Collateralized debt obligations (CDOs) have been responsible for $542 billion in write-downs at financial institutions since the beginning of the credit crisis. In this paper, I conduct an empirical investigation into the causes of this adverse performance, looking specifically at asset-backed CDO’s (ABS CDO’s). Using novel, hand-collected data from 735 ABS CDO’s, I document several main findings. First, poor CDO performance was primarily a result of the inclusion of low quality collateral originated in 2006 and 2007 with exposure to the U.S. residential housing market. Second, CDO underwriters played an important role in determining CDO performance. Lastly, the failure of the credit ratings agencies to accurately assess the risk of CDO securities stemmed from an overreliance on computer models with imprecise inputs. Overall, my findings suggest that the problems in the CDO market were caused by a combination of poorly constructed CDOs, irresponsible underwriting practices, and flawed credit rating procedures.
Findings (vai Anna Katherine Barnett-Hart @ Harvard)
The signs of the coefficients for Moody’s and S&P are consistent with the conflict of interest problem: bigger underwriters were associated with a higher initial % AAA, resulting in a subsequent higher level of downgrades, AAA Loss, and an overall higher level of prediction mistakes as calculated by the difference in predicted and actual levels of Default. However, these results could just as easily be caused by the fact that the most prolific underwriters were producing worse CDOs, and that rather than receive preferential treatment by the rating agencies, the problem was merely that these originators were treated the same as other underwriters, although in reality they were producing worse CDOs. Given the striking uniformity of initial CDO credit ratings and the fact that the prediction value of the asset credit ratings depended mainly on the quality of the underwriter, the latter explanation seems more likely, suggesting that the conflicts of interest is not as much to blame as simply a failure to distinguish among underwriter quality.
Didier Sornette has immersed his life in risk. He rides motorcycles, windsurfs and water skis long stretches of a 120-mile route between Nice and Corsica. Now comes a daunting professional challenge: “The Financial Bubble Experiment.”
Mr. Sornette, 52 years old, is the director of the Financial Crisis Observatory at the Swiss Federal Institute of Technology in Zurich, or as he calls it, “the MIT of Europe.” Late last year, he launched the bubble experiment by identifying four developing bubbles and forecasting when they’ll peak. His predictions are locked away in encrypted files that can’t be altered, to be revealed only when the forecasted bubble peaks have passed, on May 1.
This sounds like reflexivity!!! (via WSJ)
And he continued to flex his forecasting muscles, looking for certain “fingerprints” in market prices that help him identify bubbles. While there’s lots of complex math behind it, one key pattern is essentially this: periods of unsustainable growth, in which the growth rate is itself accelerating, punctuated by waves of panicky selling. Key elements are the “positive feedback” generated by optimistic investors pushing the price ever higher into bubble territory even as more pessimistic investors produce waves of selling. In the midst of this tug of war, there’s an accelerated development of the bubble.
Only about two-thirds of bubbles end in a crash, Mr. Sornette says. But in his view, as the bubble develops, it becomes increasingly unstable so that any number of small disturbances could cause it to pop. (He uses the analogy of a ruler held vertically on a finger. Any small movement will cause it to fall.) So while market-watchers often seek the causes of a crash in the events immediately preceding it, he believes the fundamental origin is in the longer-term build-up of instability.
Prevailing models of capital markets capture a limited form of social influence and information transmission, in which the beliefs and behavior of an investor affect others only through market price, information transmission and processing is simple (without thoughts and feelings), and there is no localization in the influence of an investor on others. In reality, individuals often process verbal arguments obtained in conversation or from media presentations, and observe the behavior of others. We review here evidence concerning how these activities cause beliefs and behaviors to spread, affect financial decisions, and affect market prices; and theoretical models of social influence and its effects on capital markets. Social influence is central to how information and investor sentiment are transmitted, so thought and behavior contagion should be incorporated into the theory of capital markets
“This hypothesis is that investors have limited attention; that they allocate this attention to an important indicator of value added, historical earnings; and that this comes at the cost of neglecting the incremental information contained in cash flow measures of value added.”
