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Nonlinear time series with long memory : a model for stochastic volatility

Robinson, Peter M.; Zaffaroni, Paolo - 1997

Persistent link: https://www.econbiz.de/10000954585

Nonlinear time series with long memory : a model for stochastics volatility

Robinson, Peter M.; Zaffaroni, Paolo - 1996

Persistent link: https://www.econbiz.de/10000985327

Pseudo-maximum likelihood estimation of ARCH(∞) models

Robinson, Peter M. (contributor); … - 2005

Persistent link: https://www.econbiz.de/10003164285

Nonlinear long memory models with applications in finance

Zaffaroni, Paolo - 1997

Persistent link: https://www.econbiz.de/10001397476

Stationarity and memory of ARCH(∞) models

Zaffaroni, Paolo - In: Econometric theory 20 (2004) 1, pp. 147-160

Persistent link: https://www.econbiz.de/10001904870

Whittle estimation of EGARCH and other exponential volatility models

Zaffaroni, Paolo - In: Journal of econometrics 151 (2009) 2, pp. 190-200

Persistent link: https://www.econbiz.de/10003877967

Comment on: identification robust testing of risk premia in finite samples

Zaffaroni, Paolo - In: Journal of financial econometrics 21 (2023) 2, pp. 303-305

Persistent link: https://www.econbiz.de/10014314744

The estimation of misspecified long memory models

Robinson, Peter M. - In: Journal of econometrics 178 (2014) 1, pp. 225-230

Persistent link: https://www.econbiz.de/10010256170

Nonparametric trending regression with cross-sectional dependence

Robinson, Peter M. - In: Journal of econometrics 169 (2012) 1, pp. 4-14

Persistent link: https://www.econbiz.de/10009666775

Asymptotic theory for nonparametric regression with spatial data

Robinson, Peter M. - 2011

Nonparametric regression with spatial, or spatio-temporal, data is considered. The conditional mean of a dependent variable, given explanatory ones, is a nonparametric function, while the conditional covariance reflects spatial correlation. Conditional heteroscedasticity is also allowed, as well...

Persistent link: https://www.econbiz.de/10008906533