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Guegan, Dominique - HAL - 2008

In this paper we deal with the problem of non-stationarity encountered in a lot of data sets, mainly in financial and economics domains, coming from the presence of multiple seasonnalities, jumps, volatility, distorsion, aggregation, etc. Existence of non-stationarity involves spurious behaviors...

Persistent link: https://www.econbiz.de/10010750362

Global and local stationary modelling in finance : theory and empirical evidence

Guegan, Dominique - HAL - 2007

In this paper we deal with the problem of non-stationarity encountered in a lot of data sets coming from existence of multiple seasonnalities, jumps, volatility, distorsion, aggregation, etc. We study the problem caused by these non stationarities on the estimation of the sample autocorrelation...

Persistent link: https://www.econbiz.de/10010750670

Empirical Projected Copula Process and Conditional Independence An Extended Version

Frattarolo, Lorenzo; Guegan, Dominique - HAL - 2013

Conditional dependence is expressed as a projection map in the trivariate copula space. The projected copula, its … sample counterpart and the related process are defined. The weak convergence of the projected copula process to a tight … centered Gaussian Process is obtained under weak assumptions on copula derivatives. …

Persistent link: https://www.econbiz.de/10011026052

Value at Risk Computation in a Non-Stationary Setting

Guegan, Dominique - HAL - 2010

This chapter recalls the main tools useful to compute Value at Risk associated with a m-dimensional portfolio. Then, the limitations of the use of these tools is explained, as soon as non-stationarities are observed in time series. Indeed, specific behaviours observed by financial assets, like...

Persistent link: https://www.econbiz.de/10010603681