Abstract (Via SSRN)
If investors have limited attention, then accounting outcomes that saliently highlight positive aspects of a firm’s performance will promote high market valuations. When cumulative accounting value added (net operating income) over time outstrips cumulative cash value added (free cash flow), it becomes hard for the firm to sustain further earnings growth. When the balance sheet is ‘bloated’ in this fashion, we argue that investors with limited attention will overvalue the firm, because naïve earnings-based valuation disregards the firm’s relative lack of success in generating cash flows in excess of investment needs. The level of net operating assets, the difference between cumulative earnings and cumulative free cash flow over time, is therefore a measure of the extent to which operating/reporting outcomes provoke excessive investor optimism. Therefore, if investor attention is limited, net operating assets will negatively predict subsequent stock returns. In our 1964-2002 sample, net operating assets scaled by beginning total assets is a strong negative predictor of long-run stock returns. Predictability is robust with respect to an extensive set of controls and testing methods.
Abstract (via SSRN)
We document strong persistence in the performance of trades of individual investors. The correlation of the risk-adjusted performance of an individual across sample periods is about 10 percent. Investors classified in the top performance decile in the first half of our sample subsequently outperform those in the bottom decile by about 8 percent per year. Strategies long in firms purchased by previously successful investors and short in firms purchased by previously unsuccessful investors earn abnormal returns of 5 basis points per day. These returns are not confined to small stocks nor to stocks in which the investors are likely to have inside information. Our results suggest that skillful individual investors exploit market inefficiencies to earn abnormal profits, above and beyond any profits available from well-known strategies based upon size, value, or momentum. Findings (via SSRN)
Recent literature has emphasized that on average individual investors are misguided in their trades. We provide evidence here that some individual investors are persistently able to beat the market. Traders that can be classified among the top 10 percent (based on the performance of their other trades) buy stocks that earn abnormal returns of between 12 and 15 basis points per day during the following week. These findings are robust to different forms of risk adjustment, to the removal of small stocks from the sample, and to the removal of any firms in which the account has traded more than once. Similarly, there are also individual investors who consistently place underperforming trades. Traders classified among the bottom 10 percent of all traders place trades that can expect to lose up to 12 basis points per day during the subsequent week. In long horizon (holding period) returns, successful investors outperform unsuccessful investors by about eight percent per year. A trading strategy that exploits the information in investors’ trades earns risk-adjusted returns of about five basis points per day.
Finally, this evidence does not support the efficientmarket hypothesis. The ability of individual traders at a discount brokerage to select outperforming companies is not confined to small firms or to only a few firms in which the traders transact frequently; and some investors persistently trade so as to underperform. These findings suggest that investors’ persistent abnormal performance is not derived primarily from trading on inside information.
As part of a groundbreaking new Initiative for the Theoretical Sciences (ITS), the Graduate Center presents a talk by Marc Potters, co-CEO of Capital Fund Management, one of France’s oldest alternative investment management firms. After a Ph.D. in Physics from Princeton University and postdoctoral work at the University of Rome, Potters joined CFM, where he now serves as director of research.
He has made substantial contributions to many problems in quantitative finance, and is the coauthor, with Jean-Phillippe Bouchaud, of the major modern text on these issues, Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management (Cambridge University Press, 2003). His work, and that of his colleagues, shows how theoretical ideas developed to understand one part of the world find application in unexpected places.
After my interview with James Montier, I received several emails asking for additional information on reverse dcfs. Luckily we have wonderful readers, one of them named Kevin, who has emailed me a paper on the use of reverse dcfs. I recommend reading this as it follows the Mauboussin Rappaport model from the book Expectations Investing.
Rappaport and Mauboussin (2001) introduce the idea of price-implied expectations. They argue that the approach of deriving intrinsic value of the firm ignores important information embedded in current stock prices. They, therefore, propose to compute the implied parameters from current market value. This section next briefly summarizes what other information might be reflected in current market prices and then outlines how one can impute parameters from market prices. Finally, Required Business Performance is introduced.
Whatever the view on efficient markets, most agree that prices reflect, albeit imperfectly, publicly available information as well as private information. While individual investors can differ in their views on the firm value, they can be more or less bullish on any given stock, the market price observed at any point in time reflects the views of many different
investors. The source of individuals’ disagreement in assessment of value is their interpretation of public information and possibly any private information that they may have.
