Article ID Journal Published Year Pages File Type
7357999 Journal of Econometrics 2018 66 Pages PDF
Abstract
This paper provides a general framework that enables many existing inference methods for predictive accuracy to be used in applications that involve forecasts of latent target variables. Such applications include the forecasting of volatility, correlation, beta, quadratic variation, jump variation, and other functionals of an underlying continuous-time process. We provide primitive conditions under which a “negligibility” result holds, and thus the asymptotic size of standard predictive accuracy tests, implemented using a high-frequency proxy for the latent variable, is controlled. An extensive simulation study verifies that the asymptotic results apply in a range of empirically relevant applications, and an empirical application to correlation forecasting is presented.
Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
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