Europe's deepest problem is bad ideas. Unpleasant price movements represent "illiquidity," "speculators," "market manipulation," "lack of confidence" and "contagion," not the hard reality of looming default. The point of policy is to "calm markets" and "provide confidence"—not to solve financial problems.
...
The worst idea of all is that Europe's admirable economic free trade zone and currency union cannot survive a sovereign default. It is precisely allowing sovereign default, and isolating the central bank from sovereign default, that is the only way to keep the union together. That is, after all, how the euro was set up in the first place. It's almost too late. But not quite.
Wednesday, September 28, 2011
Letting Greece Go
John Cochrane makes a good point about Greece: if you don't let it default within the Euro framework, the Euro is doomed.
Tuesday, September 27, 2011
Another Reason to Worry
Over at the AEI, Andrew Biggs asks an important question:
The answer, of course, is that that period had a reduction in rates from 10% to 3%. The raised the sample return to an average bond portfolio by about 3% annually. If long term interest rates went to zero, the benefit would only be about 2.1% annually. Most likely, rates will rise, because that is what the Fed wants them to do! Thus, instead of a 3% tailwind, there will be something like a 1-2% wind in our faces over the next 25 years.
I hope there are lots of Doug Edwards's out their, eager to pay more taxes.
Public pensions report that over the 25-year period from 1985 through 2011 they have achieved a median investment return of 8.8 percent, exceeding the 8 percent returns they project for the future, and have earned these returns without taking undue risks. Given this, they say, why shouldn’t we assume they can keep on doing so into the future?
The answer, of course, is that that period had a reduction in rates from 10% to 3%. The raised the sample return to an average bond portfolio by about 3% annually. If long term interest rates went to zero, the benefit would only be about 2.1% annually. Most likely, rates will rise, because that is what the Fed wants them to do! Thus, instead of a 3% tailwind, there will be something like a 1-2% wind in our faces over the next 25 years.
I hope there are lots of Doug Edwards's out their, eager to pay more taxes.
Why Ambiguity Aversion is Rational
Kierkegaard noted that 'Life is to be understood backwards, but it is lived forwards,' which is kind of sad--as is much existentialism--because it emphasizes how much time we spend on things we can't affect. Leave it to the government to make this an economic policy.
The SEC gave a Wells notice to S&P for their dealings with a 2007 AAA rated CDO that subsequently went into junk status. The smoking gun is that while the deal was done with an assumed collateral issue that would be investment grade, by early 2007 the market was already tanking, and the issuer had subprime collateral. An email documents S&P was aware of this.
This was a mistake, one that was probably made many times previously but they got away with it because AAA securities tend to have multiple levels of redundancy, belts and suspenders. Securitization became very complicated over the years, with many different tranches and waterfalls, and alas any explicit, complicated process invites its circumvention, so issuers and borrowers eventually figured out the mortgage-CDO game and pushed weaker and weaker collateral into them until they finally imploded. Those screaming warnings while it was happening were ignored (Stan Liebowitz), those who said these effects were innocuous, even morally righteous, were rewarded (eg, Richard Syron, Alicia Munnell). When this house of cards collapsed, everyone points to those with the deepest pockets, though no one seems to be going after Jamie Gorelick.
This was probably the last big mortgage deal to go through as if things were business as usual. As Bernanke noted, the mortgage market shut down in mid 2007 because issuers could not get the ratings needed. Market players make mistakes, but at least they stopped their idiocy 4 years ago, unlike our government, which even today issues mortgages with 3.5% down though private lenders are back to demanding 20% down.
This case highlights the importance of ambiguity aversion, as opposed to risk aversion. If a bad outcome results from a prospect about which an agent had, with the benefit of hindsight, made a mistake, he looks not just unlucky, but incompetent or malicious. In experiments, a lottery ticket is worth a lot less after the drawing for most people even if they don't know what the true number is, and seemingly the seller does not either. People shy away from processes about which they think they have insufficient, as opposed to probabilistic, information, even if framed identically (eg, both with a 50% chance). This is ambiguity aversion.
A bad outcome resulting from a pure risky prospect, on the other hand, cannot be attributed to poor judgment. If all possible information about a risky prospect was known, failure can only be bad luck. The key is, ex post, can you look like a sucker or just unlucky? Investment managers can live with bad luck, but their reputation is essential and they can't be seen a fool.
This aversion to 'incomplete information' games is related to, but different from, classical risk aversion, and probably explains why lenders are now so afraid to lend: if they make a mistake now, it won't be merely a bad investment, but a crime. Life is a lot more like a game of incomplete information than a roulette wheel.
AAA ratings on securities that subsequently suffered generated big losses to investors, the people who ultimately should be monitoring the credit agencies. Their incentives are already aligned. The rating agencies themselves have suffered credibility shocks for this, and so now we have DBRS and Kroll jumping into the previously unpenetrable field. Jumping onto the battlefield and court-marshalling the wounded is a poor tactic for improving morale or future performance, rather, it will just encourage all sorts of tentative, butt-covering behavior that precludes the dynamism a growing economy needs.
The SEC gave a Wells notice to S&P for their dealings with a 2007 AAA rated CDO that subsequently went into junk status. The smoking gun is that while the deal was done with an assumed collateral issue that would be investment grade, by early 2007 the market was already tanking, and the issuer had subprime collateral. An email documents S&P was aware of this.
This was a mistake, one that was probably made many times previously but they got away with it because AAA securities tend to have multiple levels of redundancy, belts and suspenders. Securitization became very complicated over the years, with many different tranches and waterfalls, and alas any explicit, complicated process invites its circumvention, so issuers and borrowers eventually figured out the mortgage-CDO game and pushed weaker and weaker collateral into them until they finally imploded. Those screaming warnings while it was happening were ignored (Stan Liebowitz), those who said these effects were innocuous, even morally righteous, were rewarded (eg, Richard Syron, Alicia Munnell). When this house of cards collapsed, everyone points to those with the deepest pockets, though no one seems to be going after Jamie Gorelick.
This was probably the last big mortgage deal to go through as if things were business as usual. As Bernanke noted, the mortgage market shut down in mid 2007 because issuers could not get the ratings needed. Market players make mistakes, but at least they stopped their idiocy 4 years ago, unlike our government, which even today issues mortgages with 3.5% down though private lenders are back to demanding 20% down.
This case highlights the importance of ambiguity aversion, as opposed to risk aversion. If a bad outcome results from a prospect about which an agent had, with the benefit of hindsight, made a mistake, he looks not just unlucky, but incompetent or malicious. In experiments, a lottery ticket is worth a lot less after the drawing for most people even if they don't know what the true number is, and seemingly the seller does not either. People shy away from processes about which they think they have insufficient, as opposed to probabilistic, information, even if framed identically (eg, both with a 50% chance). This is ambiguity aversion.
