Similar Search Results

Narrow search

How to deal with intercept and trend in practical cointegration analysis?

Franses, Philip Hans - 1999

Persistent link: https://www.econbiz.de/10001495844

Outlier detection in the GARCH (1,1) model

Franses, Philip Hans; Dijk, Dick van - 1999

Persistent link: https://www.econbiz.de/10001495849

Cointegration in a periodic vector autoregression

Kleibergen, Frank; Franses, Philip Hans - 1999

Persistent link: https://www.econbiz.de/10001495876

Semi-parametric modelling of correlation dynamics

Hafner, Christian M. (contributor); … - 2005

Persistent link: https://www.econbiz.de/10003010850

Confidence intervals for maximal reliability of probability judgments

Lam, Kar Yin (contributor); Koning, Alex J. (contributor); … - 2007

Persistent link: https://www.econbiz.de/10003484019

Semi-parametric modelling of correlation dynamics

Hafner, Christian M.; Dijk, Dick van; Franses, Philip Hans - 2006

Persistent link: https://www.econbiz.de/10003331369

Exploiting spillovers to forecast crashes

Gresnigt, Francine; Kole, Erik; Franses, Philip Hans - In: Journal of forecasting 36 (2017) 8, pp. 936-955

Persistent link: https://www.econbiz.de/10011860928

Visualizing time-varying correlations across stock markets

Franses, Philip Hans; Groenen, Patrick J. F. - 1999

Persistent link: https://www.econbiz.de/10001447137

Does rounding matter for payment efficiency?

Bijwaard, Govert (contributor); … - 2006

Persistent link: https://www.econbiz.de/10003385243

Short Patches of Outliers, ARCH and Volatility Modeling

Franses, Philip Hans; van Dijk, Dick; Lucas, André - 1998

In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span...

Persistent link: https://www.econbiz.de/10010324601

A service of the

zbw