Generic Conditions for Forecast Dominance
Bibliographic Data
| ID | 19418925 |
|---|---|
| Authors | Fabian Krüger (0000-0002-5112-9037, Karlsruhe Institute of Technology, corresponding author), Johanna F Ziegel (0000-0002-5916-9746, University of Bern) |
| Year | 2021 |
| Volume | 39 |
| Issue | 4 |
| Pages | 972-983 |
| Publication date | 2021-10-02 |
| Peer Reviewed | Yes |
| 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 | 10.1080/07350015.2020.1741376 |
| OpenAlex | W3010967283 |
| Language | EN |
| Citations received | 1 |
| References cited | 34 |
Recent studies have analyzed whether one forecast method dominates another under a class of consistent scoring functions. While the existing literature focuses on empirical tests of forecast dominance, little is known about the theoretical conditions under which one forecast dominates another. To address this question, we derive a new characterization of dominance among forecasts of the mean functional. We present various scenarios under which dominance occurs. Unlike existing results, our results allow for the case that the forecasts’ underlying information sets are not nested, and allow for uncalibrated forecasts that suffer, for example, from model misspecification or parameter estimation error. We illustrate the empirical relevance of our results via data examples from finance and economics
Consensus forecast · Econometrics · Economics · Estimation · Statistics · Stochastic dominance · Computer Science · Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact
Econometric Computing with HC and HAC Covariance Matrix Estimators
Increasing risk
Automatic Lag Selection in Covariance Matrix Estimation
Modeling and Forecasting Realized Volatility
Elicitation of Personal Probabilities and Expectations
A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
Forecast Rationality Tests Based on Multi-Horizon Bounds
Comparing Possibly Misspecified Forecasts
| Unique citing works | 1 |
|---|---|
| Citations per year | 0.2 |
| Citation span | 2021 - 2021 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |