Animal Spirits

Do investment choices derived from experiencing and visualizing returns differ from those derived from analyzing numerical return distribution statistics? In their May 2010 paper entitled “How Much Risk Can I Handle? The Role of Experience Sampling and Graphical Displays on One’s Investment Risk Appetite”, Emily Haisley, Christine Kaufmann and Martin Weber examine how different types of five-year investment performance information (numerical statistics, simulations of portfolio allocation outcomes, graphical displays of the distribution of these outcomes and a simulation/graphics combination) influence the investment risk taking of individuals in an experimental setting. Using data from a series of three experiments in which 133 German, 188 American and  362 American participants choose allocations to a risk-free and a risky asset, they conclude that: Keep Reading

In the opening paragraphs of his April 2010 article entitled “Traditional vs. Behavioral Finance”, Robert Bloomfield handicaps his subject contest as follows:

“The traditional finance researcher sees financial settings populated not by the error-prone and emotional Homo sapiens, but by the awesome Homo economicus. The latter makes perfectly rational decisions, applies unlimited processing power to any available information, and holds preferences well-described by standard expected utility theory. Anyone with a spouse, child, boss, or modicum of self-insight knows that the assumption of Homo economicus is false.”

Might some other frame of reference relieve the asserted asymmetry in self-insight and more equally burden the contestants, rationalist and irrationalist? Keep Reading

In his 2010 book entitled The Little Book of Behavioral Investing: How Not to Be Your Own Worst Enemy, author James Montier states: “I…highlight some of the most destructive behavioral biases and common mental mistakes that I’ve seen professional investors make. I’ll teach you how to recognize these mental pitfalls while exploring the underlying psychology behind the mistake. Then I show you what you can do to try to protect your portfolio from their damaging influence on your returns.” Biases he surveys include: action bias, bias for stories, confirmation bias, conformity bias (herding or groupthink), conservatism (including sunk cost fallacy), disposition effect, empathy gap, endowment effect, hindsight bias, illusion of control, inattentional blindness, information overload, loss aversion, myopia, overconfidence, overoptimism, placebo effect, self-attribution bias and self-serving bias). Value investing provides the context for discussion. Citing a number of studies, he concludes that: Keep Reading

What makes individual investors trade more or less? In the March 2010 version of their paper entitled “Success/Failure of Past Trades and Trading Behavior of Investors”, Sankar De, Naveen Gondhi, Vishal Mangla and Bhimasankaram Pochiraju investigate how trading results affect future trading. Using detailed trading histories for 1.32 million individual Indian investors  involving 111 million transactions worth $85 billion in S&P CNX Nifty stocks during January 2006 through June 2006, they find that: Keep Reading

What types of corporate news have the most impact on stock price? In their February 2010 paper entitled “Market Reaction to Corporate News and the Influence of the Financial Crisis”, Andreas Neuhierl, Anna Scherbina and Bernd Schlusche analyze immediate stock return, volatility and liquidity reactions to various types of corporate news (focusing on one day before to five days after release date). They segment news releases into nine major categories and 52 subcategories. Using a comprehensive sample of 285,917 corporate press releases carried by all major news wire services between April 2006 and August 2009, they find that: Keep Reading

How can an advisor accurately gauge and effectively respond to the risk tolerance(s) of an advisee? In their January 2010 paper entitled “Beyond Risk Tolerance: Regret, Overconfidence, and Other Investor Propensities”, Carrie Pan and Meir Statman: (1) argue that the typical questionnaire used to assess advisee risk tolerance is deficient for five reasons; and, (2) offer remedies for these deficiencies. Using historical asset class return data and results of multiple investor surveys, they conclude that: Keep Reading

In his 2009 book Trading from Your Gut: How to Use Right Brain Instinct & Left Brain Smarts to Become a Master Trader, author Curtis Faith uses stories and examples to “show how to develop your intuition and confidence in the decisions of your gut instinct so that you can use your whole mind while trading.” He preempts left-brained skeptics as follows: “If you are one of those traders who doesn’t believe that gut instinct or intuition has any place in trading, I invite you to keep an open mind. I, too, once felt as you did. After all, I was trained to take a very systematic and logical approach to trading… I believed that it was important to keep your emotions in check.” Some notable points from the book are: Keep Reading

A reader commented: “Re ‘Clustering of Market Closes Near Round Numbers?’, the situation in which clustering is important is at option expiration on stocks with heavily traded options. Professional option writers maximize profit when the underlying stock closes near to the strike price at which the open interest is highest. Look at GOOG and how close it gets to a number divisible by $10 on that one day a month. The odds of closing exactly on such a number are 1/1000. Look at May 15: $390.00. Only the August expiration price for GOOG was not close to a ’10’ number.” Keep Reading

There is a fair amount of research on clustering of prices for individual stocks and other assets near round numbers. (For examples, search the Social Science Research Network for “price clustering”.) Do closing levels of the S&P 500 Index tend to cluster near round numbers? To investigate, we count the number of daily closes for adjacent 10-point ranges of the S&P 500 Index from one centered on 500 to one centered on 1570. The first range in the sample is therefore 495-505 and the last is 1565-1575. Using all closes of the index above 495 (roughly since 1995), we find that: Keep Reading

Do sleep disruptions from switches between standard time and daylight saving time reliably affect the return on the next trading day? In their September 2009 paper entitled “The Daylight Saving Time Anomaly in Stock Returns: Fact or Fiction?”, Russell Gregory-Allen, Ben Jacobsen and Wessel Marquering revisit this question based on a much larger sample than used in prior studies. Using daily returns of stock market indexes around switches to/from daylight saving time for 22 countries around the world spanning 1966-2005 (1,150 switches, tilted toward later decades), they conclude that: Keep Reading