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robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility … propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long …
Persistent link: https://www.econbiz.de/10009719116
This study extends the literature on the relation between trading activity and volatility by looking at a new asset class in the form of VIX futures, and by decomposing each side of the relation into two components. The results confirm several findings documented in prior studies: The number of...
Persistent link: https://www.econbiz.de/10013007322
Persistent link: https://www.econbiz.de/10015110400
We investigate a new separable nonparametric model for time series, which includes many ARCH models and AR models …
Persistent link: https://www.econbiz.de/10010746316
Persistent link: https://www.econbiz.de/10010191407
estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps …
Persistent link: https://www.econbiz.de/10010487528
This paper extends the classical work of bipower variation by allowing the return process to be autocorrelated. We propose a method of estimating the return volatility when the price process is described by a fractal Brownian motion with jumps.
Persistent link: https://www.econbiz.de/10011116217
This paper proposes a novel positive nonparametric estimator of the conditional variance function without reliance on … nonparametric regression applied to squared mean regression residuals. The estimator is shown to be asymptotically equivalent to the …
Persistent link: https://www.econbiz.de/10005093922
We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework...
Persistent link: https://www.econbiz.de/10005797706
Stochastic variance models where the logarithmic volatility is modelled by an ARMA process and models with conditional heteroscedasticity for daily returns are studied. Volatility of monthly relative changes computed as a product of daily changes is considered and estimated from daily...
Persistent link: https://www.econbiz.de/10008528874