A bad outcome resulting from a pure risky prospect, on the other hand, cannot be attributed to poor judgment. If all possible information about a risky prospect was known, failure can only be bad luck. The key is, ex post, can you look like a sucker or just unlucky? Investment managers can live with bad luck, but their reputation is essential and they can't be seen a fool.
This aversion to 'incomplete information' games is related to, but different from, classical risk aversion, and probably explains why lenders are now so afraid to lend: if they make a mistake now, it won't be merely a bad investment, but a crime. Life is a lot more like a game of incomplete information than a roulette wheel.
AAA ratings on securities that subsequently suffered generated big losses to investors, the people who ultimately should be monitoring the credit agencies. Their incentives are already aligned. The rating agencies themselves have suffered credibility shocks for this, and so now we have DBRS and Kroll jumping into the previously unpenetrable field. Jumping onto the battlefield and court-marshalling the wounded is a poor tactic for improving morale or future performance, rather, it will just encourage all sorts of tentative, butt-covering behavior that precludes the dynamism a growing economy needs.
Sunday, September 25, 2011
Risk-Return Duality
If the standard asset pricing model is correct, we estimate expected returns from risk premiums and their factor loadings (eg, beta*equity return premium), and we can infer the risk loadings and risk premiums from an expected return. Given we don't observe expected returns, but assume that with large samples, average returns estimate expected returns, this is why the small cap risk factor is supposed to exist, because it tautologically explains the higher return to small cap stocks over large cap stocks. In this way there should be a risk-return duality from expected return to risk.
There has been a long tradition in Western thought of trying to develop a set of beliefs that are objectively true and rational. This usually involved some basic assumptions and then logic, as in dialectical materialism, or Russell and Whitehead's Principia Mathematica. It is very comforting to think that important beliefs are can be rationally justified, in contrast to beliefs based on faith or aesthetic preferences. When finance created asset pricing theory in the 50's and 60's, this kind of rational reductionism was dominant, and it seemed obvious that applying the logic would render previously intractable, qualitative problems into unambiguous solutions within linear programming or dynamic programming. Expected returns in this framework have a rational, objective grounding, a la Logical Positivism. Alas, out investment beliefs is just like our other beliefs, and it is futile to try and make them apodictic.
ProShares has revolutionized trading with their plethora of levered funds that provide 2 times the daily return of some target index, such as the SSO ETF which replicates a strategy that generates 200% return of the S&P500 index over a single day. These ETFs are very popular, and obviously have the precise doubling or tripling of the covariance as the targeted index. Yet, due to trading costs and compounding, the returns over longer periods are significantly lower than 2 times the return on the index. Of the 24 ETFs that promise a 200% daily return of the index, where the index has risen since the end of 2009 through August 2011, the average Ultra ETF has returned about 10% less than 2 times the index. If returns are a function of covariances, investors are being shortchanged here, and the ETF should trade at a discount to net asset value, but they don't.
Imagine a world where expected returns are solely a function of covariances, as standard theory implies. Then if you create assets with specific covariances, the market should give them specific expected returns. Everything should be consistent. People should expect risk and return to be positively correlated.
Instead, Sharpe and Amromin find that people expect volatility and returns to be inversely correlated: when they are bullish they expect low volatility, and when they are bearish they expect high volatility. This is counter to standard theory, where basically expected equity returns should be a linear function of market variance. Given the inverse correlation between returns and volatilities, where increases in stock prices correspond to decreases in implied volatilities and vice versa, this makes sense. People are clearly assuming a specific return, and then deriving the volatility consistent with that scenario.
For buyers this means they expect volatility to decrease as the price rises, as it does in practice (and is implicit in the volatility skew in equity options). It is not possible to expect a really large expected return without assuming a large amount of risk, merely because it necessarily follows that if you expect, say, a 20% return on an asset, it must be capable of generating a fluctuation that high, which unfortunately also implies it could fall by 20%. The conditional volatility on an asset where a relatively large return is significantly probable must be larger than for an asset where a relatively large return is less common. Expected returns are a function of expected volatility (higher volatility assets have higher conceivable returns), but they are collectively wrong, which is why future returns are decreasing as a function of volatility.
Investors understand that stocks prices fluctuate randomly, but just as 'no conqueror believes in chance,' no active investor believes in chance either when they take risk. People are thinking about the collapse of the wave function, as opposed to the wave, because it’s more common for investors to think about outcomes as opposed to probability distributions. They understand they can be wrong, and experience much anxiety about their investments, but that's different than thinking that expected returns are random, and very few investors base their expected return on risk factors and their loadings, as opposed to some specific outcome.
There is a duality, but it involves two sets of expected returns. If people invest based on the delusion that their expected returns are single outcomes, they are constantly evaluating value. Many investors are making this work, investing by applying some discounted cash flow logic. They are sufficiently right that a stock price is a decent estimate of its future profitability, but sufficiently wrong so that the stocks with the greatest expected variances, which necessarily include those stocks with the greatest expected returns among its investors, tend to be most 'over-bought', and thus have the lowest returns. Expected returns, derived from a model that empirically estimates expected returns from historical returns, as opposed to canvassing investor opinion, are negatively related to risk. Low volatility investing is truly outside-the-box, an expectation that comes from noting the emergent pattern caused by investor beliefs, which contain a systematic bias.
There has been a long tradition in Western thought of trying to develop a set of beliefs that are objectively true and rational. This usually involved some basic assumptions and then logic, as in dialectical materialism, or Russell and Whitehead's Principia Mathematica. It is very comforting to think that important beliefs are can be rationally justified, in contrast to beliefs based on faith or aesthetic preferences. When finance created asset pricing theory in the 50's and 60's, this kind of rational reductionism was dominant, and it seemed obvious that applying the logic would render previously intractable, qualitative problems into unambiguous solutions within linear programming or dynamic programming. Expected returns in this framework have a rational, objective grounding, a la Logical Positivism. Alas, out investment beliefs is just like our other beliefs, and it is futile to try and make them apodictic.
ProShares has revolutionized trading with their plethora of levered funds that provide 2 times the daily return of some target index, such as the SSO ETF which replicates a strategy that generates 200% return of the S&P500 index over a single day. These ETFs are very popular, and obviously have the precise doubling or tripling of the covariance as the targeted index. Yet, due to trading costs and compounding, the returns over longer periods are significantly lower than 2 times the return on the index. Of the 24 ETFs that promise a 200% daily return of the index, where the index has risen since the end of 2009 through August 2011, the average Ultra ETF has returned about 10% less than 2 times the index. If returns are a function of covariances, investors are being shortchanged here, and the ETF should trade at a discount to net asset value, but they don't.
Imagine a world where expected returns are solely a function of covariances, as standard theory implies. Then if you create assets with specific covariances, the market should give them specific expected returns. Everything should be consistent. People should expect risk and return to be positively correlated.
