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This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and...
Persistent link: https://www.econbiz.de/10014052432
In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...
Persistent link: https://www.econbiz.de/10014052487
This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, the authors first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models....
Persistent link: https://www.econbiz.de/10014202226
Forecasters and applied econometricians are often interested in comparing the predictive accuracy of nested competing models. A leading example of a context in which competing models are nested is when predictive ability is equated with "out-of-sample Granger causality". In particular, it is...
Persistent link: https://www.econbiz.de/10014075927
In the conduct of empirical macroeconomic research, unit root, cointegration, common cycle, and related tests statistics are often constructed using logged data, even though there is often no clear reason, at least from an empirical perspective, why logs should be used rather than levels....
Persistent link: https://www.econbiz.de/10014075928
This paper introduces a conditional Kolmogorov test, in the spirit of Andrews (1997), that allows for comparison of multiple misspecifed conditional distribution models, for the case of dependent observations. A conditional confidence interval version of the test is also discussed. Model...
Persistent link: https://www.econbiz.de/10014075930
In this paper, we show the first order validity of the block bootstrap in the context of Kolmogorov type conditional distribution tests when there is dynamic misspecification and parameter estimation error. Our approach differs from the literature to date because we construct a bootstrap...
Persistent link: https://www.econbiz.de/10014075931