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Realized Volatility and the Variance Risk Premium. The approach is innovative along two different dimensions, namely: (1) we …-type models and (2) we price equity volatility risk using factors which go beyond the equity class. These are volatility factors …
Persistent link: https://www.econbiz.de/10013045628
The financial industry has eagerly adopted machine learning algorithms to improve on traditional predictive models. In this paper we caution against blindly applying such techniques. We compare forecasting ability of machine learning methods in evaluating future payoffs on synthetic variance...
Persistent link: https://www.econbiz.de/10013242609
We estimate MIDAS regressions with various (bi)power variations to predict future volatility measured via increments in …
Persistent link: https://www.econbiz.de/10003900365
We propose a general GARCH framework that allows the predict volatility using returns sampled at a higher frequency …-GARCH models, as the volatility dynamics are driven by what we call HYBRID processes. The HYBRID processes can involve data sampled … volatility are less preferred than HYBRID involving intra-daily weighting scheme even for longer horizons …
Persistent link: https://www.econbiz.de/10013114867
broadly, our study dispels the notion that volatility is not forecastable at long horizons and offers an approach that …
Persistent link: https://www.econbiz.de/10011976983
transaction durations and vice versa. Otherwise the spacings between trades are considered exogenous to the volatility dynamics … causality between volatility and intra-trade durations. Under general conditions we propose several GMM estimation procedures … that volatility of IBM stock prices Granger causes intra-trade durations. We also find that the persistence in GARCH drops …
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