amusing:

I remember reading a response by Habermas to a critic, limited to the statement that he refused to discuss with an individual who quoted Hegel from a secondary source.

I remember seeing a documentary on Jacques Derrida, and he was asked what one question he would like to ask Ludwig Wittgenstein if he were alive, and he said he would ask him about his sex life. Philosophers are pretty loony.

Dying Thoughts

Steve Jobs, a true mensch, left an estate worth around $6.5B. Nevertheless:

“Steve made choices,” Dr. Ornish said. “I once asked him if he was glad that he had kids, and he said, ‘It’s 10,000 times better than anything I’ve ever done.’ ”

I think those of us who love our kids are better off than childless billionaires. More importantly, the value of our children is 10,000 times more important than any financial fortune.

Taleb's Latest BB Riff

People often email me Nassim Taleb rants because I've written on him previously (see Black Swan review, Bed of Procrustes review), and I must say I enjoyed his latest. From the latest Bloomberg article on Spitznagel and Taleb, Spitz comes off as an incredibly fun guy, whereas I think this Taleb quote only got in the because the writer knew it was over the top:

“I’m not interested in money; I’m not interested in finance,” Taleb says. “I’m comfortable enough as it is. I don’t need it. Finance should be a footnote in my bio, not a central component. Why should I waste time in finance when my influence as an intellectual is so high?”

I hope someday he gets stuck in an elevator with Tom Friedman, and then after a couple hours one might realize that if there exist at least one bloviating best-seller, perhaps there exist more than one.

Elsewhere in the article someone notes that Universa’s clients lost about 4 percent in both 2009 and 2010. I'm skeptical that represents his average investor loss, as opposed to some cherry-picked account, and I'll write a check for $1000 to a charity of Taleb/Spitznagel's choice if that's true (just send the audited consolidated returns for Universa). Allowing random people to spout data like that allows funds to intimate performance without taking responsibility for such statements, highlighting another regulation that is worse than nothing (by law hedge funds aren't allowed to mention their record in general media, but if you say something and they don't comment, who's to say?).

English Fun Facts

A psycholinguist wrote a book on language, and this was funny:

Mr. Pennebaker shows, for example, that someone is more likely to be lying if he says "Let me state clearly and without qualification" and more likely to be giving an opinion if he says: "There is absolutely no doubt that . . . ."

Another linguist comments on English, and argues

The advantage of the huge vocabulary of English, of course, is that it makes English a superb literary and scientific language, able to express fine and precise shades of meaning far more easily than other tongues. This is no small part of the reason English has become the near universal language of science. It also makes English more efficient. The English version of a lengthy text is always substantially shorter than versions in other languages.

English's verbs are simpler than, say, French and German, and nouns don't have gender. English isn't perfect, but it could be worse.

IS-LM Is Ignored for a Reason

Lots of talk by Tyler Cowen and Scott Sumner arguing against the IS-LM framework, and Brad DeLong and Paul Krugman defending it. I remember how important it was as an ungraduate, and then when I was a TA for undergrads at Northwestern, found it odd that macro emphasized this framework that was totally ignored in graduate school.

The IS-LM framework was an intellectual dead end. It started with all sorts of optimism about how it could generate useful predictions and guidance on how to steer the economy, but basically deflected focus from the little things that make an economy work: property rights, good incentives. When the economy underperformed, the answer was always more goverment spending. When the economy was working well, they presumed it would keep on working no matter what, so we increased all sorts of social programs that hurt families and created an ever-larger patronage portion of the economy.

Then, the 70's. Empirically we had stagflation, which shouldn't happen. The model was internally inconsistent as the Lucas Critique showed the IS-LM implied the modeler knew about different relationships than the economic agents in the models, which is always attractive to those in the vanguard (thus, the popularity of Behavioral economics, based on correcting the biases of others). When Chris Sims showed that an atheoretical, simple, vector autoregression outperformed the fancy macro models built upon IS-LM logic, the ghost was up. No one wrote dissertations extending the IS-LM framework anymore. When I was in grad school it simply was never discussed except when working on undergraduate expositions.

Here's Krugman describing his situation having to teach graduate macro a few years ago:

This spring I have a new assignment: to teach Macroeconomics I for graduate students. Ordinarily this course is taught by someone who specializes in macroeconomics; and whatever topics my popular writings may cover, my professional specialties are international trade and finance, not general macroeconomic theory. However, MIT has a temporary staffing problem, which is itself revealing of the current state of macro, and I have been called in to fill the gap.

Here's the problem: Macro I is a quarter course, which is supposed to cover the "workhorse" models of the field - the standard approaches that everyone is supposed to know, the models that underlie discussion at, say, the Fed, Treasury, and the IMF. In particular, it is supposed to provide an overview of such items as the IS-LM model of monetary and fiscal policy, the AS-AD approach to short-run versus long-run analysis, and so on. By the standards of modern macro theory, this is crude and simplistic stuff, so you might think that any trained macroeconomist could teach it. But it turns out that that isn't true.

