savageinfidel

Due to severe inclement weather (ice storm), less than half of my investments class showed up on Wednesday. The topic (market indexes) seems to give some of them trouble. So, rather than either go over it again in the next class (and make those who attend have to sit through it twice) or just move on (and leave those who clearly had a reason for missing class hanging), I put together a video on the topic. Since it's done, figured I might as well share. It's not professionally done by any stretch, but it's not bad (it runs about 40 inutes, but has a table of contents that whould allow you to jump back and forth). Enjoy. NOTE:if the video doesn't come up, try this link .

When I teach investments, there's always a section on market efficiency. A key point I try to make is that any test of market efficiency suffers from the "joint hypothesis" problem - that the test is not tests market efficiency, but also assumes that you have the correct model for measuring the benchmark risk-adjusted return. In other words, you can't say that you have "alpha" (an abnormal return) without correcting for risk. Falkenblog makes exactly this point: In my book Finding Alpha I describe these strategies, as they are built on the fact that alpha is a residual return, a risk-adjusted return, and as 'risk' is not definable, this gives people a lot of degrees of freedom. Further, it has long been the case that successful people are good at doing one thing while saying they are doing another. Even better, he's got a pretty good video on the topic (it also touches on other topics). Enjoy.

Here's a paper by Bradford Cornell that I've had in my in box for a while. It's titled "Investment Research: How Much Is Enough?" Here's the abstract Aside from the decision to enter the equity market, the most fundamental question an investor faces is whether to passively hold the market portfolio or to do investment research. This thesis of this paper is that there is no scientifically reliable procedure available which can be applied to estimate the marginal product of investment research. In light of this imprecision, investors become forced to rely on some combination of judgment, gut instinct, and marketing imperatives to determine both the research approaches they employ and the capital they allocate to each approach. However, decisions based on such nebulous criteria are fragile and subject to dramatic revision in the face of market movements. These revisions, in turn, can exacerbate movements in asset prices. I raises some interesting issues about th...

I try not to get too excited about short-term market movements. At the same time, I have to keep up since I'm the faculty advisor for Unknown University's St udent-managed fund. Even so, it's been a pretty good week (and month and year) so far - almost every equity index I can think of is in the green for the last month (and even year to date). As an aside, our fund is up 11.4% YTD (but I'm sure that'll change). click for larger image (courtesy of investmentpostcards.com)

Instead of the CCAPM (Consumption CAPM), we now have the GCAPM (Garbage CAPM). Alexi Savov (graduate student at U of Chicago) finds that he can explain much more of the Equity Risk Premium using aggregate garbage production than he can using National Income and Product Account (NIPA) data. Here's the logic behind his research (from Friday's Wall Street Journal article titled "Using Garbage to Measure Consumption"): In theory, one way to explain the premium would be to look at consumption, a broad measure of wealth. People should demand a premium from an investment that goes down when consumption goes down. That’s because the alternative — bonds — hold on to their value when consumption declines. Another way to put it: When you are making lots of garbage, you are rich. When you stop making garbage, you are poor. Unlike bonds, which continue to pay out whether you produce lots of garbage (and are rich) or not, stocks are likely to lose their value during bad time...

It's a pretty well-known fact that correlations between asset classes increase in really bad markets. To get a sense of how much this effect matters in terms of portfolio diversification, read this Wall Street Journal piece (published Friday, 7/10) titled "Failure of a Fail-Safe Strategy Sends Investors Scrambling. Here's a snippet: Correlation is a statistical measure of the degree to which investment returns move together. Between 1991 and 1994, the correlation between the S&P 500 index and high-yield bonds was low, at 0.2 or 0.3, according to Pimco statistics. (A correlation of 1 means returns move in perfect sync.) International stocks had a correlation with the S&P 500 of 0.3 or 0.4, and real-estate investment trusts had a correlation of 0.3, according to Pimco data. Commodities showed little correlation to U.S. stocks. By early 2008, investment categories of just about every stripe were moving significantly more in sync with the S&P 500. The correlation...

Here's an excellent piece on the Psi-Fi Blog , titled "Quibbles With Quants." Here's a choice part: What the models failed to capture was that humans don’t behave in simple, predictable and uncorrelated ways. It’s impossible to overstate the importance of the way these models cope with correlation of peoples’ psychology. To sum it up: they don’t. Let me know if that’s too complex an analysis for the mathematical masters of the universe. Anyone who’s ever been to a nightclub, a football game or even a very loud party will know that there are situations where we don’t act as individuals, buzzing about doing our own thing. These are occasions when we all suddenly stop being individuals and start doing the same thing – usually involving large quantities of drugs and some very bad singing. Although these sorts of events are specifically designed to trigger this behaviour – which is probably a deep evolutionary adaptation to sponsor group behaviour, useful when it comes t...

The more Long Chen's work I read, the more I like it. I recently mentioned one of his pieces on a new 3-factor model . Here's another, on the momentum effect, titled " Myopic Extrapolation, Price Momentum, and Price Reversal ." In it, he links the well-known momentum effect to patterns in firm fundamentals. Here's the abstract: The momentum profits are realized through price adjustments reflecting shocks to firm fundamentals after portfolio formation. In particular, there is a consistent cross - sectional trend, from short-term momentum to long-term reversal, that happens to earnings shocks, to revisions to expected future cash flows at all horizons, and to prices. The evidence suggests that investors myopically extrapolate current earnings shocks as if they were long lasting, which are then incorporated into prices and cash flow forecasts. Accordingly, the realized momentum profits can be completely explained by the cross - sectional variation of contemp...

First, a little background on "factor models": The CAPM model for estimating expected returns is the oldest and most widely know of all finance models. In it, exposure to systematic risk (i.e. beta) is only factor that gets "priced" (i.e. that's related to expected returns). In 1993, Fama and French showed that a three factor model (the CAPM market factor plus a size factor and a value/growth factor), did a much better job of explaining cross-sectional returns when compard to the "plain vanilla" CAPM. Since the FF model became popular, a number of studies have come out that identify other factors that seem to be associated with subsequent returns, such as momentum (Jegadeesh and Titman, 1993), distress (Campbell, Hilscher, and Szilagyi, 2008), stock issues (Fama and French, 2008) and asset growth (Cooper, Gulen, and Schill, 2008). Now, on to the meat of this post - another factor model. This one is based on q-theory (i.e. on the marginal produc...

Robert Haugen is one of (if not THE) best-known figure in the behavioral finance (i.e. "markets are not efficient") camp. He wrote one of the earliest books on the topic in 1995 (The New Finance) and runs a quantitative finance shop based on much of his research. In a recent paper with Nardin Baker of UC-Irvine, he examines the explanatory and predictive ability of a wide array of observable factors. Here's the abstract This article provides conclusive evidence that the U.S. stock market is highly inefficient. Our results, spanning a 45 year period, indicate dramatic, consistent, and negative payoffs to measures of risk, positive payoffs to measures of current profitability, positive payoffs to measures of cheapness, positive payoffs to momentum in stock return, and negative payoffs to recent stock performance. Our comprehensive expected return factor model successfully predicts future return, out of sample, in each of the forty-five years covered by our study s...

Things have been crazy lately - we have two speakers this week at Unknown University's College of Business, and I'm involved in both visits. In addition, I'm getting ready for my CFA prep class and trying to get a paper out for a conference. So, blogging has been light this week (and will probably continue to be spotty for the rest of the week). But in the meantime, here's an interesting paper to chew on. We were recently talking about different risk premia (size, market/book, momentum, etc...) in class. This paper, "Portfolio of Risk Premia : A New Approach to Diversification" by Remy Brian, Frank Nielsen, and Dan Stefek paper that takes the idea of risk premia combines it with a equally-weighted portfolio weighting scheme across assets with exposures to the various premiums. Traditional approaches of structuring policy portfolios for strategic asset allocation have not provided the full potential of diversification. Portfolios based upon a 60/40 a...

I'm not a big fan of market timing and/or technical trading rules. From what I've seen, the empirical evidence casts a lot of doubt on their effectiveness. But I just read a very interesting paper titled "A Quantitative Approach to Tactical Asset Allocation", by Mebane Faber. Here's the abstract: The purpose of this paper is to present a simple quantitative method that improves the risk-adjusted returns across various asset classes. A simple moving average timing model is tested since 1900 on the United States equity market before testing since 1973 on other diverse and publicly traded asset class indices, including the Morgan Stanley Capital International EAFE Index (MSCI EAFE), Goldman Sachs Commodity Index (GSCI), National Association of Real Estate Investment Trusts Index (NAREIT), and United States government 10-year Treasury bonds. The approach is then examined in a tactical asset allocation framework where the empirical results are equity-like returns with ...

