Value Premium

Reader Richard Beddard, editor of Interactive Investor, flagged a series of three studies by Keith Anderson and Chris Brooks on approaches to enhancing the value premium via empirical analysis of the price-earnings ratio (P/E) calculated with lagged earnings. One study seeks to optimize value indication based on the extent and weighting of historical earnings used in the P/E calculation. The second study seeks to concentrate the value premium by decomposing P/E into components related to market, firm size, industry and company-specific factors. The third study combines the findings of the first two and examines the returns for the extreme tails of the enhanced P/E distribution. All three studies use earnings and stock return data for a broad range of UK companies (excluding the smallest) for the period 1975-2004. Summaries of the three studies follow. Keep Reading

What causes the value premium, a rational risk factor or an irrational overreaction? If the latter, who overreacts and to what? In his February 2007 paper entitled “Institutional Investors, Intangible Information and the Book-to-Market Effect”, Hao Jiang investigates a connection between the value premium and the trading behavior of institutional investors. Specifically, he tests whether institutions overreact to intangible information (that not derived directly from firm accounting measures). Using data on returns, accounting fundamentals and institutional ownership encompassing 49,164 firm-years over the period 1981-2004, he concludes that: Keep Reading

Attempting to follow long stock market trends is a common investment approach, with much guru attention focused on calling long-term tops and bottoms. Is this approach meaningful for investors as an avenue to improve upon buy-and-hold performance? In the December 2006 version of his paper entitled “Analyzing Regime Switching in Stock Returns: An Investment Perspective”, Jun Tu investigates the potential importance to investors of exploiting differences between bull and bear markets within a Bayesian framework that accommodates considerable uncertainty. Using monthly value-weighted stock return and volatility data for July 1963 to February 2006 (512 observations), he finds that: Keep Reading

Can investors/traders amplify excess returns by combining value investing with stock repurchase activities? In other words, do companies with low price-fundamentals ratios that buy back stock outperform value companies in general? In their recent paper entitled “Corporate Financing Activities and Contrarian Investment”, Turan Bali, Ozgur Demirtas and Armen Hovakimian examine returns for investing strategies that combine value indicators and stock repurchase/issuance activities. Using monthly return data and company financial statements for the period May 1972 to April 2002, they find that: Keep Reading

Are there investing/trading strategies that can turn stock price noise into alpha? More specifically, are there types of stocks for which the noise has a systematic effect on price? In the October 2006 draft of their paper entitled “Does Noise Create the Size and Value Effects?”, Robert Arnott, Jason Hsu, Jun Liu and Harry Markowitz model the cross-sectional effects of mean-reverting noise on randomly walking stock values. Noise (for example, from overreacting, informationally challenged and/or liquidity-driven investors/traders) introduces random transients of inefficiency. Based on this model, they conclude that: Keep Reading

Are value (growth) investors stolid conservatives (wild risk-takers)? If so, is there a way to trade on the difference in behavioral preferences? In their September 2006 paper entitled “Risk Aversion and Clientele Effects”, Douglas Blackburn, William Goetzmann and Andrey Ukhov compare the risk preferences of value and growth investors by examining: (1) option prices for pairs of value-growth indexes, and (2) funds flows for value and growth mutual funds. They further investigate whether any profitable options trading strategies devolve from the difference in risk preferences. Using recent data for five value-growth index pairs and for several value and growth mutual funds, they find that: Keep Reading

If noise is a significant component of stock prices, does a portfolio that favors large market capitalization stocks automatically underperform? In the May 2006 draft of their paper entitled “Pricing Noise, Rejecting the CAPM and the Size and Value Effects”, Robert Arnott and Jason Hsu examine the implications of a very simple model that assumes stock prices deviate from fundamental value based on a single source of unknown risk (noise). They assume the deviations revert to a mean of zero, with no long-term effect on stock returns. Based on this model, they conclude that: Keep Reading

As companies evolve, their characteristics may migrate from one category to another (for example, from small to large, or from growth to value). Does such migration, in aggregate, help explain differences in average returns for different categories of stocks? In the August 2006 draft of their paper entitled “Migration”, Eugene Fama and Kenneth French investigate how migration of firms across categories contributes to the size effect and the value premium. Specifically, at the end of each June from 1926 through 2004 they construct six value-weighted portfolios of stocks from the major U.S. exchanges based on market capitalization and price-to-book ratio. They then examine the effects on portfolio returns of four kinds of annual rebalancing actions: (1) firms that do not move (Same); (2) firms that change size (dSize); (3) firms that improve toward growth, or are acquired (Plus); and, (4) firms that deteriorate toward value, or are delisted (Minus). Using subsequent-year return data for 1927-2005, they conclude that: Keep Reading

We have selected for retrospective review a few all-time “best selling” research papers of the past few years from the General Financial Markets category of the Social Science Research Network (SSRN). Here we summarize the August 2003 paper entitled “Bad Beta, Good Beta” (download count over 1,700) by John Campbell and Tuomo Vuolteenaho. In this research, the authors separate stock beta into two components, one reflecting news about cash flows and one reflecting news about discount rates. They apply this decomposition to explain the size effect and the value premium. They hypothesize that:

[Market] “value…may fall because investors receive bad news about future cash flows; but it may also fall because investors increase the discount rate…that they apply to these cash flows. In the first case, wealth decreases and investment opportunities are unchanged, while in the second case, wealth decreases but future investment opportunities improve. …[A]n investor may demand a higher premium to hold assets that covary with the market’s cash-flow news than to hold assets that covary with news about the market’s discount rates, for poor returns driven by increases in discount rates are partially compensated by improved prospects for future returns. …The required return on a stock is determined not by its overall beta with the market, but by its bad cash-flow beta and its good discount-rate beta. Of course, the good beta is good not in absolute terms, but in relation to the other type of beta.” [Underlining is ours.]

Using monthly returns from an early period (January 1929 through June 1963) and a modern period (July 1963 through December 2001) to test this idea, the authors conclude that: Keep Reading

Conventional wisdom holds that: (1) risk begets reward; and, (2) volatility is a manifestation of risk. Exceptionally high volatility in individual stock prices should, therefore, indicate future excess returns in those stocks. In their May 2006 paper entitled “The Relation between Time-Series and Cross-Sectional Effects of Idiosyncratic Variance on Stock Returns in G7 Countries”, Hui Guo and Robert Savickas investigate why the realized idiosyncratic volatility (beta) of individual stocks correlates negatively with future returns — why there is a penalty instead of a reward for this apparent risk. Using two sets of U.S. data (1926-2005 and 1963-2005) and one set of international data (1973-2003), they conclude that: Keep Reading