You see, younger macroeconomists - say, those under 40 or so - by and large don't know this stuff. Their teachers regarded such constructs as the IS-LM model as too ad hoc, too simplistic, even to be worth teaching - after all, they could not serve as the basis for a dissertation. Now our younger macro people are certainly very smart, and could learn the material in order to teach it - but they would find it strange, even repugnant.

So, he admits 1) he knows as much about macro as a cardiologist knows about cancer, and 2) no younger economists care to know about the IS-LM model. Of course his conclusion is that this is a travesty, not the more reasonable inference that his prejudices have probably led him to like the IS-LM model more than warranted.

Here's a tip. When a new paradigm is introduced, and it generates many honors, books, and large-scale-collaberative models, and then after 40 years is found uninteresting by young graduate students who don't have a dog in the fight, this is a sign it has been a good-faith mistake. Best to move on. All the IS-LM model predicts is that with massive fiscal or monetary stimulus there will be a short run effect, but you don't need the IS-LM for that (eg, WW3 will increase output). And like any short run stimulus, that shouldn't be the focus of economists, any more than a psychologist should recommend drinking beer to get over your problems (you'll feel better in an hour!).

LVOL vs. SPLV

There are two low vol ETFs out there, and there's one main difference. LVOL is Russell-Axioma US Large Cap Low Volatility Index, and is drawn from the Russell 1000. SPLV is the PowerShares S&P500 Low Volatility Fund, and is drawn from the S&P. Thus, SPLV is more large cap, LVOL more small cap.

If we look at the time series since they both have been available (7/1/11), we see the SPLV has done much better than the LVOL, just as the S&P500 did better than the Russell 1000 over this period.



Looking at my own indices, I too see that my US Minimum Variance Portfolio drawn from the S&P500 has outperformed my Beta 0.5 portfolio that is drawn from the Russell 1000, again primarily reflecting the higher cap bias on the MVP portfolio.


This highlights that there are many factors and these often explain short-term performance independent of any alpha. I think size is something to account for, so it's very important to know your benchmark, whether it is large cap or small cap, when implementing a low volatility strategy.

Envy Solves The Allais Paradox

Maurice Allais won the Nobel prize for stuff that is never really read anymore, but his curious Allais paradox has endured because it's both simple and baffling.

It arises when comparing participants' choices in two different experiments, each of which consists of a choice between two gambles, A and B. The payoffs for each gamble in each experiment are as follows:

Experiment 1				Experiment 2
Gamble 1A		Gamble 1B		Gamble 2A		Gamble 2B
Winnings	Chance	Winnings	Chance	Winnings	Chance	Winnings	Chance
$1 million	100%	$1 million	89%	Nothing	89%	Nothing	90%
		Nothing	1%	$1 million	11%
		$5 million	10%			$5 million	10%

Several studies involving hypothetical and small monetary payoffs, and recently involving health outcomes, have supported the assertion that when presented with a choice between 1A and 1B, most people would choose 1A. Likewise, when presented with a choice between 2A and 2B, most people would choose 2B. Personally, I would make those choices too, and haven't met anyone who wouldn't.

This is inconsistent with expected utility theory. According to expected utility theory, the person should choose either (1A and 2A) or (1B and 2B).

The problem comes from basic utility theory, because if you plug in a utility function like

U(x)=-exp(-aW) or W^(1-a)/(1-a)

Where W is your wealth and 'a' is your relative risk aversion coefficient, it never works; that is, they can't generate the preferences for 1A and 2B. The Wikipedia page on this outlines the simple proof, which is irrefutable. Something is wrong, and there have been several solutions, all ad hoc. For example, Kahneman and Tversky's Prospect theory allows one to weight outcomes arbitrarily, and so can accomodate this, but the weightings that solve one paradox imply nonsensical other outcomes, such as the simultaneous desire to prefer gambling and insurance, which was the initial motivation for prospect theory (see here).

Allais highlighted that the problem was probably with the independence axiom of von Neumann-Morgenstern utility functions, which basically is the one that implies we don't care about our peers, just our own wealth. For fun, I tried applying a relative utility function to the gambles in the Allais paradox (back to the envy meme). The key is that decision makers imagine the gamble in a world where their neighbor is presented with the same option, so you have to imagine them having been given this absurdly generous gamble as well, and contemplating the relative squalor or richness in the various states. Basically, applying U(x/y), where y is your neighbor's wealth (who is offered the same gamble), as opposed to U(x), where your utility is independent of your neighbor.

If you assume you and your neighbor start with $100k in wealth, then at a certain level of risk aversion (>3.02), with exponential utility, your preferences are for 1A and 2B! This applies to either averaging the two states, or a 'maximin' approach that maximizes the minimum utility among all the states. At really low risk aversion, you prefer the higher expected value choice 'B' in both gambles, and with sufficiently large risk aversion you prefer choice 'A' in both gambles.

