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variations in returns. Forecasting volatility has been a stimulating problem in the financial systems. This study examined the … forecasting technique with respect to various volatility estimators. The methodology of volatility estimation included Close …Volatility has been used as an indirect means for predicting risk accompanied with an asset. Volatility explains the …
Persistent link: https://www.econbiz.de/10012870348
variations in returns. Forecasting volatility had been a stimulating problem in the financial systems. The study examined the … forecasting technique with respect to various volatility estimators. The methodology of volatility estimation includes Close …Volatility had been used as an indirect means for predicting risk accompanied with the asset. Volatility explains the …
Persistent link: https://www.econbiz.de/10012860158
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …
Persistent link: https://www.econbiz.de/10011674479
Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …
Persistent link: https://www.econbiz.de/10011730304
the new model's moment properties are also derived. Empiricalresults are given for the daily returns of the compositeindex …
Persistent link: https://www.econbiz.de/10011303289
In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in … of covariates as well as the smoothing parameters via cross-validation. We find that volatility forecastability is much … squared return prediction errors gives an adequate approximation of the unobserved realised conditional variance for both the …
Persistent link: https://www.econbiz.de/10012127861
suggests that the introduction of asymmetric effects with respect to the returns and the volatility in the HAR model result in …In this paper, we estimate, model and forecast Realized Range Volatility, a realized measure and estimator of the … forecasting daily stocks volatility. We consider an HAR model with asymmetric effects with respect to the volatility and the …
Persistent link: https://www.econbiz.de/10013076452
The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with … model a time-varying generalization of the HAR model for the realized volatility series. It emerges that during the recent … stochastic volatility model suggest that the change in the dynamic structure of the realized volatility during the financial …
Persistent link: https://www.econbiz.de/10010402299
Persistent link: https://www.econbiz.de/10010191413
only daily returns for daily and weekly horizons. Among the HEAVY-type models, for a dataset of twenty-nine stocks, those … the full-day covariance provides more economic value than using the overnight returns, as the latter tend to yield noisy …
Persistent link: https://www.econbiz.de/10014434629