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A Practical Guide To Harnessing The Har Volatility Model, Adam Clements, Daniel P. A. Preve
A Practical Guide To Harnessing The Har Volatility Model, Adam Clements, Daniel P. A. Preve
Research Collection School Of Economics
The standard heterogeneous autoregressive (HAR) model is perhaps the most popular benchmark model for forecasting return volatility. It is often estimated using raw realized variance (RV) and ordinary least squares (OLS). However, given the stylized facts of RV and well-known properties of OLS, this combination should be far from ideal. The aim of this paper is to investigate how the predictive accuracy of the HAR model depends on the choice of estimator, transformation, or combination scheme made by the market practitioner. In an out-of-sample study, covering the S&P 500 index and 26 frequently traded NYSE stocks, it is found that …
Generalized Jump Regressions For Local Moments, Tim Bollerslev, Jia Li, Leonardo Salim Saker Chaves
Generalized Jump Regressions For Local Moments, Tim Bollerslev, Jia Li, Leonardo Salim Saker Chaves
Research Collection School Of Economics
We develop new high-frequency-based inference procedures for analyzing the relationship between jumps in instantaneous moments of stochastic processes. The estimation consists of two steps: the nonparametric determination of the jumps as differences in local averages, followed by a minimum-distance type estimation of the parameters of interest under general loss functions that include both least-square and more robust quantile regressions as special cases. The resulting asymptotic distribution of the estimator, derived under an infill asymptotic setting, is highly nonstandard and generally not mixed normal. In addition, we establish the validity of a novel bootstrap algorithm for making feasible inference including bias-correction. …