|
Archive@NYU >
Stern School of Business >
IOMS: Statistics Working Papers >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/28470
|
| Title: | Predictive Regression With Order-p Autoregressive Predictor |
| Authors: | Amihud, Yakov
Hurvich, Clifford M.
Wang, Yi |
| Keywords: | autoregressive
augmented regression method (ARM) |
| Issue Date: | 11-Dec-2009 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | SOR-2009-07; |
| Abstract: | Studies of predictive regressions analyze the case where yt is predicted
by xt-1 with xt being first-order autoregressive, AR(1). Under some
conditions, the OLS- estimated predictive coefficient is known to be
biased. We analyze a predictive model where yt is predicted by xt-1,
xt-2,... xt-p with xt being autoregressive of order p, AR(p) with p >
1. We develop a generalized augmented regression method that produces a
reduced-bias point estimate of the predictive coefficients and derive an
appropriate hypothesis testing procedure. We apply our method to the
prediction of quarterly stock returns by dividend yield, which is
apparently AR(2). Using our method results in the AR(2) predictor series
having insignificant effect, although under OLS, or the commonly assumed
AR(1) structure, the predictive model is significant. We also generalize
our method to the case of multiple AR(p) predictors. |
| URI: | http://hdl.handle.net/2451/28470 |
| Appears in Collections: | IOMS: Statistics Working Papers
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| ARp15.pdf | Predictive Regression with Order-p Autoregressive Predictor | 227.63 kB | Adobe PDF | View/Open |
|
All items in Faculty Digital Archive are protected by copyright, with all rights reserved.
|
