The Long and the Short of It: Long Memory Regressors and Predictive Regressions
AbstractPersistent regressors pose a common problem in predictive regressions. Tests of the forward rate unbiased hypothesis (FRUH) constitute a prime example. Standard regression tests that strongly reject FRUH have been questioned on the grounds of potential long-memory in the forward premium. Researchers have argued that this could create a regression imbalance thereby invalidating standard statistical inference. To address this concern we employ a two-step procedure that rebalances the predictive equation, while still permitting us to impose the null of FRUH. We conduct a comprehensive simulation study to validate our procedure. The simulations demonstrate the good small sample performance of our two-stage procedure, and its robustness to possible errors in the first stage estimation of the memory parameter. By contrast, the simulations for standard regression tests show the potential for significant size distortion, validating the concerns of previous researchers. Our empirical application to excess returns, suggests less evidence against FRUH than found using the standard, but possibly questionable, t-tests.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 384.
Date of creation: 11 Nov 2005
Date of revision:
Long Memory; Predictive Regressions; Forward Rate Unbiasedness Hypothesis;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- F31 - International Economics - - International Finance - - - Foreign Exchange
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-11-19 (All new papers)
- NEP-ECM-2005-11-19 (Econometrics)
- NEP-ETS-2005-11-19 (Econometric Time Series)
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