Instead, Sharpe and Amromin find that people expect volatility and returns to be inversely correlated: when they are bullish they expect low volatility, and when they are bearish they expect high volatility. This is counter to standard theory, where basically expected equity returns should be a linear function of market variance. Given the inverse correlation between returns and volatilities, where increases in stock prices correspond to decreases in implied volatilities and vice versa, this makes sense. People are clearly assuming a specific return, and then deriving the volatility consistent with that scenario.
For buyers this means they expect volatility to decrease as the price rises, as it does in practice (and is implicit in the volatility skew in equity options). It is not possible to expect a really large expected return without assuming a large amount of risk, merely because it necessarily follows that if you expect, say, a 20% return on an asset, it must be capable of generating a fluctuation that high, which unfortunately also implies it could fall by 20%. The conditional volatility on an asset where a relatively large return is significantly probable must be larger than for an asset where a relatively large return is less common. Expected returns are a function of expected volatility (higher volatility assets have higher conceivable returns), but they are collectively wrong, which is why future returns are decreasing as a function of volatility.
Investors understand that stocks prices fluctuate randomly, but just as 'no conqueror believes in chance,' no active investor believes in chance either when they take risk. People are thinking about the collapse of the wave function, as opposed to the wave, because it’s more common for investors to think about outcomes as opposed to probability distributions. They understand they can be wrong, and experience much anxiety about their investments, but that's different than thinking that expected returns are random, and very few investors base their expected return on risk factors and their loadings, as opposed to some specific outcome.
There is a duality, but it involves two sets of expected returns. If people invest based on the delusion that their expected returns are single outcomes, they are constantly evaluating value. Many investors are making this work, investing by applying some discounted cash flow logic. They are sufficiently right that a stock price is a decent estimate of its future profitability, but sufficiently wrong so that the stocks with the greatest expected variances, which necessarily include those stocks with the greatest expected returns among its investors, tend to be most 'over-bought', and thus have the lowest returns. Expected returns, derived from a model that empirically estimates expected returns from historical returns, as opposed to canvassing investor opinion, are negatively related to risk. Low volatility investing is truly outside-the-box, an expectation that comes from noting the emergent pattern caused by investor beliefs, which contain a systematic bias.
Thursday, September 22, 2011
UBS Staffed by Idiots
Perhaps the aristocratic heritage of Swiss banking has generated their version of Charles II of Spain. That's the poor, misshapen sap to the right with only 2 great-great-great-great grandparents, a family tree that converges.
I wrote a rather fawning post complimenting UBS on their candor and perception when the wrote up their 2008 debacle. They seemed to have identified key errors in judgment, and were refreshingly detailed in the origin of their write-down (I never saw anything similar among US banks). Everyone slips up now and then, and so I figured that was a sign of a healthy organization that merely made a singular mistake.
However, 2 strikes and you are out. Reading snippets about their $2B loss via some low-level trader makes me think the bank is thoroughly incompetent. This 'Delta One' desk had a $7B rogue trader loss only a couple years ago, so they should have been keenly aware of the potential risks (this was at Soc Gen--the businesses have the same Delta One name for some reason). To generate that kind of loss implies several levels of fail within risk management, the trading desk itself, and the back office. It's easy to think a couple people screwed up, but this must have involved at least a dozen important people who apparently got paid to surf the web all day.
When I worked for a large bank there were many senior executives who were good at playing the game, but ultimately ignorant of how banks made money. These include those who were good at glad-handling the various political bodies that were essential to many of our strategic efforts, such as what businesses we could enter, and keeping competitors out under the pretext of protecting the consumer. Unfortunately, as $115MM Citigroup executive Bob Rubin showed, such skill doesn't translate in an ability or even interest in nitty gritty issues like what's on the balance sheet. A smart banker avoids positions unrelated to the core business of originating and distributing loans and deposits and other financial instruments. For example, it does not make sense to trade corn futures if you have no business with futures exchanges or corn growers.
I used to think the Swiss financial types were smart, with their solid currency and all. Perhaps they merely avoided both World Wars, which could have been due to savvy strategy, but also chance. They seem to have good general competence (thus the nice mea culpa on their 2008 write-down), but are too aloof or naive for the realities of modern banking. They should stick to chocolate.
Wednesday, September 21, 2011
Credit Suisse Arb Index Fishy
Credit Suisse has an 'Arbitrage US Index' (CSIARBUS Index), that presumably reflects the return on 10 stat arb strategies. The total return since inception in Jan 2002 is above. It's a Sharpe of about 2.4, Madoff-like. If it's real, everyone should put most of their money in such strategies asap.
I'm rather skeptical of such indices. Where's the infamous August 2007 draw down? The index was first made available on Bloomberg in February 2011, and just this August this index had its worst draw-down ever. I have a feeling it is filled with innumerable back-fill biases, a typical naive backtest quants present all the time, oblivious to their selection biases. I looked on the internet for some kind of description, and found nothing.
The world doesn't need more institutions presenting implausible returns. It sure doesn't help their credibility.
Tuesday, September 20, 2011
Keynesian Anecdote
From Ron Suskin's book on Obama:
The focus on jobs irrespective of whether they pass a cost-benefit test, highlights the worldview of Keynesians, where spending on anything when unemployment is high, is a good thing via the magic of the multiplier. Further, spending $100k per job is good because it's a million jobs. One wonders if there's a price at which it would not be attractive.
By the estimates of [Christina Romer's] Council of Economic Advisers, at a cost of $100,000 per job, $100 billion would mean one million new jobs. "A million people is a lot of people."
Obama was unenthusiastic. Romer, in meeting after meeting, came back with new plans, new ways either to locate $100 billion or pitch it to Congress. Her appeals were passionate. She said they were falling into a "The perfect is the enemy of the good" trap. It's about doing something, anything."
The focus on jobs irrespective of whether they pass a cost-benefit test, highlights the worldview of Keynesians, where spending on anything when unemployment is high, is a good thing via the magic of the multiplier. Further, spending $100k per job is good because it's a million jobs. One wonders if there's a price at which it would not be attractive.
Monday, September 19, 2011
Obama to Lower Interest Expense by $430B?
Sunday, September 18, 2011
Is Low Vol Investing a Value Play?
Dimensional Fund Advisors, the embodiment of conventional wisdom for rational academics, has a paper out--Understanding Low Volatility Strategies: Minimum Variance, by Ronnie R. Shah--arguing that low volatility funds are basically value and industry plays in disguise (I can't find it on the web, so I won't post it, but it seems like a standard white paper for public consumption). It's really a spin on Berd Scherer's white paper from last year, inspired by Dan DiBartolomeo's 2007 PowerPoint, that the value stocks are driving low volatility's seeming alpha. Both of these papers devolve into convoluted arguments certain to rationalize the CAPM framework, but instead are just squid ink. DiBartolomeo states that the value premium is primarily just a return to negative skew, which investors dislike and thus demand a premium.
The skew explanation for anomalies is plausible at 30,000 feet, but find this line of reasoning rather unserious, as when Nassim Taleb pals around with Danny Kahneman, one arguing that we are primarily prefer positive skew (Kahneman), the other negative skew (Taleb), and they happily consider themselves brothers in arms. It's like anarchists and fascists united against the status quo, which would excusable if they were not also happily convinced they are more alike than different.
