Small-sample tests for stock return predictability with possibly non-stationary regressors and GARCH-type effects

Arbeitspapier

We develop a simulation-based procedure to test for stock return predictability with multiple regressors. The process governing the regressors is left completely free and the test procedure remains valid in small samples even in the presence of non-normalities and GARCH-type effects in the stock returns. The usefulness of the new procedure is demonstrated both in a simulation study and by examining the ability of a group of financial variables to predict excess stock returns. We find robust evidence of predictability during the period 1948-2014, driven entirely by the term spread. This empirical evidence, however, is much weaker over subsamples.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Bank of Canada Staff Working Paper ; No. 2017-10

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Information and Market Efficiency; Event Studies; Insider Trading
• Subject: Econometric and statistical methods ; Asset pricing ; Financial markets

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gungor, Sermin ; Luger, Richard
• Event: Veröffentlichung
• (who): Bank of Canada
• (where): Ottawa
• (when): 2017

Further information

• DOI: doi:10.34989/swp-2017-10
• Handle: http://hdl.handle.net/10419/197935
• Last update: 10.03.2025, 11:44 AM CET