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We propose a semiparametric multivariate estimator and a multivariate score-type testing procedure under a perturbed multivariate fractional process. The estimator is based on the periodogram and uses a local Whittle criterion function which is generalised by an additional constant to capture...
Persistent link: https://www.econbiz.de/10014247836
We propose exible models for multivariate realized volatility dynamics which involve generalizations of the Box …
Persistent link: https://www.econbiz.de/10010344500
This paper generalises Boswijk and Zu (2018)'s adaptive unit root test for time series with nonstationary volatility to … resulting likelihood ratio test statistic. We find that under suitable conditions, adaptation with respect to the volatility … process is possible, in the sense that nonparametric volatility matrix estimation does not lead to a loss of asymptotic local …
Persistent link: https://www.econbiz.de/10012026102
Persistent link: https://www.econbiz.de/10011974604
This paper derives a multivariate local Whittle estimator for the memory parameter of a possibly long memory process and the fractional cointegration vector robust to low frequency contaminations. This estimator as many other local Whittle based procedures requires a priori knowledge of the...
Persistent link: https://www.econbiz.de/10012105358
In this paper, we extend copula-based univariate time series models studied in Chen & Fan (2006) to multivariate time series. Doing so, we tackle at the same time serial dependence as well as interdependence between several time series. The proposed methodology is totally different from the...
Persistent link: https://www.econbiz.de/10013133767
This study compares the size and power of autoregressive conditional heteroskedasticity (ARCH) tests that are robust to the presence of a misspecified conditional mean. The approaches employed are based on two nonparametric regressions for the conditional mean: an ARCH test with a...
Persistent link: https://www.econbiz.de/10013183738
It is well-knownthat financial data sets exhibit conditional heteroskedasticity. GARCH type models are often used to model this phenomenon. Since the distribution of the rescaled innovations is generally far froma normal distribution, a semiparametric approach is advisable. Several publications...
Persistent link: https://www.econbiz.de/10014155199
Persistent link: https://www.econbiz.de/10010191407
In this paper, we propose a two-step less volatile value-at-risk (LVaR) estimation using the generalized nearly-isotonic regression (GNIR) model. The first step of our LVaR estimation is to produce a VaR sequence under the generalized autoregressive conditional heteroskedasticity (GARCH)...
Persistent link: https://www.econbiz.de/10013290709