Investing

Thinking, Fast and Slow

Posted by Peter on January 15, 2012
Posted in: Book Reviews, Investing, The Human Mind. Tagged: , , .

Book review: Thinking, Fast and Slow, by Daniel Kahneman.

This book is an excellent introduction to the heuristics and biases literature, but only small parts of it will seem new to those who are familiar with the subject.

While the book mostly focuses on conditions where slow, logical thinking can do better than fast, intuitive thinking, I find it impressive that he was careful to consider the views of those who advocate intuitive thinking, and that he collaborated with a leading advocate of intuition to resolve many of their apparent disagreements (mainly by clarifying when each kind of thinking is likely to work well).

His style shows that he has applied some of the lessons of the research in his field to his own writing, such as by giving clear examples. (“Subjects’ unwillingness to deduce the particular from the general was matched only by their willingness to infer the general from the particular”).

He sounds mildly overconfident (and believes mild overconfidence can be ok), but occasionally provides examples of his own irrationality.

He has good advice for investors (e.g. reduce loss aversion via “broad framing” – think of a single loss as part of a large class of results that are on average profitable), and appropriate disdain for investment advisers. But he goes overboard when he treats the stock market as unpredictable. The stock market has some real regularities that could be exploited. Most investors fail to find them because they see many more regularities than are real, are overconfident about their ability to distinguish the real ones, and because it’s hard to distinguish valuable feedback (which often takes many years to get) from misleading feedback.

I wish I could find equally good book for overuse of logical analysis when I want the speed of intuition (e.g. “analysis paralysis”).

Bitcoin

Posted by Peter on October 28, 2011
Posted in: Investing. Tagged: .

In the process of researching Bitcoin to help me decide whether to buy some as an investment, I’ve come across some confusion about money in some prominent articles.
This article says:

the demand for Bitcoins is driven by the volume of Bitcoin-denominated transactions.

…

the value of a currency is built on its reputation, and five months of bad news and depreciation have done serious damage.

Money serves several different functions. To be widely accepted, a currency typically needs to serve as a medium of exchange and as a store of value. But gold is a good example of a quasi-currency that functions as a fairly good store of value (at least for people with long time horizons). Bitcoin shows more promise of functioning as a store of value than as a medium of exchange.

If Bitcoin were only a medium of exchange, it might make sense to say the volume of Bitcoin transactions drives the demand for it. But if most people who are buying Bitcoins are hiding them under their mattresses on EMP-resistant media (cd-rom?), the price of Bitcoins can rise indefinitely without an increase in transactions.

It isn’t very useful to lump many beliefs about a currency into a single reputation. Bitcoin has different reputations for different traits.

A currency should have a reputation for being in limited supply and for not having that supply increase too rapidly. I’d say Bitcoin has developed a better reputation for this than the US dollar, and might exceed gold’s reputation.

A currency should be easy to store and transport safely. This is an area where Bitcoin’s reputation is the subject of much confusion. There’s currently an unpleasant tradeoff between secure ways to store Bitcoin and convenient ways to have them available to spend. It make take a major rewrite of operating systems (e.g. to use Capability-based security with a good UI) for it to be possible to have Bitcoins be conveniently accessible but hard to steal. Confusion over the risk of theft has probably driven a fair amount of the recent Bitcoin price volatility. My guess is that it’s better that theft has happened now than after people become more reliant on Bitcoin. It will either drive the creation of more secure software (with benefits much wider than Bitcoin use) or discourage people from relying on insecure ways of handling digital money.

Finally, it’s important that a currency have a reputation for being something that people will value in the future. This is a source of significant uncertainty, because it depends on people’s perceptions of the alternative stores of value, the alternative media of exchange, and the risk of Bitcoin theft. Bitcoin has the potential to be a better store of value than gold, because a transparent algorithm can better guarantee a limited supply than the difficulty of mining a metal. People who started watching Bitcoin prices a few months ago in response to a flurry of publicity attach a low reputation to its prospects as a store of value because the recent price crash is more vivid in their mind than the earlier boom, but that’s a temporary phenomenon that doesn’t deserve much attention.

For most uses as a medium of exchange, Bitcoin doesn’t offer much advantage now. For most transactions, the small cost savings aren’t enough to persuade consumers to give up the ability to dispute a payment, or for stores that accept Bitcoin with an option to dispute payment to offer a discount for Bitcoin purchases. And I expect governments and large financial institutions to create obstacles to its use as a medium of exchange. There are a few small uses where it works better than any existing alternative – e.g. Wikileaks, where the existing financial system refuses to support online payments. Bitcoin anonymity doesn’t appear strong enough to attract people engaged in illegal businesses. Online gambling companies might get some advantage from using Bitcoin if the obstacles to transferring money to gambling sites exceed the obstacles to buying Bitcoin, but I’m guessing the obstacles are and will be at least as large for buying Bitcoin. So I expect very slow adoption of Bitcoin as a medium of exchange.

I do think there’s a nontrivial chance that Bitcoin will become widely used as a store of value, and that might replace a significant amount of demand for gold a decade or two from now. A decline in demand for gold as a store of value might well snowball, as extrapolating that trend would imply that gold becomes a less reliable store of value. That doesn’t yet make me reluctant to buy gold, but a Bitcoin price over 0.1 ounces of gold might make me reconsider.

I will probably invest a small fraction of my net worth in Bitcoin, but I don’t feel any urgency about it.

Expected Returns

Posted by Peter on August 23, 2011
Posted in: Book Reviews, Investing. Tagged: , .

Book review: Expected Returns: An Investor’s Guide to Harvesting Market Rewards, by Antti Ilmanen.
This book is causing me to change my approach to investing much more than any other book has. It is essential reading for any professional investor.

The foreword starts by describing Ilmanen as insane, and that sounds like a good description of how much effort was needed to write it.

Amateur investors will have trouble understanding it – if you’re not familiar with Sharpe ratios, you should expect to spend a lot of time looking elsewhere for descriptions of many concepts that the book uses. I had a few problems understanding the book – he uses the term information ratio on page 188, but doesn’t explain it until page 491 (and it’s not indexed). I was also somewhat suspicious about how he handled data mining (overfitting) concerns in momentum strategies until I found a decent answer in a non-obvious place (page 404).

The most important benefit of this book is that he has put a lot of thought into identifying which questions investors should be trying to answer. Questions such as whether past performance is a good indicator of future returns, and what would cause a pattern of superior returns to persist or vanish.

Some other interesting topics:

  • why it’s important to distinguish between different types of undiversifiable risk, and how to diversify your strategies so that the timing of losses aren’t highly correlated across those strategies.
  • why earnings per share growth has been and probably will continue to be below GDP growth, contrary to what most forecasts suggest.
  • how to estimate the premium associated with illiquidity
  • why it’s useful to look at changes in correlations between equities

It’s really strange that I ordered this a few weeks after what Amazon lists as the publication date, but it took them nearly 7 weeks to find a copy of it.

Some quotes:

overfitting bias is so insidious that we cannot eliminate it (we cannot “become virgins again” and forget our knowledge)

the leverage of banks will soon be more tightly restricted by new regulations. The practical impact will be more pronounced risk premia for low-volatility assets, more sustained mispricings, and greater opportunities for those who can still apply leverage

European financial crisis

Posted by Peter on August 8, 2011
Posted in: Investing, Politics.

Arnold Kling has a concise summary of the current crisis:

Apparently, the resolution of the debt ceiling restored the dollar’s status as a safe haven in the eyes of the world’s investors. That accelerated the flight from European sovereign debt and European banks. That in turn raised fears in financial markets, driving down stocks, including in the United States.

The European monetary system appears to suffer from the same problems as Bretton Woods.

European voters seem unlikely to tolerate the measures needed to maintain the current system. Yet the breakup will cause enough problems for the banking system that politicians will postpone it as long as possible.

Avoid News

Posted by Peter on March 9, 2011
Posted in: Investing, Politics. Tagged: .

Avoid News is a good rant against paying attention to the storytellers that typically get labeled as news reporters:

Information is no longer a scarce commodity. But attention is. Why give it away so easily? You are not that irresponsible with your money, your reputation or your health. Why give away your mind?

I don’t know a single truly creative mind who is a news junkie – not a writer, not a composer, mathematician, physician, scientist, musician, designer, architect or painter. On the other hand, I know a whole bunch of viciously uncreative minds who consume news like drugs.

Bryan Caplan says:

P.S. When I read this passage, the counter-example of Tyler Cowen came immediately to mind.

I don’t consider that much of a counter-example. I found Tyler Cowen’s blog to be a dangerous addiction, and I’m glad I quit. I have a strong impression that he could be much more creative than he is, but has made a deliberate choice to pursue fame at the expense of creativity.

In order to maintain the pretense that news focuses on important information, storytellers focus on events that make us unhappy (avoiding or fixing mistakes are more important than understanding what routinely goes right, which makes it hard to focus on good news). [This also applies to other sources of political information, but that means I want the most concise source, which is not likely to be a rapidly published source.]

I’m not willing to completely follow the advice to kick my news addiction, since I’m somewhat dependent on social connections with people who imagine that news media provide valuable information. But I can mostly learn enough by watching The Daily Show, which often (but hardly consistently) is careful to indicate that they focus on frivolous, entertaining stories that give low priority to educational value. I’m definitely better off with that than I was when I was addicted to serious-sounding daily news sources.

I have a system for reading financial news that minimizes the problems with news. It involves mostly reading numbers that I find via stock symbols. Most of those numbers have been checked by accountants, who have strict rules to minimize biases. I’m fairly careful to select which symbols I follow by analyzing numbers, not stories.

For more evidence that news harms you, see an experiment done by Andreassen where subjects trading stocks did worse if they saw a constant stream of news than if they saw no news once they started trading.

Also, Robin Hanson’s analysis of how the press handled one story suggests a pretty clear positive correlation between the time a source takes to convey a story and the accuracy of that story.

[I’ve been neglecting this blog recently due to an obsession with finding waterfalls; that will change any week now when rainfall tapers off.]

Disadvantages of Stories

Posted by Peter on August 12, 2010
Posted in: Investing, The Human Mind.

Tyler Cowen has a good video describing why we shouldn’t be too influenced by stories. He exaggerates a bit when he says

There are only a few basic stories. If you think in stories, that means you are telling yourself the same thing over and over

but his point that stories allow storytellers to manipulate our minds deserves more emphasis. For me, one of the hardest parts of learning how to beat the stock market was to admit that I did poorly when I was influenced by stories, and did well mainly when I relied on numbers that are available and standardized for most companies, and on mechanical rules which varied little between companies (I sometimes use different rules for different industries, but beyond that I try to avoid adapting my approach to different circumstances).

For example, The stories I heard about Enron’s innovative management style gave me a gut feeling that it was a promising investment. But its numbers showed an uninteresting company, and persuaded me to postpone any investment.

But I’ve only told you a story here (it’s so much easier to do than provide rigorous evidence). If you really want good reasons, try testing for yourself story versus non-story approaches to something like the stock market.

(HT Patri).

Stock Market Liquidity

Posted by Peter on May 11, 2010
Posted in: Investing. Tagged: .

One simple way to prevent fluctuations like those of last Thursday would be for stock exchanges to prohibit orders to buy or sell at the market.

That wouldn’t mean prohibiting orders that act a lot like market orders. People could still be allowed to place an order to sell at a limit of a penny. But having an explicit limit price would discourage people from entering orders that under rare conditions end up being executed at a price 99 percent lower than expected.

It wouldn’t even require that people take the time to type in a limit price. Systems could be designed to have a pseudo-market order that behaves a lot like existing market orders, but which has a default limit price that is, say, 5 percent worse than the last reported price.

However, it’s not obvious to me that those of us who didn’t sell at ridiculously low prices should want any changes in the system. Moderate amounts of money were transferred mainly from people who mistakenly thought they were sophisticated traders to people who actually were. People who are aware that they are amateurs rarely react fast enough to declines to have done anything before prices recovered. The decline looked like it was primarily the result of stop-loss strategies, and it’s hard to implement those without at least superficially imitating an expert investor.

Finding Alpha

Posted by Peter on December 1, 2009
Posted in: Investing. Tagged: , .

Book review: Finding Alpha: The Search for Alpha When Risk and Return Break Down by Eric Falkenstein.

This book presents mostly convincing arguments that refute the basic principle of CAPM that riskier investments are rewarded with higher returns, and the relation between risk and returns is better explained by modeling investors as wanting high returns relative to other investors rather than high absolute returns. But the quality of the arguments is quite variable. Much of the book assumes a good understanding of finance theory. If you don’t understand the importance of a Sharpe ratio, you’re not in his target audience.

I was not convinced by his most heavily emphasized empirical claim, that returns on equities are unrelated to beta because controlling for size eliminates the apparent relation. There’s enough connection between size and risk that this raises many questions he doesn’t answer (e.g. JB Berk, A critique of size-related anomalies). But later on he devotes a chapter to a wide variety of evidence that overcomes these concerns, and somewhat supports his claim that for riskier investments, the correlation between risk and return is negative (for the safest investments, it’s positive). And the authoritative Fama and French paper has more convincing evidence about beta – even without controlling for size, the correlation between beta and returns vanished during the 1963 to 1990 period.

He claims that the equity risk premium is effectively zero for a typical investor. His attempt to add up the different adjustments is confusing. He concludes with a table showing size adjustments to that standard estimate that add up to a mind-boggling 15 percent, which would result in a “premium” of -9 percent or so. But adding them is clearly wrong – the tax adjustment assumes the absence of some of the other adjustments. Still, the arguments he assembles from other researchers imply a good chance that the sign of the equity risk premium varies with the time period over which it’s measured.

