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Investing Expertise

Can analysts, experts and gurus really give you an investing/trading edge? Should you track the advice of as many as possible? Are there ways to tell good ones from bad ones? Recent research indicates that the average “expert” has little to offer individual investors/traders. Finding exceptional advisers is no easier than identifying outperforming stocks. Indiscriminately seeking the output of as many experts as possible is a waste of time. Learning what makes a good expert accurate is worthwhile.

If You Are in the Market for an Investment Advisor…

…you may be seeing something like this: Keep Reading

How Investors Do (or Don’t) Take Advice

How do typical investors/traders process advice from others? Are they overconfidently dismissive, or underconfidently trading on the latest guru pronouncement? In their February 2006 paper entitled “Effects of Task Difficulty on Use of Advice”, Francesca Gino and Don Moore perform two controlled experiments to examine the tendencies of people to reject or accept advice depending on the complexity of the associated task. In one experiment, the 61 participants (mostly university students) must seek advice, and in the other they have the option of seeking advice. Since the advice came from other participants who were generally no better informed, the best strategy for each participant was to reduce noise by averaging own opinion and advisor’s opinion. Based on the results of these experiments, the authors conclude that: Keep Reading

Classic Paper: Any Excess Returns from Investment Newsletters?

Are newsletters good sources of stock picks? Specifically, do their recommendations persistently generate excess returns? In their October 1998 paper entitled “The Performance of Investment Newsletters”, Jeffrey Jaffe and James Mahoney tackle these questions. Using the investment newsletter archive of the Hulbert Financial Digest for 1980-1996, they determine that: Keep Reading

Are Individual Investors Entrepreneurs? If So…

Is success as an entrepreneur all luck, or is there a provable contribution from skill? Do winners win just because they are willing to roll the dice, or because they consistently bring innovative insights to the market? In their July 2006 paper entitled “Skill vs. Luck in Entrepreneurship and Venture Capital: Evidence from Serial Entrepreneurs”, Paul Gompers, Anna Kovner, Josh Lerner and David Scharfstein pit skill against luck by investigating the persistence of success among serial entrepreneurs. Focusing on the founders of companies listed by Venture Source as recipients of venture capital during the period 1975-2000, they conclude that: Keep Reading

Holding Court with Stock Market Gurus

Suppose investors/traders were to apply the same standards to a stock market guru that federal courts apply to an expert witness. What, if anything, would they find admissible? Using as a guide the 2003 paper by Jennifer Mnookin and Samuel Gross entitled “Expert Information and Expert Evidence: A Preliminary Taxonomy”, we conclude that: Keep Reading

Stock Picking in a “Fruit Fly Lab”

Does a natural selection metaphor apply to stock picking models? In other words, can competition among a large set of dynamic models to mimic historical stock performance data evolve the most fit models? In their May 2006 paper entitled “Stock Selection – An Innovative Application of Genetic Programming Methodology”, Ying Becker, Peng Fei and Anna Lester address these questions by applying genetic programming to stock picking. Genetic programming enables the testing of a wide range of stock performance indicators in linear, non-linear and non-obvious combinations. The authors choose the S&P 500, excluding financials and utilities, as their universe of stocks and define two distinct types of stock-picking model fitness: (1) risk-adjusted outperformance compared to a traditional stock-picking model; and, (2) highest possible return independent of risk. They construct for comparison a traditional stock return forecasting model based on a linear combination of four composite factors: valuation, quality, analyst expectations and price. They use monthly data (65 variables for each of about 350 stocks) over the period January 1990 through December 2005 to create environments for model development and out-of-sample testing. They show that: Keep Reading

Classic Article: Seer-Suckers, or the Efficient Everything Hypothesis

In his article entitled “The Seer-Sucker Theory: The Value of Experts in Forecasting” from the June/July 1980 issue of Technology Review, Scott Armstrong investigates the general supply of and demand for expertise across several disciplines. Based upon his survey of decades of research in multiple fields (including financial markets, psychology, health care, politics, sports), he concludes that: Keep Reading

Expert Political Judgment: How Good Is It? How Can We Know? (Chapter-by-Chapter Review)

In his 2005 book Expert Political Judgment: How Good is It? How Can We Know?, Philip Tetlock describes the results of his long-term systematic measurement of the forecasting abilities of political experts. These results include insights into the critical success factors of forecasting. Making the very small leap that these insights apply also to experts in economics and financial markets, we offer here a chapter-by-chapter review of the insights in this book: Keep Reading

Who Reads Yahoo! Message Boards?

We get a varying flow of traffic from Yahoo! message boards, usually from boards of “Cramerized” stocks to either our review of Jim Cramer’s market timing record or our evaluation of his stock picking ability. Who reads these stock boards? Using a sample of 212 unique Internet Protocol (IP) addresses for readers recently visiting from five different Yahoo! message boards, we find that: Keep Reading

The Secret Ingredients of Top Analysts?

What makes a guru, or analyst, good? The research on this question is predominantly “technical” rather than “fundamental,” focusing on performance and performance persistence rather than process (hence, the frequent use of the word guru, implying mystical insight). In their preliminary and incomplete paper of November 2004 entitled “Determinants of Superior Stock Picking Ability”, Michael Mikhail, Beverly Walther, Xin Wang and Richard Willis seek to identify the determinants of consistent analyst stock picking outperformance. Using a sample encompassing 268,170 recommendations issued by 4,923 analysts for 7,845 firms during 1985-1999 from Zacks Investment Research, they tentatively find that the best analysts tend to: Keep Reading

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