The negative skew premium may exist, but then one would have to then explain why equities are generally thought to have higher returns than corporate bonds, even though clearly bonds have much greater negative skew than equities. And just look at the histogram of monthly returns for the market, size and value factors (from Ken French's website). I don't see how value is considered to have negative skew.
Lastly, Post and van Vliet (2006) showed that if you actually look at utility functions where investors care about variance AND skew, the maximum skew premium is a fraction of the 'variance premium', about one-fifth as large. This is because investors still must be globally risk averse, and since skew and variance are positively correlated, there are limits on how large the skew aversion can be relative to the variance aversion.
Scherer notes that if you construct a minimum variance portfolio a certain way, and regress it against the 3 Fama-French factors (market, size, and value), as well as long-short portfolios formed on betas and residual variance, much of the MVP's performance is 'explained'. Now, given MVPs load up on low beta and low residual risk stocks, it's obvious that a long-short portfolio formed on CAPM betas and residual variances would explain the MVP return relative to the broader index, but that's really not interesting. It's a bit like saying the book/market effect explains the price/earnings effect.
The DFA's Ronnie Shah, meanwhile, is much clearer, but makes the same point. He notes that the return premium to value and the market is about 4% for both. As the market beta on his MVP portfolio is about 0.75, and his beta on value is about 0.25, it seems like a swap of market exposure for value exposure.
It could be, but I'm skeptical for two reasons. First, as Daniel and Titman 1997 noted, the return to 'value' is more a function of it's characteristic, low book/market, than its 'factor loading', which in the case of value is merely a loading on itself. Houge and Loughran found that mutual funds with high value loading, independent of whether or not it was a 'value fund', had no explanatory power. The value risk factor is really just the value anomaly rebranded as a risk factor, because it isn't obviously 'risky' in any sense. Originally it was thought value was related to financial distress, but then when we look at distress directly, such as using agency ratings or metrics of default based on income statements and balance sheets, distressed firms actually have lower-than-average returns. So I'm skeptical value is anything but a characteristic-based anomaly, not a 'risk factor'.
Secondly, when I look at the Minimum Variance and Low Beta portfolios I have created, I do not see a consistent value loading. Looking at the MVP, which I have data from 1998 to 2011, it estimates value beta of 0.34 using monthly data. Using daily data from July 2000 through July 2011, the value beta is 0.24. These are around what Shah gets. Yet it floats around like an incidental symptom, not something fundamental. Here's the data for my MVP and Beta 0.5 portfolios using daily data (value beta being a loading on the Fama-French HML value factor proxy):
Here it is using the longer monthly time series:
While on average, the value beta may be around 0.3, it doesn't seem consistent enough to be fundamental.
Now, Shah does note that low vol portfolios tend to have a lot of utility loading, and little technology. True. But I've never seen someone argue that various industries have higher risk than others. Looking at industry relative returns, one three-year period over the prior, there is no pattern. That is, past winners do not repeat consistently, as they would if there were an industry risk premium. So, to say this is picking up the 'utility' risk premium, and avoiding the 'tech' insurance premium, does not make sense. Of course, the higher-weighted utility industry has much lower volatility than the lower weighted tech industry, and so if there was a risk story here, it would take some special pleading.
Dimensional's reluctance to embrace low volatility investing is good news to low volatility investors. As long as people generally keep doing what they have done, the opportunity remains to simply improve one's index returns by focusing on the low volatility subset of stocks, lowering volatility and increasing the return. It's the easiest, large-scale way to better institutional returns since the invention of the index fund.
The skew explanation for anomalies is plausible at 30,000 feet, but find this line of reasoning rather unserious, as when Nassim Taleb pals around with Danny Kahneman, one arguing that we are primarily prefer positive skew (Kahneman), the other negative skew (Taleb), and they happily consider themselves brothers in arms. It's like anarchists and fascists united against the status quo, which would excusable if they were not also happily convinced they are more alike than different.
The negative skew premium may exist, but then one would have to then explain why equities are generally thought to have higher returns than corporate bonds, even though clearly bonds have much greater negative skew than equities. And just look at the histogram of monthly returns for the market, size and value factors (from Ken French's website). I don't see how value is considered to have negative skew.
Lastly, Post and van Vliet (2006) showed that if you actually look at utility functions where investors care about variance AND skew, the maximum skew premium is a fraction of the 'variance premium', about one-fifth as large. This is because investors still must be globally risk averse, and since skew and variance are positively correlated, there are limits on how large the skew aversion can be relative to the variance aversion.
Scherer notes that if you construct a minimum variance portfolio a certain way, and regress it against the 3 Fama-French factors (market, size, and value), as well as long-short portfolios formed on betas and residual variance, much of the MVP's performance is 'explained'. Now, given MVPs load up on low beta and low residual risk stocks, it's obvious that a long-short portfolio formed on CAPM betas and residual variances would explain the MVP return relative to the broader index, but that's really not interesting. It's a bit like saying the book/market effect explains the price/earnings effect.
The DFA's Ronnie Shah, meanwhile, is much clearer, but makes the same point. He notes that the return premium to value and the market is about 4% for both. As the market beta on his MVP portfolio is about 0.75, and his beta on value is about 0.25, it seems like a swap of market exposure for value exposure.
It could be, but I'm skeptical for two reasons. First, as Daniel and Titman 1997 noted, the return to 'value' is more a function of it's characteristic, low book/market, than its 'factor loading', which in the case of value is merely a loading on itself. Houge and Loughran found that mutual funds with high value loading, independent of whether or not it was a 'value fund', had no explanatory power. The value risk factor is really just the value anomaly rebranded as a risk factor, because it isn't obviously 'risky' in any sense. Originally it was thought value was related to financial distress, but then when we look at distress directly, such as using agency ratings or metrics of default based on income statements and balance sheets, distressed firms actually have lower-than-average returns. So I'm skeptical value is anything but a characteristic-based anomaly, not a 'risk factor'.
Secondly, when I look at the Minimum Variance and Low Beta portfolios I have created, I do not see a consistent value loading. Looking at the MVP, which I have data from 1998 to 2011, it estimates value beta of 0.34 using monthly data. Using daily data from July 2000 through July 2011, the value beta is 0.24. These are around what Shah gets. Yet it floats around like an incidental symptom, not something fundamental. Here's the data for my MVP and Beta 0.5 portfolios using daily data (value beta being a loading on the Fama-French HML value factor proxy):
Here it is using the longer monthly time series:
While on average, the value beta may be around 0.3, it doesn't seem consistent enough to be fundamental.
