Narrow search
Showing 1 - 10 of 11
Cover Image
Sample and implied volatility in GARCH models
Horváth, Lajos; Kokoszka, Piotr; Zitikis, Ričardas - In: Journal of financial econometrics : official journal of … 4 (2006) 4, pp. 617-635
Persistent link: https://www.econbiz.de/10003565751
Cover Image
Functional dynamic factor model for intraday price curves
Kokoszka, Piotr; Miao, Hong; Zhang, Xi - In: Journal of financial econometrics : official journal of … 13 (2015) 2, pp. 456-477
Persistent link: https://www.econbiz.de/10011339294
Cover Image
Monitoring the intraday volatility pattern
Gabrys, Robertas; Hörmann, Siegfried; Kokoszka, Piotr - In: Journal of time series econometrics 5 (2013) 2, pp. 87-116
Persistent link: https://www.econbiz.de/10010225463
Cover Image
Predictability of shapes of intraday price curves
Kokoszka, Piotr; Reimherr, Matthew - In: The econometrics journal 16 (2013) 3, pp. 285-308
Persistent link: https://www.econbiz.de/10010253641
Cover Image
Risk analysis of cumulative intraday return curves
Kokoszka, Piotr; Miao, Hong; Stoev, Stilian; Zheng, Ben - In: Journal of time series econometrics 11 (2019) 2, pp. 1-31
Persistent link: https://www.econbiz.de/10012022894
Cover Image
Empirical wavelet analysis of tail and memory properties of LARCH and FIGARCH models
Jach, Agnieszka; Kokoszka, Piotr - In: Computational Statistics 25 (2010) 1, pp. 163-182
Persistent link: https://www.econbiz.de/10008596094
Cover Image
Large Dynamic Covariance Matrices : Enhancements Based on Intraday Data
De Nard, Gianluca - 2020
Modeling and forecasting dynamic (or time-varying) covariance matrices has many important applications in finance, such as Markowitz portfolio selection. A popular tool to this end are multivariate GARCH models. Historically, such models did not perform well in large dimensions due to the...
Persistent link: https://www.econbiz.de/10012827099
Cover Image
Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2022 - This version: January 2022
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how...
Persistent link: https://www.econbiz.de/10013040932
Cover Image
Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2021 - This version: June 2021
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how...
Persistent link: https://www.econbiz.de/10012584099
Cover Image
Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2020
Modeling and forecasting dynamic (or time-varying) covariance matrices has many important applications in finance, such as Markowitz portfolio selection. A popular tool to this end are multivariate GARCH models. Historically, such models did not perform well in large dimensions due to the...
Persistent link: https://www.econbiz.de/10012253083