Big Ideas

Does high-frequency trading amplify noise and thereby reduce the signal-to-noise ratio in stock returns? In his August 2010 paper entitled “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Frank Zhang examines the effect of high-frequency trading on stock price volatility and on incorporation of fundamental news into price. He defines high-frequency trading as that driven by fully automated trading strategies with very high trading volume and extremely short holding periods ranging from milliseconds to minutes and possibly hours (typically not overnight). He estimates the volume of high-frequency trading as the residual after accounting for institutional and individual investor activities. Using price, trading and institutional holdings data for a broad sample of U.S. stocks from the first quarter of 1985 through the second quarter of 2009, he finds that: Keep Reading

How stable are risk premiums? How should investors respond to instabilities? In his August 2010 paper entitled “A New ‘Risky’ World Order: Unstable Risk Premiums: Implications for Practice”, Aswath Damodaran presents approaches for estimating equity, bond and real asset risk premiums that are imprecise, unstable and linked across markets. He also explores the implications of dynamic, linked premiums for asset allocation, market timing and asset valuation. Using long-run data for all three asset classes, he concludes that: Keep Reading

A reader commented and asked: “I frequently read that stock prices are not normally distributed, and that by assuming they are, an investor will tend to underestimate market risk. One paper I read says their distribution is leptokurtic, a distribution that has a more acute peak around the mean (that is, a higher probability than a normally distributed variable of values near the mean) and fatter tails (that is, a higher probability than a normally distributed variable of extreme values). My question is, given this fact, is there a practical way for retail investors who are not statisticians and who don’t have access to sophisticated tools, to better estimate risks than using functions that assume a normal distribution?” Keep Reading

Can investors count on stock markets reverting to some valuation benchmark? In their March 2010 paper entitled “Mean Reversion in International Stock Markets: An Empirical Analysis of the 20th Century”, Laura Spierdijk, Jaap Bikker and Pieter van den Hoek analyze reversion of 17 developed country stock market indexes to a valuation benchmark based on a world stock market index. Using annual index data spanning 1900-2008 (109 years), they find 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

Careful assessment of the exploitability of premiums or anomalies derived from long-run series such as stock indexes requires consideration of contemporaneous trading frictions. How have frictions changed over time? In the May 2002 version of his paper entitled “A Century of Stock Market Liquidity and Trading Costs”, Charles Jones assembles annual long-run series of three components of aggregate liquidity: (1) proportional bid-ask spreads for large-capitalization NYSE stocks (1900-2000); (2) proportional commissions for NYSE stocks (1925-2000); and, (3) turnover for NYSE stocks (1900-2000). He applies these series to explore the relationship between stock market returns and aggregate liquidity over time. Using a range of sources to calculate bid-ask spreads for the Dow Jones/DJIA stocks and commission, volume and return data for a broader sample of NYSE stocks, he finds that: Keep Reading

Does designated creditworthiness, closely related to riskiness, drive the performance of many widely acknowledged stock return anomalies? In the April 2010 revision of their paper entitled “Anomalies and Financial Distress”, Doron Avramov, Tarun Chordia, Gergana Jostova and Alexander Philipov use portfolio sorts and regressions to investigate the relationship between financial distress (low credit ratings and downgrades) and profitability for trading strategies based on: stock price momentum, earnings momentum, credit risk, analyst earnings forecast dispersion, idiosyncratic volatility, asset growth, capital investments, accruals and value. Using data for broad samples of U.S. stocks (limited by extensive information requirements) spanning October 1985 through December 2008, they conclude that: Keep Reading

Is there a common factor explaining multiple widely accepted stock return anomalies? In the March 2010 version of their paper entitled “Do Five Asset Pricing Anomalies Share a Common Mispricing Factor?Multifaceted Empirical Analyses of Failure Risk Proxies, External Financing, and Stock Returns” , Joseph Ogden and Julie Fitzpatrick investigate the ability of a single factor, involving operating profit and external financing, to explain five stock return  anomalies: (1) the failure-risk anomaly; (2) earnings momentum; (3) the external financing (stock buybacks/secondary offerings) anomaly; (4) the accruals anomaly; and, (5) the book-to-market anomaly.  Using monthly stock return and firm fundamentals data for a broad sample of U.S. stocks to form 205 portfolios over the period 1974-2008 (60,301 firm-year observations), they find that: Keep Reading

Does demographic mix of a set of investors affect aggregate demand for yield, and thereby total returns, from equity investments? In the December 2009 version of their paper entitled “Demographic Trends, the Dividend/Price Ratio and the Predictability of Long-Run Stock Market Returns”, Carlo Favero and Arie Gozluklu investigate the relationship between the aggregate stock dividend yield and the ratio of middle-aged (40-49) to young (20-29) populations in the U.S. (M/Y). Using U.S. demographic and aggregate equity dividend and price data spanning 1900-2008, they conclude that: Keep Reading

Can investors beat the market by iteratively finding and exploiting the current hot anomaly? In the September 2009 update of his paper entitled “Real-Time Profitability of Published Anomalies: An Out-of-Sample Test”, Zhijian Huang investigates whether a trader can realize excess returns by repeatedly picking the anomaly with the best return during a rolling historical window from an expanding universe of anomalies as published, with a specific objective of suppressing data snooping bias. The universe includes anomalies that: (1) have been published in at least one of five top-ranked finance journals; (2) relate to the calendar or to cross-sectional predictability; and, (3) can be re-evaluated annually. Using monthly return data associated with 11 anomalies published during 1972-2005 (Monday/weekend effect, January effect and cross-sectional effects related to size, book-to-market ratio, momentum, earnings-price ratio, cash flow-price ratio, dividend yield, debt-equity ratio, sales growth and trading volume/turnover) as available from 1926 through 2008, he concludes that: Keep Reading