He suggests some strategies to invest more wisely as a result of the ideas he presents, which he aptly summarizes as “selling hope relative to the market” (i.e. treating volatile stocks as overpriced due to a hope premium). But claiming this produces “superior returns, with less risk however measured” is too strong. Financial risk is not the only relevant measure of risk. Following his advice has social risks that he hints at elsewhere. Being invested in boring stocks in a bubble impairs your ability to engage in some interesting conversations, and you won’t make up for that by mentioning how you outperform the market in times when other want to avoid remembering their investments. Is it possible to minimize both kinds of risks by investing token amounts in ways that trendy folks are talking about, and investing most of your money to maximize your Sharpe ratio? Or does that require too much cognitive dissonance?

The book encourages pessimism, especially about the effects of people wanting relative wealth, and makes disturbing claims such as “Envy is necessary for compassion”.

He provides a number of other good ideas about investing, such as the possibility that the internet bubble adds a big anomaly to many data sets used for backtesting.

Confusing S&P Index Earnings Numbers

Posted by Peter on July 4, 2009
Posted in: Investing. Tagged: .

I just noticed some confused arguments between Jeremy Siegel and Standard and Poors over how to aggregate earnings for companies in a stock index to produce a meaningful report of what the companies in the index earned.
See here and here.

Siegel provides an example involving percent changes in Exxon-Mobil and Jones Apparel. But that has a weak resemblance to what S&P is doing. A more accurate analogy to what S&P is doing would use changes to market cap rather than percent changes. If Jones Apparel declined in market cap by $10 billion, it would hurt the index just as badly as a $10 billion decline in Exxon-Mobil’s market cap. Looked at that way, S&P’s approach looks sensible.

But since Jones Apparel has a market cap of less than $1 billion, the current bankruptcy laws make it far-fetched that Jones Apparel could lose more than $1 billion in market cap.

If you’re using earnings as a proxy for the health of the economy, S&P’s method doesn’t create a problem – the bankruptcy laws affect who loses money, but the money is still lost. But for an investor, Siegel has a point which is half right.

Siegel’s solution of weighting earnings by market cap may work well under any realistic conditions, but has no sensible theory behind it, and can fail badly under some far-fetched conditions. Imagine that Jones Apparel reports an unexpected one-time windfall of $1 trillion, which ought to raise the market cap of Jones Apparel by about $1 trillion. The way S&P computes S&P 500 earnings, an investor looking at S&P 500 earnings would see a strong hint that the value of the S&P 500 ought to rise by about $1 trillion. But under Siegel’s method, the initial effect on S&P 500 earnings would suggest a barely noticeable rise in the value of the S&P 500 of under $1 billion. Then at some point the Jones Apparel market cap would soar and the S&P 500 earnings would be recomputed with much different weights and investors would see a much different picture. So Siegel has proposed something which could result in a potentially large change in reported S&P 500 earnings without any change in the what shares someone who invests in the S&P 500 holds and without any changes in reported earnings.

Morningstar has a method (PDF) designed for evaluating portfolios that uses a harmonic weighted average and ignores companies with negative earnings. That has advantages, but the magnitude of losses provides some hints about how far a company is from profitability, so an ideal method should pay some attention to losses.

Siegel mentions comments by Shiller that suggest Shiller has better (but possibly impractical) ideas. I doubt Shiller’s analysis provides as much support for Siegel’s argument as Siegel claims.

Any sensible investor looks at a multi-year average of earnings along the lines suggested by Shiller, which minimizes the problems associated with faulty weighting of earnings.

Evidence-Based Technical Analysis

Posted by Peter on April 17, 2009
Posted in: Book Reviews, Investing. Tagged: .

Book review: Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, by David Aronson.

This is by far the best book I’ve seen that is written for professional stock market traders. That says more about the wishful thinking that went into other books that attempt to analyze trading rules than it does about this author’s brilliance. There are probably books about general data mining that would provide more rigorous descriptions of the relevant ideas, but they would require more effort to find the ideas that matter most to traders.

There hasn’t been much demand for rigorous analysis of trading systems because people who understand how hard it is to do it well typically pick a different career, leaving the field populated with people who overestimate their ability to develop trading systems. That means many traders won’t like the message this book sends because it doesn’t come close to fitting their preconceptions about how to make money. It is mostly devoted to explaining how to avoid popular and tempting mistakes.

Although the book only talks specifically about technical analysis, the ideas in it can be applied with little change to a wide variety of financial and political forecasting problems.

He is occasionally careless. For example: “All other things being equal, a TA rule that is successful 52 percent of the time is less valuable than one that works 70 percent of the time.” There might be a way of interpreting this that is true, but it’s easy for people to mistake this for a useful metric, when it has little correlation with good returns on investment. It’s quite common for a system’s returns to be dominated by a few large gains or losses rather than the frequency of success.

The book manages to spell Occam three different ways!