Here's an interesting cross-breeding of Internet technology and financial information: A wiki-style resource for investors called Wikinvest . In case the term is unfamiliar to you (other than Wikipedia, that is) a wiki is an Internet community where participants can load pages up on various topics and edit pages put up by others. Ideally, it serves as a self-editing source of information, where experts correct mistakes posted by those less informed. Wikinvest has the following areas: Information on companies (0ver 2200 posted to date) A Concepts section, covering topics ranging from industry-specific areas like Technology and the Internet and Energy to "Green Issues) A Commodities section (i.e. metals, energy, grains, etc.) An area covering Funds and Indices (a handful of ETFs and 37 different indices, from the S&P to Baltic Dry Goods) And, of course, Global Markets , ranging from interest rates to investing in Brazil. It's not a source of data, but rather a co...

When the average Joe (or Jane) looks at transactions costs from trading, they typically focus on the commission charged by the broker. But in the case of some thinly-traded ETFs (exchange-traded funds), the bid-ask spread can add significantly to that cost. Here's a good piece on the topic from Morningstar: No one has a very precise definition of liquidity, but it roughly boils down to how easy it is to buy or sell a particular security and how much agreement there is in the marketplace upon the security's fair value. The most liquid funds or stocks have miniscule bid-ask spreads, where the prices differ by only a penny. On the other side, a brand new ETF tracking a selection of more thinly traded mortgage-backed securities has a bid-ask spread near 0.80% as I write this. That means that buying and selling the fund at market prices, even without any commissions charges or price changes, would result in a 0.80% loss. Not exactly a terrifying loss, especially compared with wha...

Here's one of the better explanations I've recently read on the idea of fundamental analysis or "value" investing (from the Ideas Report: Buying a stake in a publicly traded company is deceptively easy. Log into your brokerage account, type in the ticker of the company whose stock you wish to buy, and— voilà !—you own a stake in the enterprise. Many investors don’t even refer to companies by their name; they simply invoke the ticker symbol. The ease with which stocks are bought and sold obscures the underlying nature of a stock market transaction and invites bad decision-making. The trick is to avoid thinking of a stock as a readily disposable piece of paper and instead consider that you are buying a percentage of a business whenever you purchase a share of stock. Read the whole thing here

As usual, Scott Adams has a good take on things

Are successful traders born, or made? Here's some evidence supporting the latter, from the Washington Post: A new study has found that men who were programmed in the womb to be the most responsive to testosterone tend to be the most successful financial traders, providing powerful support for the influence of the hormone over their decision-making. Read the whole thing here

Many people use levered ETFs to either leverage (i.e. double) or hedge their exposure to an index Unfortunately, their results can often differ from what they expect. This Wall Street Journal gives a good explanation why in this article. It's a good illustration how volatility makes geometric and arithmetic averages differ.

Andy Kern and Welsey Gray are two finance doctoral student who also run the blog Empirical Finance Research . They've just put a study up on SSRN titled " Fundamental Value Investors: Characteristics and Performance ." In it, they examine the investment recommendations of a fairly large and sophisticated community of fundamental value investors (the folks at Valueinvestorclub.com ): The data in this study are collected from a private internet community called Valueinvestorsclub.com (VIC), proclaimed by the founders to be an “exclusive online investment club where top investors share their best ideas.”1 The site has been heralded in many business publications as a top-notch resource for anyone who can attain membership (Financial Times, Barron’s, Business Week, and Forbes among others). The site was founded by Joel Greenblatt and John Petry, both successful value investors and managers of the large hedge fund Gotham Capital. It was created with $400,000 of start-up ca...

Seth Klarman, is the president of Boston hedge fund the Baupost Group. He's known as one of the savviest value investors around, having earned a 26% average annual return over the last 26 years. In fact, he was asked to write the foreword to the latest edition of Graham and Dodd's classic "Value Investing." Here's an interview he gave to the Harvard Business School Bulletin back in December. In it, he talks about why he's a value investor, target returns (he doesn't believe in them), the credit crisis, and much more. Read it here