Now, Shah does note that low vol portfolios tend to have a lot of utility loading, and little technology. True. But I've never seen someone argue that various industries have higher risk than others. Looking at industry relative returns, one three-year period over the prior, there is no pattern. That is, past winners do not repeat consistently, as they would if there were an industry risk premium. So, to say this is picking up the 'utility' risk premium, and avoiding the 'tech' insurance premium, does not make sense. Of course, the higher-weighted utility industry has much lower volatility than the lower weighted tech industry, and so if there was a risk story here, it would take some special pleading.
Dimensional's reluctance to embrace low volatility investing is good news to low volatility investors. As long as people generally keep doing what they have done, the opportunity remains to simply improve one's index returns by focusing on the low volatility subset of stocks, lowering volatility and increasing the return. It's the easiest, large-scale way to better institutional returns since the invention of the index fund.
Friday, September 16, 2011
The Big Lie
The KIPP education group has been trying to sell some character values to its students:
Now, if on average the poor possess an equivalent amount of most virtues--discipline, generosity, prudence, etc.--then there's a massive and subtle conspiracy of DaVinci code proportions going on. Virtues by definition make us prosperous, statistically. The idea that the poor are so insecure that they have to be told an obvious untruth to maintain their self-esteem merely creates more resentment against society, which they are told again and again is fundamentally unfair in a really subtle pervasive way. The truth, or something close to it, is necessary for finding the good, and that means telling kids they need bourgeois values. If someone points out that such values are more like 'middle class values' than 'public housing values', the kinder might actually appreciate the connection between these abstract concepts and concrete results.
What appealed to Levin about the list of character strengths that Seligman and Peterson compiled was that it was presented not as a finger-wagging guilt trip about good values and appropriate behavior but as a recipe for a successful and happy life. He was wary of the idea that KIPP’s aim was to instill in its students “middle-class values,” as though well-off kids had some depth of character that low-income students lacked. “The thing that I think is great about the character-strength approach,” he told me, “is it is fundamentally devoid of value judgment.”
Now, if on average the poor possess an equivalent amount of most virtues--discipline, generosity, prudence, etc.--then there's a massive and subtle conspiracy of DaVinci code proportions going on. Virtues by definition make us prosperous, statistically. The idea that the poor are so insecure that they have to be told an obvious untruth to maintain their self-esteem merely creates more resentment against society, which they are told again and again is fundamentally unfair in a really subtle pervasive way. The truth, or something close to it, is necessary for finding the good, and that means telling kids they need bourgeois values. If someone points out that such values are more like 'middle class values' than 'public housing values', the kinder might actually appreciate the connection between these abstract concepts and concrete results.
Wednesday, September 14, 2011
Bogle's Beginnings
John Bogle is one of the founders of index investing, a very valuable tool still underutilized by investors. Bogle writes over at the WSJ:
The idea that passive equity management could outpace active management—then the mutual fund industry's universal strategy—was derogated and ridiculed. The fund, now called the Vanguard 500 Index Fund, was referred to as "Bogle's Folly." Yet today indexing has come to dominate the field. Over the past five years, index funds have accounted for 100% of all equity funds' cash flows, with assets now totaling $2 trillion, one-fourth of all equity fund assets.
The story is a good one. In 1951, the anecdotal evidence John Bogle--a mediocre student at Princeton--assembled in his senior thesis on the then-minuscule mutual fund industry led him to write that mutual funds “can make no claim to superiority to the market averages.”
In 1975 Vanguard was a shareholder-owned mutual fund group—the company was owned by the mutual fund investors—so low-cost fund administration was not taking money from owners, it was giving money to them. In contrast, the idea of an index fund would have hardly appealed to a high-cost fund complex whose very revenue depended on the conviction that active management did add value, at least, in their particular case.
In his pitch to the Vanguard board for starting an index fund, he brought some of his own data on the performance of mutual fund managers, suggesting that they underperformed by about the same amount as their expenses, and some references to recent articles by Paul A. Samuelson and Charles Ellis. So, blessed with some good intuition from Bogle, the rising popularity of the idea in the academy, timing, and good incentives from Vanguard, they had both the opportunity and the motive to create the first retail index fund, which is now the largest index fund in the world, and Vanguard, the second-largest fund family. By the next summer, the fund was launched with about $11 million.
While Bogle seemingly had the idea right all along, it should be noted that there were several missteps among the index founding fathers. John McQuown and David Booth at Wells Fargo, and Rex Sinquefield at American National Bank in Chicago, both established the first passive Index Funds in 1973. These were portfolios targeted at institutions. The Wells Fargo fund was initially an equal-weighted fund on all the stocks on the NYSE, which, given the large number of small stocks, and the fact that a price decline meant you should buy more, and at a price increase sell more, proved to be an implementation nightmare.
It was replaced with a value-weighted index fund of the S&P500 in 1976, which eliminates this problem. Another misstep was clearly not targeting the retail investor early, which turned out to be where the real money was. Rex Sinquefeld and David Booth started Dimensional Fund Advisors in 1981, in part to address this deficiency. Sinquefeld was also hooked into the University of Chicago, which had Eugene Fama as its head of research. As the size effect was the hot thing at that time, DFA had a small cap portfolio at the outset to take advantage of this anomaly. Unfortunately, the size effect disappeared in the 1980s, but Dimensional was able to survive this setback admirably. Thus, even a great, simple idea like an index fund, has a learning curve in practice.
Even good ideas like index funds are not straightforward, and take some interested care to make work. Further, as John Bogle showed, it was not until he was the CEO of a fund complex that he could implement his idea for a retail index fund, and even then he dealt with a skeptical board, and relied heavily on authority figures like Paul Samuelson (Sinquefeld and McQuown were also well-connected). Imagine if he were a bright-eyed young kid with merely a PowerPoint presentation and his own data. It is essential to have the right connections when you have a good idea, more so the bigger the idea.
Tuesday, September 13, 2011
Why Government Spending is So Impotent
We have a proposed Southwest Light Rail Transit line, a high frequency train that would connect downtown Minneapolis to my town of Eden Prairie. funding for capital costs will come from four sources: the transit sales tax in the metro area (30 percent), the County (10 percent), the State (10 percent), and the Federal Transit Administration (up 50 percent). Every month there's a new cost added to the currently estimated $1.25 billion project.
Ridership is projected to be 24,000 to 30,000 rides per day by year 2030, which would be a large increase from the 2000 rides a day generated via the buses that run from Eden Prairie to downtown. Currently, very cushy buses with large comfortable seats carry a handful of people downtown all day on each trip. Revenue, meanwhile, is falling, reflect low demand. Riders pay an average of $2.5 per trip, even though it costs $8 to cover marginal costs. The proposed project has many stops as planners hate express routes that travel nonstop node-to-node because this just encourages riders to live outside the city! The wishful thinking is basically designed to fail, not that anyone cares because they are all spending not just someone else's money, but each agency feels like the other agencies are subsidizing them, as if it doesn't all come from taxpayers in the end.
