Forecasting the Equity Risk Premium: The Role of Technical Indicators

• 成果类型: Article
• 署名作者: Neely, Christopher J.; Rapach, David E.; Tu, Jun; Zhou, Guofu
• 署名单位: Federal Reserve System - USA; Federal Reserve Bank - St. Louis; Saint Louis University; Singapore Management University; Washington University (WUSTL)
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2013.1838
• 发表日期: 2014
• 页码: 1772-1791
• 关键词: equity risk premium predictability; Macroeconomic variables; Moving averages; momentum; volume; Sentiment; Out-of-sample forecasts; asset allocation; business cycle

摘要

Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the predictive ability of technical indicators with that of macroeconomic variables. Technical indicators display statistically and economically significant in-sample and out-of-sample predictive power, matching or exceeding that of macroeconomic variables. Furthermore, technical indicators and macroeconomic variables provide complementary information over the business cycle: technical indicators better detect the typical decline in the equity risk premium near business-cycle peaks, whereas macroeconomic variables more readily pick up the typical rise in the equity risk premium near cyclical troughs. Consistent with this behavior, we show that combining information from both technical indicators and macroeconomic variables significantly improves equity risk premium forecasts versus using either type of information alone. Overall, the substantial countercyclical fluctuations in the equity risk premium appear well captured by the combined information in technical indicators and macroeconomic variables.