Testing Predictive Ability and Power Robustification
Bibliographic Data
| ID | 19418945 |
|---|---|
| Authors | Kyungchul Song (0000-0002-8497-5934, University of British Columbia, corresponding author) |
| Year | 2012 |
| Volume | 30 |
| Issue | 2 |
| Pages | 288-296 |
| Publication date | 2012-04-01 |
| 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 | 10.1080/07350015.2012.663245 |
| OpenAlex | W2037035662 |
| Language | EN |
| References cited | 21 |
One of the approaches to compare forecasting methods is to test whether the risk from a benchmark prediction is smaller than the others. The test can be embedded into a general problem of testing inequality constraints using a one-sided sup functional. Hansen showed that such tests suffer from asymptotic bias. This article generalizes this observation, and proposes a hybrid method to robustify the power properties by coupling a one-sided sup test with a complementary test. The method can also be applied to testing stochastic dominance or moment inequalities. Simulation studies demonstrate that the new test performs well relative to the existing methods. For illustration, the new test was applied to analyze the forecastability of stock returns using technical indicators employed by White
Econometrics · Economics · Physics · Predictive power · Robustification · Statistics · Advanced Statistical Methods and Models · Computer Science · Financial Risk and Volatility Modeling · Mathematics · Statistical Methods and Inference
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Tests of Conditional Predictive Ability
Consistent Tests for Stochastic Dominance
A Test for Superior Predictive Ability
Comparing Density Forecasts via Weighted Likelihood Ratio Tests
Multivariate Density Forecast Evaluation and Calibration In Financial Risk Management
Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality
Testing for Asymmetric Information in Insurance Markets
| Highly cited | No |
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