It's not really important what the precise numbers are, but it's useful to understand this paradox has a solution within relative utility that is not as ad hoc as prospect theory. Exponential utility is very common because the expected utility for normally distributed wealth has a closed form solution, and this is very convenient, an innocuous simplification for exposition in many applications. However, as it implies 'constant absolute risk aversion', where everyone treats $1 of wealth variance the same, this is not desirable, because then the rich and poor would allocate the same dollar amount to risky assets, which we don't find realistic. Thus, most researchers like to use 'constant relative risk aversion utility functions' like x^(1-a)/(1-a), and there the trick does not work--same paradox as before.

So, it's not as if relative utility neatly provides an insanely robust solution to a prominent game-theoretic paradox, but it does provide a reasonable solution. The exponential utility function is pretty common, and I suspect this result holds across many other specifications. Further, it highlights Maurice Allais's initial intuition was correct, that the wrong assumption was that utility is independent of what others have.

You can download my Excel sheet with the example worked out here.

Learning to Accept Envy

Economists are pretty comfortable with simple self-interest, where individuals maximize their own wealth. It's part of what makes them flint-eyed realists as opposed to naive social philosophers who think the world can be made better by convincing men to be selfless. That is, after being beaten up by utopians who envisaged a society ruled by thinking about society instead of themselves, most now see how selfishness is consistent with a growing economy (the invisible hand, Adam Smith), being nice (reciprocal altruism, see Robert Axelrod or Robert Trivers), and is an efficient way to incent people with relevant information to get them to do the right thing (Friedrich Hayek's work). Just consider that ants, who sacrifice themselves without pause for the group and work tirelessly for the tribe, are also genocidal maniacs. Our selfishness, paradoxically, makes us wealthy and nice.

Unfortunately, after having reconciled with greed, envy seems still outside acceptable behavior. Envy is one of the Seven Deadly Sins, and is rather prominent in the Ten Commandments (coveting neighbor's goods, God's envy of other gods). So, compared to simple greed, it has a similar pedigree, even if we think it worse than greed.

Several econ bloggers commented on Brad DeLong's remark that the rich gain utility from their relative consumption, and so the optimality of more progressive taxation. Alex Tabarrok remarked that we should not encourage envy by the lower-income people; Greg Mankiw sees envy as economically destructive, and arbitrary (stopping at our borders); Megan McArdle sees inequality in much more than income, which leads to absurdities if we tried to apply this to looks. All seem pretty intent on keeping envy out of their assumptions about human behavior, a vice more like pettiness than greed.

It's hard to avoid envy when a colleague gets a great new job, but that's not society's problem, just mine. Luck is a big part of life, and it's actually not pretty to envisage a world where payoffs are not so random. Consider that in competitive chess players have much less random outcomes than in other sports, and they are rather depressive bunch (see Tyler Cowen on this here, and he was a good young chess player). Randomness in life allows us all a little excessive optimism, and such optimism makes us happier and more successful.

Rober Frank's book on Social Darwinism, reviewed here in Slate, argues that because of conspicuous consumption driven by attempts to increase our relative status, we engage in lots of wasteful consumption analogous to elks with large antlers: we'd all be better off with smaller antlers (houses), but individually we all benefit from larger antlers (houses). He then thinks, why not tax consumption progressively, to the benefit of all? No fancy watches, cars, and grills, for anyone, will benefit everyone.

It's heartening to see so many taking up the envy paradigm--even if to say it's all wrong--because as I've argued, if we are primarily envious as opposed to greedy, that would explain the lack of a risk premium. I'm also OK with envy, in that we just started trying to figure out its implications, and it may turn out to be as innocuous, even beneficial, as with greed. For example, envy allows us to empathize with others who still don't need our money to survive, which describes virtually all of the poor in America; it's nice that we are charitable towards the poor today even though they are wealthy beyond anyone's dreams prior to the 20th century. As envy is rather hard-wired it would be odd if it were completely dysfunctional to our species, and so I suspect it is essential in moderate doses because every instinct we have has some base benefit (greed, lust, pride). In any case, it can still be important even if it makes us all worse off.

As to discouraging antler growth, the size of elephant seals, or Patek Phillipe watches, this seems to ignore the fact that almost all of the amenities of modern life are unanticipated benefits from someone who was probably partially driven by his desire to have the best car among his social circle. The great technology, art, and philosophy we enjoy is a by-product of selfish, and envious, individuals. Were we to prevent conspicuous consumption, how much less would we have? That's a hypothetical, but consider that many technologies started as baubles for the idle rich, and then became extremely useful for more mundane uses (no one anticipated computers or cars becoming essential household products).

Envy is ubiquitous, one of the Human Universals found in every culture at every time. It's not a societal problem, but a personal one, one that deserves moderation like so many of our instincts. Economists would do well to start taking seriously the implications of envy over greed, its effects show up in all sorts of unexpected, important places (eg, asset pricing theory).

Low Vol Investing in The News

See Barron's here, and WSJ here. I'm mentioned in both articles, so obviously they got their facts straight.

As Eddy Elfenbein noted, this was probably all instigated by his post last week on the subject.