Spending money on such boondoggles to create jobs relies on a faith in the fiscal multiplier, and the magic of spending to reduce debt. Bush II spent like a drunken sailor (wars, medicare) and this ended with a disaster even though it should have been no worse than the alien invasion expenditures suggested by Keynesian economists. It should be remembered that after independence India focused on jobs and the poor, as opposed to free trade and property rights, and they stagnated for decades. If governments could boost the economy spending on big top-down projects, countries like India would have done much better than countries that were less hands-on in their management.
Ridership is projected to be 24,000 to 30,000 rides per day by year 2030, which would be a large increase from the 2000 rides a day generated via the buses that run from Eden Prairie to downtown. Currently, very cushy buses with large comfortable seats carry a handful of people downtown all day on each trip. Revenue, meanwhile, is falling, reflect low demand. Riders pay an average of $2.5 per trip, even though it costs $8 to cover marginal costs. The proposed project has many stops as planners hate express routes that travel nonstop node-to-node because this just encourages riders to live outside the city! The wishful thinking is basically designed to fail, not that anyone cares because they are all spending not just someone else's money, but each agency feels like the other agencies are subsidizing them, as if it doesn't all come from taxpayers in the end.
Spending money on such boondoggles to create jobs relies on a faith in the fiscal multiplier, and the magic of spending to reduce debt. Bush II spent like a drunken sailor (wars, medicare) and this ended with a disaster even though it should have been no worse than the alien invasion expenditures suggested by Keynesian economists. It should be remembered that after independence India focused on jobs and the poor, as opposed to free trade and property rights, and they stagnated for decades. If governments could boost the economy spending on big top-down projects, countries like India would have done much better than countries that were less hands-on in their management.
Monday, September 12, 2011
Sunday, September 11, 2011
Stock Returns by Debt Rating
Above are annual returns for portfolios formed every July 1, based on the Senior rating of the company. I only used non-financial companies because financial companies tend to be only with investment grade, and they are very different from a debt rating perspective (when I modeled default at Moody's, there was a clear non-financial focus because financial companies are very different). The annual data are as follows for this period (Jul1975-Jun2011):
| StockReturns(%) | beta | Volatility(%) | |
| AAA | 12.4 | 0.78 | 17.1 |
| AA | 13.9 | 0.81 | 16.1 |
| A | 14.3 | 0.81 | 16.5 |
| BBB | 14.2 | 0.82 | 17.9 |
| BB | 15.0 | 1.04 | 23.4 |
| B | 8.6 | 1.43 | 32.0 |
| C | -12.7 | 1.18 | 44.9 |
It appears there's a reasonable story one could tell about returns from AAA to BB: higher returns, and higher intuitive measures of risk: beta, volatility. But for B and C rated stocks, the returns make no sense to standard asset pricing theory, because these are obviously risky stocks. I remember presenting this chart to an NBER conference around 2000, and the esteemed audience told me I was wrong; my data had to be incorrect. I was working at Moody's, so my ratings data was as good as it got. Anyway, I wrote it up and sent it to Journal of Portfolio Management, and the editor, Peter Bernstein, wrote back they weren't accepting submissions at that time. I thought that was an odd response. This avenue wasn't part of my day job, so I let it go, but I keep updating my data for fun.
The result is really corroborated by Campbell, Hilscher and Szilagyi (2005), who found distress risk to be negatively correlated with stock returns, which makes sense because volatility and leverage is inversely correlated with future returns, and cash-flow is positively correlated with future returns, so those are the main drivers of default risk.
Reality is that which, when you don't believe it, doesn't go away, so I don't really mind when people tell me I'm wrong on facts like this.
Saturday, September 10, 2011
This is not Our Day
On September 11 2001, there were many individual acts of unambiguous courage, a primal virtue. As the instigators had no reasonable end to rationalize their means, the moral calculus was very simple that day. Everyone dying stoically or risking death to save others was a courageous person, and other than the terrorists all those who died were innocent victims.
I knew one person who died that day, Brit Oliver Bennett, a real mensch, but as I worked at Moody's and took the daily stop at the World Trade Center to get to work, when I see the documentaries it really makes me tear up thinking about the horrible ending to people so 'close' to me.
Physical courage is admirable, but in modern society it simply isn't as important as it was when philosophy developed 2500 years ago. Intellectual courage, the readiness to risk humiliation, is much harder, precisely because it is more ambiguous. Only with the virtue of hindsight of generations do we see intellectually courageous stands for what they were, what distinguishes the Churchills from the Maos, the Galileos from the Lysenkos. It is courage combined with prudence, not mere zealotry.
Having something terrible happen to you generates instant sympathy. Our culture has moved from from celebrating accomplishment (Eisenhower) to suffering (McCain), where suffering has been expanded to include the indignity of growing up a non-asian minority. Thus, Obama's rather cushy Hawaiian life was transformed in his autobiography into something subtly oppressive because his biological father was African.
I think it's fine to remember that many people were virtuous on that day, but statistically it occurs among millions of people who get up day after day, without complaining, and suffer indignities and physical inconvenience doing a job they are overqualified for, primarily to provide for their families. Let's not make random victimization the new template for heroes and holidays.
Friday, September 09, 2011
Unions of Peace
Joe Biden, Labor Day:
From the NYT yesterday:
von Mises noted that unions were based on coercion and monopoly, sources of inefficiency and simple injustice in most scenarios, but, they're populist, so it's always tempting to rationalize them in some way.
"We've been through a lot of fights, but this is a different kind of fight," he told an annual Labor Day gathering of the Cincinnati AFL-CIO. "This is a fight for the heart and soul of the labor movement. This is a fight literally for our right to exist. Don't misunderstand what this is. … You are the only folks keeping the barbarians from the gates."
From the NYT yesterday:
About 500 longshoremen stormed the new $200 million terminal in Longview before sunrise Thursday, carrying baseball bats, smashing windows, damaging rail cars and dumping tons of grain from the cars, police and company officials said.
von Mises noted that unions were based on coercion and monopoly, sources of inefficiency and simple injustice in most scenarios, but, they're populist, so it's always tempting to rationalize them in some way.
Thursday, September 08, 2011
Why I'm Pessimistic
Last month, a big deal was made about a deal to raise the debt ceiling, which involved a major concession by Obama: $917 billion in spending cuts over 10 years. A special committee of lawmakers would be charged with finding another $1.5 trillion in deficit reduction, which could come through a tax overhaul and changes to safety-net programs. That included only $22B in fiscal 2012.
Tonight, Obama just added about $100B in spending for FY2012, as well as tax cuts and more spending in future years. Next time there's a debt ceiling stalemate, Obama should promise to cut spending by $10 trillion in future decades.
Tonight, Obama just added about $100B in spending for FY2012, as well as tax cuts and more spending in future years. Next time there's a debt ceiling stalemate, Obama should promise to cut spending by $10 trillion in future decades.
Wednesday, September 07, 2011
Risk and Return: Knowledge is Dangerous
From Yoav Ganzach, Judging Risk and Return of Financial Assets (2001).
