Article ID: | iaor20043647 |
Country: | Netherlands |
Volume: | 19 |
Issue: | 3 |
Start Page Number: | 369 |
End Page Number: | 385 |
Publication Date: | Jul 2003 |
Journal: | International Journal of Forecasting |
Authors: | Fang Yue, Xu Daming |
Keywords: | time series & forecasting methods |
We investigate predictability of asset returns by developing an approach that combines technical analysis and conventional time series forecasts. While exploiting components as functions of past prices or returns, technical trading rules and time series forecasts capture different aspects of market predictability: the former tends to identify periods to be in the market when returns are positive and the latter is capable of identifying periods to be out when returns are negative. Applied to daily Dow Jones Averages over the first 100 years, the combined strategies outperform both technical trading rules and time series forecasts. The predictability can be explained largely by non-trivial low-order correlations in returns and is not mainly attributable to measurement errors arising from non-synchronous trading.