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Investing Research Articles

Comprehensive Analysis of Calendar Effects

In the January 2005 version of their working paper entitled “Testing the Significance of Calendar Effects”, Peter Reinhard Hansen, Asger Lunde and James Nason test a broad range of possible calendar effects in multiple equity markets. They examine the following effects: day-of-the-week, month-of-the-year, day-of-the-month, week-of-the-month, semi-month, turn-of-the-month, end-of-the-year and holiday. Calendar effects could be a result of data mining (finding anomalies of randomness), an especially plausible explanation when theoretical explanations are suggested only subsequent to empirical “discovery.” Applying robust tests to daily closing prices of stock indices from Denmark, France, Germany, Hong Kong, Italy, Japan, Norway, Sweden, the United Kingdom and the United States through early May 2002, they find that: Keep Reading

When Stock Market Models Crash

Didier Sornette has an interest in financial markets as examples of complex systems. He authored Why Stock Markets Crash : Critical Events in Complex Financial Systems, published in November 2002. He has maintained on his web site for several years a series of predictions regarding the behavior of the S&P 500 index. In initiating this series, he wrote:

“Based on a theory of cooperative herding and imitation working both in bullish as well as in bearish regimes that we have developed in a series of papers, we have detected the existence of a clear signature of herding in the decay of the US S&P 500 index since August 2000 with high statistical significance, in the form of strong log-periodic components.”

His September 2002 paper (with Wei Zhou) entitled “The US 2000-2002 Market Descent: How Much Longer and Deeper?” provides a detailed justification of this assertion, including a comparison of the 1990 Japanese and 2000 U.S. stock market crashes. The evolution of Professor Sornette’s predictions is as follows: Keep Reading

Book (Value) It?

In the September 2005 version of their paper entitled “The Anatomy of Value and Growth Stock Returns”, Eugene Fama and Kenneth French separate the average returns on both value and growth portfolios into dividends and three sources of capital gains: (1) reinvestment of earnings (growth in book value); (2) change in price-to-book ratios (P/B) due to mean reversion in profitability, and (3) a secular upward drift in P/B. Using data spanning 1926-2003 for NYSE, AMEX and NASDAQ stocks, they find that: Keep Reading

Warren Buffett’s Track Record: Luck or Skill?

In their August 2005 paper entitled “Imitation is the Sincerest Form of Flattery: Warren Buffett and Berkshire Hathaway”, Gerald Martin and John Puthenpurackal rigorously examine various possible explanations for Berkshire Hathaway’s superior investment performance. Is it luck? Is it reward-for-risk? Is it outstanding stock-picking skill? Using information on 261 common equity investments from Berkshire Hathaway’s SEC filings and market databases for 1980-2003, they conclude that: Keep Reading

Sophistication + Experience > Behavioral Bias?

In their March 2005 paper entitled “Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?”, Lei Feng and Mark Seasholes analyze how sophistication and trading experience of investors affect their disposition behavioral bias (reluctance to realize losses and propensity to realize gains). They define sophistication based on four factors: number of trading rights; initial level of portfolio diversification; age; and, gender. They define trading experience as the number of positions taken since account initiation. Using data from a national brokerage firm in the People’s Republic of China for 1,511 individual accounts initiated on or after 1/1/99 and monitored through 12/31/00, they conclude that: Keep Reading

Fooled by Randomness: A Review

Nassim Taleb’s central theme in Fooled by Randomness (the 2004 second edition) is that noise generally swamps signal (true outperformance or underperformance) in financial markets, and in life generally. A standard deviation much larger than an associated average excess return, encountered consistently in the search for outperforming investing/trading strategies, is an indicator of such swamping. The book effectively uses corollaries and examples to reinforce Nassim Taleb’s contention that past performance is neither a guarantee of future returns nor a proof of either intelligence or stupidity. Rather than recount his arguments, we focus this review on his conclusions as they relate specifically to speculating in financial markets. These conclusions are: Keep Reading

Brokerage Business Biases Analysts

In the August 2005 draft of their paper entitled “Analyst Conflicts and Research Quality”, Anup Agrawal and Mark Chen examine whether the forecasts quality of stock analysts relates to conflicts of interest from the investment banking and brokerage businesses of their employers. They define forecast quality in terms of: (1) accuracy; (2) bias; (3) frequency of quarterly earnings per share (EPS) forecast revisions; and, (4) relative optimism of long-term earnings growth forecasts. By cross-referencing the forecasts of 3,000 analysts with line-of-business revenue breakdowns for their respective employers (163 different firms) over the period 1994-2003, they find that: Keep Reading

Buying on Impulse (Change in Momentum)

In their September 2005 paper entitled “Acceleration Strategies”, Eric Gettleman and Joseph Marks examine the change in six-month stock price momentum (a second derivative of price with respect to time, which the authors call “acceleration”) for individual companies as a potential indicator of future performance. Does increasing (decreasing) stock price momentum indicate commensurate relative outperformance (underperformance)? Based on monthly data spanning 1926-2003, they conclude that: Keep Reading

Value Versus Growth: The Winner Is…

In their August 2005 paper entitled “Value Versus Growth: Stochastic Dominance Criteria”, Abhay Abhyankar, Keng-Yu Ho and Huainan Zhao apply stochastic dominance techniques to assess the relative performance of value and growth investment strategies in U.S. equity markets over the past half century. These techniques: (1) compare entire return distributions (not just means or medians); (2) are independent of specific asset pricing models; and, (3) require only minimal assumptions about investor preferences. In this application, the assumptions are that investors always want more wealth, are risk-averse and accept small high-probability losses in exchange for huge low-probability returns. With these assumptions, stochastic dominance implies generation of greater wealth. Using a full sample covering 1951-2003 and a sub-sample covering 1963-1990 from the Kenneth French database, they find that: Keep Reading

Individuals => Institutions: One-Way Flow?

In their January 2005 paper entitled “Who Loses from Trade? Evidence from Taiwan”, Brad Barber , Yi-Tsung Lee, Yu-Jane Liu and Terrance Odean investigate wealth transfer between individuals and institutions in financial markets. Using a complete common stock trading history of all investors in Taiwan (the 12th largest financial market in the world) for 1995-1999, they document that: Keep Reading

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