Fundamental Valuation

Can investors enhance momentum returns for individual stocks with combination strategies that incorporate other technical and accounting indicators? In the April 2010 draft of their paper entitled “Technical, Fundamental, and Combined Information for Separating Winners from Losers”, Cheng-Few Lee and Wei-Kang Shih investigate combined momentum strategies based on past stock returns, past trading volume and sets of fundamental (accounting) indicators. They consider two distinct sets of fundamentals: Piotroski’s FSCORE for value stocks and Mohanram’s GSCORE for growth stocks. Their combined strategy is long (short) past winners (losers) with weak (strong) past relationship between returns and trading volume and high (low) fundamental scores. Using stock return/volume and firm fundamentals data for a broad sample of NYSE and AMEX non-financial stocks spanning 1982-2007 (26 years), they find that: Keep Reading

We occasionally select for retrospective review an all-time “best selling” research paper of the past few years from the General Financial Markets category of the Social Science Research Network (SSRN). Here we summarize the April 2004 version of the paper entitled “Separating Winners from Losers among Low Book-to-Market Stocks using Financial Statement Analysis” (download count over 5,800) by Partha Mohanram. The study tests the ability of a stock scoring system (GSCORE) based on eight binary signals derived from profitability and growth-specific financial measures (see the list below) to predict future returns. Using stock returns and firm fundamentals for the fifth of a broad sample of U.S. firms with the lowest book-to-market ratios over the period 1979-1999, the author concludes that: 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

Are there ways to concentrate the predictive power of accruals for future individual stock and equity market returns? Two recent papers explore potential refinements. In the January 2010 draft of their paper entitled “Predicting Stock Market Returns with Aggregate Discretionary Accruals”, Qiang Kang, Qiao Liu and Rong Qi focus on whether aggregate discretionary accruals (distinguished from normal accruals) are a better predictor of stock market returns than aggregate total accruals. In their February 2010 paper entitled “Percent Accruals”, Nader Hafzalla, Russell Lundholm and Matt Van Winkle investigate scaling firm-level accruals by earnings rather than total assets to predict returns for individual stocks. These studies conclude that: Keep Reading

Since 7/9/09, Christophe Faugère has been publishing (almost) daily “Market Estimates” of the value of the S&P 500 Index based on Required Yield Theory (RYT). RYT views investors as: (1) requiring that U.S. stocks and bonds in aggregate prospectively provide a real after-tax yield directly related to real long-term GDP per capita growth; and then, (2) deciding between stocks and bonds based on the better after-tax real return. To test the predictive power of these market estimates, we focus on daily percentage mismatches between estimated and actual values of the S&P 500 Index [(Estimated-Actual)/Actual] and exploitability of these mismatches via S&P Depository Receipts (SPY). Using daily RYT market estimates and daily levels of the S&P 500 Index and SPY over the period 7/9/09 through 3/3/10 (160 daily model outputs), we find that: Keep Reading

Are stock earnings yield (E/P) and firm book-to-price ratio (B/P) complementary indicators of future stock returns? In their December 2009 paper entitled “Returns to Buying Earnings and Book Value: Accounting for Growth and Risk”, Francesco Reggiani and Stephen Penman investigate the interplay of E/P and B/P in an accounting context, including joint implications for future stock returns. The authors hypothesize that B/P measures the degree to which firms defer recognition of risky earnings. Using monthly stock return and firm financial data for a broad sample of U.S. stocks spanning 1963-2006 (153,858 firm-years over 44 years), 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

A reader asked: “Have you done any backtesting to compare value investing versus market timing? Magic Formula Investing seems to rank #1 in value investing and Decision Moose seems to stand out for market timing. Is there any direct comparison between Magic Formula Investing vs. Decision Moose?” Keep Reading

Does decomposition of widely used valuation ratios into components that reflect long-term trend and shorter-term variation from trend reveal predictability? In their November 2009 paper entitled “Do Decomposed Financial Ratios Predict Stock Returns and Fundamentals Better?”, Xiaoquan Jiang and Bong-Soo Lee explore decomposition of the dividend-price, earnings-price and book-to-market ratios into stochastic trend and cyclical components. The stochastic trend component measures variations in longer-term trend (fundamental structural changes), while the cyclical component measures shorter-term deviations from this trend. The study employs rolling four-quarter sums of dividends and earnings, with the latter smoothed via a ten-year moving average, and accounting data to model older book values. Using quarterly S&P 500 Index returns and valuation metrics for the S&P 500 over the period 1926-2008, they find that: Keep Reading

As espoused by many market commentators, do positive (negative) earnings surprises in fact predict upward (downward) stock market movement? In their January 2010 paper entitled “Aggregate Market Reaction to Earnings Announcements”, William Cready and Umit Gurun investigate the relationship between earnings announcement surprises and market returns, focusing on the days surrounding earnings news. Using quarterly earnings announcements for a broad sample of firms spanning January 3, 1973 through June 21, 2006 (413,687 announcements) and contemporaneous values of a combined NYSE/AMEX index, they find that: Keep Reading