Similar Search Results

On Stable Factor Structures in the Pricing of Risk

Ghysels, Eric - Centre Interuniversitaire de Recherche en Analyse des … - 1995

Much of the research describing the cross-sectional and time series behavior of asset returns can be characterized as a search for the relevant state variables and also a search for the relevant model specification. Ultimately the scope of such efforts is to find a satisfactory and stable asset...

Persistent link: https://www.econbiz.de/10005100814

Market Time and Asset Price Movements Theory and Estimation

Ghysels, Eric; Gouriéroux, Christian; Jasiak, Joanna - Centre Interuniversitaire de Recherche en Analyse des … - 1995

Subordinated stochastic processes, also called time deformed stochastic processes, have been proposed in a variety of contexts to describe asset price behavior. They are used when the movement of prices is tied to the number of market transactions, trading volume or the more illusive concept of...

Persistent link: https://www.econbiz.de/10005101080

Stochastic Volatility and Time Deformation: An Application to Trading Volume and Leverage Effects

Ghysels, Eric; Jasiak, Joanna - Centre Interuniversitaire de Recherche en Analyse des … - 1995

In this paper, we study stochastic volatility models with time deformation. Such processes relate to early work by Mandelbrot and Taylor (1967), Clark (1973), Tauchen and Pitts (1983), among others. In our setup, the latent process of stochastic volatility evolves in a operational time which...

Persistent link: https://www.econbiz.de/10005101089

A Semi-Parametric Factor Model for Interest Rates

Ghysels, Eric; Ng, Serena - Centre Interuniversitaire de Recherche en Analyse des … - 1996

paper follows a longstanding tradition of using factor models of interest rates but proposes a semi-parametric procedure to … model interest rates. In a semi-parametric approach one typically parameterizes the object of interest while leaving …, which is a semi-parametric procedure proposed by Hardle and Stoker (1989) and Powell, Stock and Stoker (1989), allows us to …

Persistent link: https://www.econbiz.de/10005100562

Robust Sign-Based and Hodges-Lehmann Estimators in Linear Median Regressions with Heterogenous Serially Dependent Errors

Coudin, Elise; Dufour, Jean-Marie - Centre Interuniversitaire de Recherche en Analyse des … - 2011

We propose estimators for the parameters of a linear median regression without any assumption on the shape of the error distribution including no condition on the existence of moments allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous distributions, and very...

Persistent link: https://www.econbiz.de/10008855591

Is Seasonal Adjustment a Linear or Nonlinear Data Filtering Process?

Ghysels, Eric; Granger, Clive W.J.; Siklos, Pierre L. - Centre Interuniversitaire de Recherche en Analyse des … - 1995

In this paper, we investigate whether seasonal adjustment procedures are, at least approximately, linear data transformations. This question is important with respect to many issues including estimation of regression models with seasonally adjusted data. We focus on the X-11 program and first...

Persistent link: https://www.econbiz.de/10005100511

Nonlinearity and Temporal Dependence

Chen, Xiaohong; Hansen, Lars P.; Carrasco, Marine - Centre Interuniversitaire de Recherche en Analyse des … - 2009

Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models. We study this link using two notions of temporal dependence: β−mixing and ρ−mixing. Weshow that β−mixing and ρ−mixing with exponential decay are essentially equivalent...

Persistent link: https://www.econbiz.de/10005100536

Seasonal Time Series and Autocorrelation Function Estimation

Bell, William R.; Ghysels, Eric; Lee, Hahn Shik - Centre Interuniversitaire de Recherche en Analyse des … - 1997

Time series are demeaned when sample autocorrelation functions are computed. By the same logic it would seem appealing to remove seasonal means from seasonal time series before computing sample autocorrelation functions. Yet, standard practice is only to remove the overall mean and ignore the...

Persistent link: https://www.econbiz.de/10005100761

Seasonal Nonstationarity and Near-Nonstationarity

Ghysels, Eric; Osborn, Denise R.; Rodrigues, Paulo M. M. - Centre Interuniversitaire de Recherche en Analyse des … - 1999

This paper presents a detailed discussion of the characteristics of seasonal integrated and near integrated processes, as well as the asymptotic properties of seasonal unit root tests. More specifically, the characteristics of a seasonal random walk and a more general seasonal integrated ARMA...

Persistent link: https://www.econbiz.de/10005100904

Distribution-Free Bounds for Serial Correlation Coefficients in Heteroskedastic Symmetric Time Series

Dufour, Jean-Marie; Farhat, Abdeljelil; Hallin, Marc - Centre Interuniversitaire de Recherche en Analyse des … - 2005

We consider the problem of testing whether the observations X1, · · ·, Xn of a time series are independent with unspecified (possibly nonidentical) distributions symmetric about a common known median. Various bounds on the distributions of serial correlation coefficients are proposed:...

Persistent link: https://www.econbiz.de/10005100838

1
2
3
4
5
6
7
8
9
10
Next
Last