Inferring the Predictability Induced by a Persistent Regressor in a Predictive Threshold Model
Bibliographic Data
| ID | 19418808 |
|---|---|
| Authors | Jesús Gonzalo (0000-0002-4309-5025, Universidad Carlos III de Madrid), Jean-Yves Pitarakis (University of Southampton), Jean‐Yves Pitarakis (0000-0002-6305-7421, University of Southampton) |
| Year | 2017 |
| Volume | 35 |
| Issue | 2 |
| Pages | 202-217 |
| Publication date | 2017-04-03 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2016.1164054 |
| OpenAlex | W111836674 |
| Language | EN |
| Citations received | 5 |
| References cited | 23 |
We develop tests for detecting possibly episodic predictability induced by a persistent predictor. Our framework is that of a predictive regression model with threshold effects and our goal is to develop operational and easily implementable inferences when one does not wish to impose à priori restrictions on the parameters of the model other than the slopes corresponding to the persistent predictor. Differently put our tests for the null hypothesis of no predictability against threshold predictability remain valid without the need to know whether the remaining parameters of the model are characterized by threshold effects or not (e.g., shifting versus nonshifting intercepts). One interesting feature of our setting is that our test statistics remain unaffected by whether some nuisance parameters are identified or not. We subsequently apply our methodology to the predictability of aggregate stock returns with valuation ratios and document a robust countercyclicality in the ability of some valuation ratios to predict returns in addition to highlighting a strong sensitivity of predictability based results to the time period under consideration
Econometrics · Economics · Heteroscedasticity · Null hypothesis · Predictability · Regression · Statistics · Complex Systems and Time Series Analysis · Computer Science · Financial Risk and Volatility Modeling · Forecasting Techniques and Applications · Mathematics
A joint test of predictability and structural break in predictive regressions
Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions
Regime-Specific Return Predictability in Quantiles
Testing for Structural Change of Predictive Regression Model to Threshold Predictive Regression Model
Threshold Regression with Errors-in-Variables
| Citations per year | 1 |
|---|---|
| Citation span | 2021 - 2026 (6) |
| Highly cited | No |