So, when judging familiar stocks, analysts' judgments of risks and returns were positively correlated, as conventionally predicted. But when judging unfamiliar stocks, analysts tended to judge the stocks as if they were generally good or generally bad - low risk and high returns, or high risk and low returns. Ganzach presents some surveys, testing a bunch of MBAs familiar with the CAPM. He basically argues that when people really understand an asset, they then apply the standard CAPM reasoning (expected return inversely related to risk), and worked backward from the intitial 'good asset' to 'low return' (or from 'bad' to 'high'), using their theoretical training. The author assumed without much note the CAPM theory as correct. I see it as applying a theory that is severely contradicted by the data, solely because it is so well believed by conventional wisdom.
These students would have been better off in a state of ignorance. Empirically we know that high cashflow and low volatility are correlated with higher-than-average returns, but there's no dominant theory for that.
Ganzach's 'unfamiliar asset' finding is what Sharpe and Amromnin found in general surveys of American investors that when they believed times were propitious for stocks, they would have high returns and low risk. Forecasting the overall market is something difficult for anyone, so individuals would likely behave as if this were an 'unfamiliar' asset play.
But with some knowledge of the situation, one sees the particulars which are invariably mixed: everything has pros and cons. To see a pattern within this overload of data requires a theory, and the dominant one in this case is that a 'good' company is not risky (eg, high profits, low volatility), so its return therefore should be low.
People apply the halo effect because it's generally true, in this case to company risk and returns. The 'halo effect' theory is certainly not true all the time, but the key is it just has to be true most of the time to be a useful generalization, because it then saves one time thinking about things.
When we have a lot of data, however, we override this generalization, because we figure more knowledge should increase our understanding of whatever we are examining. This too, as a generalization, is true. All theories are wrong, some are useful, so the hope is that your theory is of the latter sort. In these cases, the more one knows, the more one is lured into applying their theoretical knowledge, and then the issue is whether or not their underlying theory is either irrelevant or has a sign error. Unfortunately, a lot of conventional theories are profoundly wrong.
Consider that in earlier days, people thought eating fat made you fat, boys secretly desired to have sex with their mothers, and that people learned solely through operant conditioning. Consider that today, people with education degrees tend to emphasize credentialism even though they are in the best position to understand how wrong this is, or most macroeconomists think that when unemployment is high the government should spend ever more money regardless of how it is spent; experts are less wise than laypersons in their very own fields.
When you know a lot of facts you can rationalize your opinions very well, but it does not converge one's beliefs onto better theories, more so the bigger the theory. Consider how psychologists are not happier than average, political scientists never seem attractive politicians, economists are generally not good economics advisers .
When William Blake noted that 'To generalize is to be an idiot. To particularize alone is a distinction of merit', I am sympathetic. People are bad at generalizing in general. Humans are pretty good at picking up social cues, sensing when their dog is hungry, but the more abstract the worse it gets. Our wet neural nets simply weren't optimized for this kind of thing, which is why common sense among experts is less frequent than what one thinks greater learning should bring. We are often led astray by theories that tend to tell comforting stories, or that contain bad analogies, faulty extrapolations, or omitted variables biases. We can't avoid generalizing at some level, just as we can't look at data and see anything without some kind of theory. But it's a useful generalization that when your source is an academic theory, caveat emptor.
According to this model, unfamiliar assets are unidimensionally perceived on a continuum ranging from “good” to “bad.” Judgments of risk and return are derived from this unidimensional attitudinal continuum. If an asset is perceived as good, it will be judged to have both high return and low risk, whereas if it is perceived as bad, it will be judged to have both low return and high risk.
[for familiar assets the results are] similar to the standard economic model of the risk and return of financial assets (e.g., the Capital Assets Pricing Model; see, for example, Sharpe, 1981).
So, when judging familiar stocks, analysts' judgments of risks and returns were positively correlated, as conventionally predicted. But when judging unfamiliar stocks, analysts tended to judge the stocks as if they were generally good or generally bad - low risk and high returns, or high risk and low returns. Ganzach presents some surveys, testing a bunch of MBAs familiar with the CAPM. He basically argues that when people really understand an asset, they then apply the standard CAPM reasoning (expected return inversely related to risk), and worked backward from the intitial 'good asset' to 'low return' (or from 'bad' to 'high'), using their theoretical training. The author assumed without much note the CAPM theory as correct. I see it as applying a theory that is severely contradicted by the data, solely because it is so well believed by conventional wisdom.
These students would have been better off in a state of ignorance. Empirically we know that high cashflow and low volatility are correlated with higher-than-average returns, but there's no dominant theory for that.
Ganzach's 'unfamiliar asset' finding is what Sharpe and Amromnin found in general surveys of American investors that when they believed times were propitious for stocks, they would have high returns and low risk. Forecasting the overall market is something difficult for anyone, so individuals would likely behave as if this were an 'unfamiliar' asset play.
But with some knowledge of the situation, one sees the particulars which are invariably mixed: everything has pros and cons. To see a pattern within this overload of data requires a theory, and the dominant one in this case is that a 'good' company is not risky (eg, high profits, low volatility), so its return therefore should be low.
People apply the halo effect because it's generally true, in this case to company risk and returns. The 'halo effect' theory is certainly not true all the time, but the key is it just has to be true most of the time to be a useful generalization, because it then saves one time thinking about things.
When we have a lot of data, however, we override this generalization, because we figure more knowledge should increase our understanding of whatever we are examining. This too, as a generalization, is true. All theories are wrong, some are useful, so the hope is that your theory is of the latter sort. In these cases, the more one knows, the more one is lured into applying their theoretical knowledge, and then the issue is whether or not their underlying theory is either irrelevant or has a sign error. Unfortunately, a lot of conventional theories are profoundly wrong.
Consider that in earlier days, people thought eating fat made you fat, boys secretly desired to have sex with their mothers, and that people learned solely through operant conditioning. Consider that today, people with education degrees tend to emphasize credentialism even though they are in the best position to understand how wrong this is, or most macroeconomists think that when unemployment is high the government should spend ever more money regardless of how it is spent; experts are less wise than laypersons in their very own fields.
When you know a lot of facts you can rationalize your opinions very well, but it does not converge one's beliefs onto better theories, more so the bigger the theory. Consider how psychologists are not happier than average, political scientists never seem attractive politicians, economists are generally not good economics advisers .
When William Blake noted that 'To generalize is to be an idiot. To particularize alone is a distinction of merit', I am sympathetic. People are bad at generalizing in general. Humans are pretty good at picking up social cues, sensing when their dog is hungry, but the more abstract the worse it gets. Our wet neural nets simply weren't optimized for this kind of thing, which is why common sense among experts is less frequent than what one thinks greater learning should bring. We are often led astray by theories that tend to tell comforting stories, or that contain bad analogies, faulty extrapolations, or omitted variables biases. We can't avoid generalizing at some level, just as we can't look at data and see anything without some kind of theory. But it's a useful generalization that when your source is an academic theory, caveat emptor.