Two studies were conducted among professional security analysts to explore their patterns of decision making while managing investment portfolios. In study 1, a computer-based simulation, the analysts’ styles differed markedly, with most exhibiting either a momentum or contrarian approach, as indicated by responses to portfolio stock price changes. Study 2 used a verbal protocol procedure and semistructured depth interviews to probe the analysts’ thought processes. Momentum and contrarian investors were found to differ on a number of dimensions including price expectations, age, experience, raw performance, risk propensity, cognitive style, knowledge calibration, and strategy adaptivity. Implications and limitations are discussed.
Despite its prominent role in contemporary society, surprisingly little is known about the informationprocessing and decision-making strategies of professional stock market investors. A strict interpretation of traditional finance theory, with its focus on aggregate marketplace behavior, would suggest that investors are rational meanvariance optimizers operating in an efficient market where stock prices reflect their true values (Bodie, Kane, and
Marcus 1999). The nascent field of behavioral finance theory has challenged several of the assumptions of the traditional paradigm. Theorists such as Shiller (1993), De Bondt and Thaler (1985), and Shefrin and Statman (1993) have attempted to provide psychological explanations for the emerging empirical evidence of marketplace anomalies at odds with efficient-market theory. Our research explores which, if either, of these approaches is exhibited by the cognitive processing and investment decision-making of professional security analysts who take part in two stockpicking simulations.
The behavioral finance framework suggests that the collective impact of individual decision makers’ psychological biases may cause stock prices to be temporarily over- or underpriced relative to their true economic value (e.g., Shiller 1993). In support of this view, it has been shown that investors often overreact, for example, by excessively bidding down a stock price after learning of negative firm news. Graham and Dodd (1934), recognizing this possibility, were some of the earliest proponents of a contrarian approach to investment. They suggested that, because the market as a whole tends to overreact to negative news, some firms’ stocks temporarily become undervalued and thus represent buying opportunities. De Bondt and Thaler (1985) carried this notion further by suggesting not only that in vestors overreact to negative news but also that they overreact to positive news, resulting in overpriced stocks. Because of these tendencies, contrarian investors often expect that stocks that have fallen in value will rebound and that stocks that have risen in value will fall. Thus a typical contrarian investor buys out-of-favor stocks and sells popular stocks. Some studies have found support for contrarian approaches to investment under certain market conditions (e.g., Basu 1977).
The findings from both studies reported here suggest that the security-analysis decision-making process is heterogeneous and multifaceted but not random in nature. In both studies, two distinct information-processing and decision making styles emerged: momentum and contrarian. These two types of investors differed on a number of dimensions. Most notably, they inferred opposite meanings from price changes of stocks held in their portfolios. Momentum investors generally expected recent stock price trends to continue. Momentum investors favored growth stocks, those that had been exhibiting continued price increases, whether or not the increases were justified by economic fundamentals. Idiosyncratic variations of this theme emerged, such as a focus on small-cap stocks or a search for peaks and troughs. The contrarians expected stock price reversals. They typically divested themselves of stocks they owned whose prices had risen and bought more of stocks they owned whose prices had fallen. The contrarians looked for bargains, stocks they believed to be temporarily undervalued due to the market’s overreaction to negative news, and they avoided glamour stocks, those they believed were overvalued, as indicated by fundamental factor analysis. Idiosyncratic variations of this core strategy were evident in terms of the metrics deemed most relevant to assess firm value (e.g., liquidity vs. earnings measures).
Introduction (via Youtube & Erwin)
Nobel Laureate William F. Sharpe explains how futile it is to read sure-thing investing books or watch the latest financial guru to find easy answers on weathering the financial crisis or filling the holes in your portfolio. Sharpe is the Stanco 25 Professor of Finance Emeritus and Nobel Laureate. Part of a series discussion on “Stanford Pioneers in Science”, a program sponsored by Stanford Continuing Education. Interviewed by Paul Costello, communication and public affairs director, School of Medicine Story: www.gsb.stanford.edu Recorded: October 7, 2009 Watch The VIdeo Below Or Click Here For Your Subscribers
