Fundamental Valuation

Does old-fashioned value investing still work? In their recent paper entitled “Testing Benjamin Graham’s Net Current Asset Value Strategy”, Ying Xiao and Glen Arnold test Benjamin Graham’s approach to valuation based on net current asset value to market value (NCAV/MV) to see whether it outperforms in a modern market environment. NCAV is current assets minus all current and long-term liabilities, divided by the number of shares outstanding. The strategy assumes that a stock is substantially undervalued when NCAV/MV is 1.5 or greater. Using accounting and return data for stocks listed on the London Stock Exchange during 1980-2005, they find that: Keep Reading

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

How do analyst earnings forecasts vary across financial reporting periods? Does the desire of analysts to maintain a good relationship with firm management affect earnings forecasts? In their February 2007 paper entitled “Relationship Incentives and the Optimistic/Pessimistic Pattern in Analysts’ Forecasts”, Robert Libby, James Hunton, Hun-Tong Tan and Nicholas Seybert report the results of controlled blind experiments involving experienced sell-side financial analysts that address these questions. Using information gained from “training sessions” for a group of 47 analysts from a single large investment banking/brokerage firm and 34 analysts from a medium-sized regional brokerage firm, they conclude that: Keep Reading

Proponents of rational markets build on a common-sense foundation of reward for risk, with price variability (beta) as the fundamental risk. Since this single source of risk does not predict asset prices very well, rationalists have empirically appended to their models other sources of risk (proxied by size, value and momentum factors) in search of better predictions. Proponents of behavioral finance counter with innate cognitive and emotional biases (irrationality) as causes of rational model failures. Is there a way to prove one of these two views more correct? Should rationalists look for additional risk factors? Does some third perspective offer insight? In their January 2007 preliminary paper entitled “Failure of Asset Pricing Models: Transaction Cost, Irrationality, or Missing Factors” Joon Chae and Cheol-Won Yang tackle these questions. Using monthly stock return data for 700 Korean firms over the period December 1997 to November 2004 (84 months), along with associated measures for both potential degree of trader rationality (sophistication) and transaction costs, they conclude that: Keep Reading

Is the Fed Model fit only for statistics-challenged practitioners, or does it offer some trading intelligence? In the January 2007 version of his paper entitled “A Behavioral Defense of the Fed Model”, Michael Clemens combines the concepts of mean reversion of key financial variables and confidence intervals to present a behavioral defense of the Fed model. He examines the version of the model based on the spread between the S&P 500 forward earnings yield (E/P) and the yield on the 10-year Treasury note. His defense includes identification of ten potential chinks in the armor of model detractors. Using monthly data for the period January 1979 through August 2006 (322 monthly observations over 26 years) , he finds that: Keep Reading

How well do commonly used valuation multiples align with actual stock prices? In their January 2007 paper entitled “Multiples and Their Valuation Accuracy in European Equity Markets”, Andreas Schreiner and Klaus Spremann investigate the accuracy of the valuation multiple method in general and the properties of 50 different multiples (see the figure below). They define a valuation multiple as a market price variable (e.g., stock price) divided by a particular value driver (e.g., earnings). Using stock price and firm financial data over the period 1996-2005 primarily for the Dow Jones STOXX 600 (ten industries, 18 supersectors, 39 sectors, and 104 subsectors) and secondarily for the S&P 500 index, they find that: Keep Reading

ave accounting scandals (e.g., Enron, WorldCom and Global Crossing) and the 2002 Sarbanes-Oxley Act (SOX) changed management-analyst earnings dynamics? In their December 2006 paper entitled “Mechanisms to Meet/Beat Analyst Earnings Expectations in the Pre- and Post-Sarbanes-Oxley Eras”, Eli Bartov and Daniel Cohen examine whether companies have changed behaviors post-SOX with respect to accrual earnings management, real (transaction-based) earnings management and earnings expectations management. Using earnings forecast and financial data for thousands of companies during 1987-2005, they conclude that: Keep Reading

Do aggregate earnings guidance and actual aggregate earnings predict overall stock market returns? In his September 2006 paper entitled “Aggregate Earnings, Stock Market Returns and Macroeconomic Activity”, Lakshmanan Shivakumar discusses the relationships among aggregate earnings, stock market returns and the economy. He frames his discussion as commentary on prior research on earnings guidance, earnings news and stock returns. Using earnings, inflation and gross domestic product (GDP) data for 1972-2004, he finds and suggests that: Keep Reading

Deterioration over the past decade in the forecasting power of traditional indicators (such as price-dividend and price-earnings ratios) have stimulated searches for better ones, with recent emphasis on macroeconomic variables. Which financial and economic variables best predict stock returns over the short, intermediate and long terms? Is “best” good enough for market timing? In her October 2006 paper entitled “How Well Do Financial and Macroeconomic Variables Predict Stock Returns: Time-series and Cross-sectional Evidence”, Anne-Sofie Reng Rasmussen evaluates the relative performance of a wide range of variables in forecasting excess stock returns (above the one-month T-bill rate) over horizons from one quarter to eight years. Using annual data for periods as long as 1930-2005 and quarterly data for periods as long as 1926-2005, she concludes that: Keep Reading

Which accounting data is most important in predicting future stock returns? In their July 2006 paper entitled “How Do Accounting Variables Explain Stock Price Movements? Theory and Evidence”, Peter Chen and Guochang Zhang test the predictive power of a model that combines the discount rate with four indicators of company cash flow: (1) earnings yield; (2) capital investment; (3) changes in profitability; and, (4) changes in growth opportunities. Earnings yield indicates current cash flow generation, while the other three factors indicate future changes in cash flow generation. Using annual company-level accounting data and analyst growth forecasts for cash flow indicators (27,897 firm-year observations over the period 1983-2001) and the yield on 10-year Treasury notes for the discount rate, they conclude that: Keep Reading