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Investing Research Articles

Scared by Randomness?

How often should an investor/trader check the performance of their positions? Does it make a difference (psychologically) whether one checks frequently or infrequently? In their 2005 paper entitled “The Scaling Property of Randomness: The Impact of Reporting Frequency on The Perceived Performance of Investment Funds”, Nigel Finch, Guy Ford, Suresh Cuganesan and Tyrone Carlin use actual investment fund performance data to explore the likelihood that an investor would have viewed the performance as positive or negative based on sampling frequency. Applying prospect theory (a loss in wealth has a negative impact 2.25 times greater in magnitude than the positive impact of a gain in wealth) to data for four large Australian investment funds (see table below), they conclude that: Keep Reading

Focus on Return on Investment, Not P/E

Can one calculate what the return from the overall stock market, or from a specific stock, should be? In the never-ending quest to achieve this goal, Hollister Sykes presents his recent “An Equity Market Model and Its Implications”. This model calculates investor return as a function of four variables: (1) earnings yield; (2) return on equity; (3) ratio of dividend payout to earnings; and, (4) ratio of share repurchases or sales value to earnings. Model details and implications, and the results of testing it with 133 years of aggregate market data, are as follows: Keep Reading

Measuring Company Management Sentiment

Market mavens look at consumer, investor, analyst and forecaster sentiments. What about the sentiment of the executives of a company of interest? Does what they think about the prospects for their company matter? How can investors determine what they think? In the April 2006 version of his paper entitled “Do Stock Market Investors Understand the Risk Sentiment of Corporate Annual Reports?”, Feng Li examines the relationship between management risk sentiment and future company earnings and stock returns. Managers arguably have more freedom to express themselves in text than with numbers. Using counts of words related to risk or uncertainty in 34,180 Securities and Exchange Commission (SEC) Form 10-Ks filed between calendar years 1994 and 2005 to measure management risk sentiment, he concludes that: Keep Reading

Jack Schannep on Market Timing and Current Market Conditions

Our Guru Grades section ranks a group of 29 stock market experts according to our assessments of the accuracy of their stock market forecasts. Since Jack Schannep has been in the upper tier of the list since inception, we asked him to encapsulate his thinking on market timing as a guest entry for this blog. He graciously agreed. Here is Jack Schannep on market timing: Keep Reading

Global Pricing of Large-capitalization Stocks?

As worldwide economic participation broadens and deepens, are large companies (more than small companies) becoming internationally owned and therefore priced? In other words, are large companies subject to a worldwide equity risk premium while small companies remain moored to local risk premiums? In his paper entitled “Financial Integration and the Price of World Covariance Risk: Large vs. Small-cap Stocks” (forthcoming in the Journal of International Money and Finance), Wei Huang investigates whether global pricing is peculiar to large-capitalization stocks. Using three size-based stock portfolios for nine developed countries (Australia, Netherlands, Canada, France, Germany, Italy, Japan, U.K. and U.S.) over the period 1980-2004, he concludes that: Keep Reading

VIX as an Indicator for Different Kinds of Portfolios

Implied volatility, represented by the CBOE Volatility Index (VIX), incorporates the bets of speculators on future stock market behavior. In the April 2006 revision of their paper entitled “Implied Volatility and Future Portfolio Returns”, Prithviraj Banerjee, James Doran and David Peterson examine whether the predictive power of VIX applies to specific portfolio characteristics (value versus growth, small versus large and beta) and whether variations in VIX with respect to its short-term mean are predictive. Using data from June 1986 through June 2005 and future return periods of 22 and 44 trading days, they find that: Keep Reading

Predicting Stock Returns Not with Volatility, But Volatilities

Conventional wisdom holds that high (low) overall stock market volatility forecasts high (low) stock returns, as a fundamental reward-for-risk phenomenon. In their March 2006 paper entitled “Understanding Stock Return Predictability”, Hui Guo and Robert Savickas investigate a refinement to volatility-based prediction of stock market returns by combining the effects of realized overall market volatility and the average realized idiosyncratic volatility of individual stocks. They theorize that: (1) overall stock market volatility reflects the volatilities of both cash flow shocks and discount rate shocks; (2) overall stock market volatility overstates discount rate shock volatility; and, (3) average idiosyncratic volatility, which reflects the volatility of discount rate shocks only, corrects this overstatement. Using quarterly overall and idiosyncratic volatilities from 1927 through 2005, they conclude 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

Ken Fisher on Market Analysis

Guru Grades ranks a group of 29 stock market experts according to our assessments of the accuracy of their stock market forecasts. Since Ken Fisher, CEO of Fisher Investments, has been at or near the top of the list since inception, we asked him to encapsulate his thinking on anticipating financial markets. He graciously agreed. Here is Ken Fisher on market analysis: Keep Reading

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