Economic Indicators

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

What kind of economic environment makes a stock market boom? What changes in that environment lead to bust? In their September 2006 paper entitled “When Do Stock Market Booms Occur? The Macroeconomic and Policy Environments of 20th Century Booms”, Michael Bordo and David Wheelock examine the economic and policy conditions that supported equity market booms in ten developed countries (Australia, Canada, France, Germany, Italy, Japan, Netherlands, Sweden, the United Kingdom and the United States) during the 20th century. Using monthly inflation-adjusted stock prices from these countries, they conclude that: Keep Reading

In their February 2003 paper entitled “Stock Returns, Aggregate Earnings Surprises, and Behavioral Finance”,  Jonathan Lewellen, S. Kothari and Jerold Warner explore the relationships between overall stock market behavior and aggregate corporate earnings, looking for parallels with firm-level price-earnings behavior. Using quarterly data for 1970-2000, they conclude that: Keep Reading

Do certain industries tend to lead or lag stock market cycles? In the November 2004 update of their paper entitled “Do Industries Lead the Stock Market?”, Harrison Hong, Walter Torous and Rossen Valkanov investigate whether returns from some industries predict future returns for the overall stock market. The authors hypothesize that the overall market only gradually recognizes valuable information contained in the returns of specific industries. Using U.S. data for 1946-2002 and international data for 1973-2002, they conclude that: Keep Reading

Value and momentum are two very different equity investing styles, both with many adherents. Neither outperforms the overall market all the time. Is there some systematic way of combining these two approaches to enhance consistency of outperformance in global equity markets? In their March 2006 paper entitled “Generating Excess Returns through Global Industry Rotation”, Geoffrey Loudon and John Okunev examine different investing styles (momentum, value, combination of value and momentum, and growth) to exploit cyclic industry returns, with the U.S. yield curve as the critical economic indicator. Using monthly global prices, dividends, earnings and returns data for 36 industries for 1973-2005, they conclude that: Keep Reading

Do forecasts for the economy at large predict returns for stock investors? In the September 2005 version of their paper entitled “Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence”, Sean Campbell and Francis Diebold characterize the relationship between expected business conditions (predictions of real growth in GDP six and 12 months ahead) and stock returns. Using half a century (1952-2002) of Livingston Survey expected business conditions results and corresponding measures of expected stock returns, they conclude that: Keep Reading

In the August 2004 update of their paper entitled “Real-Time Price Discovery in Stock, Bond and Foreign Exchange Markets”, Torben Andersen, Tim Bollerslev, Francis Diebold and Clara Vega investigate the real-time response of U.S., German and British stock, bond and foreign exchange markets to 25 types of U.S. macroeconomic news (such as GDP, PPI, CPI and unemployment rate). They employ actively traded futures as proxies for each of these markets. They measure the degree of surprise in macroeconomic announcements based on the survey-based expectations of market players. Using data from various starting points in the 1990s through the end of 2002, they find that: Keep Reading