Tuesday, September 06, 2011
US MVP Year to Date
I have my own set of MVP and low volatility indices over at betaarbitrage.com. Here's the MVP drawn from the S&P500, compared to the S&P500 this year. It had a very good August, primarily because it has only 50 stocks from within the S&P and one of them was Motorola (that generated 1.5% to the index in August). So, it's up 13% more than the S&P for this year, whereas prior to that, from 1998 through 2010, it outperformed only by 4.8% annually. An it has about a 0.5 beta, and about 18% less volatility. Basically, it outperformed because of standard tracking error, being a subset of 50 stocks, so I don't read too much into one month.
I'd like to find the other MVPs and see how they compare, as I bet over short periods like 8 months they vary a lot. One distinction of mine is that I totally ignore industry concentration, and just take the 50 stocks that generate the lowest portfolio variance (estimated on 3 latent factors using the prior 252 business days). A lot of people add industry limits, but I find that double counting. It is not as if any industries have an obvious 'size' or 'value' effect, and to the extent they are correlated that should be addressed in my algorithm. So, que sera sera, industry-wise. I think it might be my special sauce relative to all these newcomers.
Monday, September 05, 2011
California to Regulate 2-hour Babysitter Shifts
Regulation in this country is out of control. Anyone who has met with 'regulators' knows how incredibly ignorant they are about what they are trying to manage, as when a boss 4 levels above you comes in and tries to make your daily tasks more efficient. They are often good people, just doing their job, but it's rather pitiful watching them come in, you explain what you do, and they make some silly reporting requirements. The latest turns the regulator knob to 11:
Under AB 889, household “employers” (aka “parents”) who hire a babysitter on a Friday night will be legally obligated to pay at least minimum wage to any sitter over the age of 18 (unless it is a family member), provide a substitute caregiver every two hours to cover rest and meal breaks, in addition to workers’ compensation coverage, overtime pay, and a meticulously calculated timecard/paycheck.
Betting on Banks
Warren Buffett made a big investment in Bank of America a couple weeks ago. The PE based on estimates of next year's earnings is about 4, which suggests it is really cheap. Unfortunately, there's a catch.
Our government is going after the banks, suing them for losses on loans guaranteed by Fannie and Freddie. As Dick Bove notes, this would be the tip of the iceberg:
So, if the government wins this case, it would establish a fact that other investors could use, and given the size of the mortgage market, basically wipe the banks out. Meanwhile, Obama has been castigating 'fat cat bankers' for not lending more. Bove thinks banks are a good buy because the government will realize it is making a mistake: ruining the banking sector would not help the economy, we don't have enough money to recapitalize it after giving it to the trial lawyers.
The government is basically behaving like a child, wanting inconsistent things. That's understandible, because the government is not a unified whole, rather, a collective with many parochial interests. The rumored call for selective stimulus through targeted tax breaks for 'innovative' businesses, and the constant demand for closing corporate loopholes, is inconsistent. Today's loophole is yesterday's targeted tax break. So is the idea that for labor, temporarily reducing payroll taxes is a good idea, but that same administration has pushed for increasing the minimum wage.
Bove is betting that the FHA will have the wisdom to drop the lawsuit because winning would be a tragedy for the economy, and I bet Buffett also has this kind of faith. It's an interesting gamble.
Personally, I think the quicker bad ideas fail the better. Obamacare is really poisonous because it kicks in slowly and front loads revenues, so by the time everyone notices it is a bad idea and very expensive (say 2014), it will be impossible to prove what provisions and who is at fault (the new President, or Congress, will be to blame). Let the FHA win its lawsuit asap, crash the economy, and then our legislators may understand that without a vibrant business sector, they have no taxes to distribute.
Our government is going after the banks, suing them for losses on loans guaranteed by Fannie and Freddie. As Dick Bove notes, this would be the tip of the iceberg:
The price tag is unlimited. Basically, we can look at Fannie Mae and Freddie Mac and say they've lost $33 billion, supposedly, as a result of buying these bad mortgages, and therefore, those losses should be put back to the banking system. But in essence, if we establish the precedent that anyone can sue a bank if they get a mortgage that doesn't work out, and there were $5 trillion of mortgages that were securitized through this Fannie-Freddie system over the past number of years. I have no idea how many people would sue, nor how much the courts are willing to give back to these companies and take away from the banks. It's a very, very negative development.
So, if the government wins this case, it would establish a fact that other investors could use, and given the size of the mortgage market, basically wipe the banks out. Meanwhile, Obama has been castigating 'fat cat bankers' for not lending more. Bove thinks banks are a good buy because the government will realize it is making a mistake: ruining the banking sector would not help the economy, we don't have enough money to recapitalize it after giving it to the trial lawyers.
The government is basically behaving like a child, wanting inconsistent things. That's understandible, because the government is not a unified whole, rather, a collective with many parochial interests. The rumored call for selective stimulus through targeted tax breaks for 'innovative' businesses, and the constant demand for closing corporate loopholes, is inconsistent. Today's loophole is yesterday's targeted tax break. So is the idea that for labor, temporarily reducing payroll taxes is a good idea, but that same administration has pushed for increasing the minimum wage.
Bove is betting that the FHA will have the wisdom to drop the lawsuit because winning would be a tragedy for the economy, and I bet Buffett also has this kind of faith. It's an interesting gamble.
Personally, I think the quicker bad ideas fail the better. Obamacare is really poisonous because it kicks in slowly and front loads revenues, so by the time everyone notices it is a bad idea and very expensive (say 2014), it will be impossible to prove what provisions and who is at fault (the new President, or Congress, will be to blame). Let the FHA win its lawsuit asap, crash the economy, and then our legislators may understand that without a vibrant business sector, they have no taxes to distribute.
Thursday, September 01, 2011
In practice, Correlation Implies Causation
Of course, everyone knows the cliche that correlation does not imply causation, but in practice any correlation that fits into a narrative is seen as evidence of that theory. This NBER paper by Currie and Tekin argues foreclosures lead to a variety of bad health outcomes--sort of like the symptoms of chronic fatigue syndrome. It's a joke, but sure got a lot of play over the past few days because it's so darn helpful to some people. See the attached graph, which underlies their findings. The NBER, like the American Economic Association, is a pretty official, bureaucratic, PC trade institution that wants to be relevant and respected.
This is the same group condemned The Bell Curve for producing arguments directly to a public that could not understand statistics as well as trained economists, an absurd proclamation that would eliminate all working papers and books. Econometric technique is much less important than one's biases, which is why we should have 'free-market', 'Marxist', and 'Keynesian' econometricians, just like we have Republican and Democratic pollsters. It's not like a lifetime Keynesian/supply-sider, at age 50, will suddenly publish a paper documenting that fiscal multipliers are exactly opposite to their preconceptions. It's the meta-decisions of what to look at, what to control for, that fall outside any formal statistics that determine most interesting conclusions, not some asymptotic distribution on moment restrictions.
Subscribe to:
Posts (Atom)