His scientific interests lie mostly in Econometrics, Value at risk, Arch, Stock market index and Statistics. His work in the fields of Econometrics, such as Multivariate garch, Realized variance and Volatility, intersects with other areas such as Multivariate t-distribution. His study in Realized variance is interdisciplinary in nature, drawing from both Exchange rate and Vector autoregression.
His Volatility study incorporates themes from Financial engineering, Univariate and Equity. In the field of Value at risk, his study on RiskMetrics overlaps with subjects such as Commodity. Arch is intertwined with Parametric model, Event, Risk measure, Term and Multiple in his research.
His primary areas of study are Econometrics, Volatility, Exchange rate, Autoregressive conditional heteroskedasticity and Statistics. In his study, which falls under the umbrella issue of Econometrics, Skewness is strongly linked to Multivariate statistics. His studies in Volatility integrate themes in fields like Jump and Central bank.
His Exchange rate study is concerned with Monetary economics in general. His Statistics study which covers Asymmetry that intersects with Residual and Nonparametric statistics. He integrates many fields in his works, including Value at risk, Stock market index and Risk measure.
His primary areas of investigation include Econometrics, Monte Carlo method, Applied mathematics, Estimator and Autoregressive model. His work deals with themes such as Jump and Statistics, which intersect with Econometrics. His work carried out in the field of Monte Carlo method brings together such families of science as Stochastic differential equation, Sample, Mathematical optimization and Collinearity.
His research investigates the link between Stochastic differential equation and topics such as Sample size determination that cross with problems in Degeneracy and Statistical physics. His work in Estimator tackles topics such as Cholesky decomposition which are related to areas like Covariance matrix, Positive-definite matrix, Estimation of covariance matrices and Covariance. His Diffusion process research is multidisciplinary, incorporating perspectives in Realized variance and Stock price index.
Sébastien Laurent mostly deals with Estimator, Applied mathematics, Cholesky decomposition, Monte Carlo method and Autoregressive conditional heteroskedasticity. The Applied mathematics study combines topics in areas such as Positive-definite matrix, Matrix, Covariance matrix, Estimation of covariance matrices and Sample. The study incorporates disciplines such as Stochastic differential equation, Degeneracy, Diffusion and Collinearity in addition to Monte Carlo method.
His Autoregressive conditional heteroskedasticity study is concerned with the field of Econometrics as a whole. His work in the fields of Econometrics, such as Volatility and Realized variance, overlaps with other areas such as Logarithm and Sampling bias. Sébastien Laurent works mostly in the field of Conditional variance, limiting it down to concerns involving Heteroscedasticity and, occasionally, Jump.
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Multivariate GARCH models: a survey
Luc Bauwens;Sébastien Laurent;Jeroen V. K. Rombouts.
Journal of Applied Econometrics (2006)
Modelling daily value-at-risk using realized volatility and arch type models
Pierre Giot;Pierre Giot;Sébastien Laurent;Sébastien Laurent.
Journal of Empirical Finance (2001)
Value-at-risk for long and short trading positions
Pierre Giot;Pierre Giot;Sébastien Laurent;Sébastien Laurent;Sébastien Laurent.
Journal of Applied Econometrics (2003)
A new class of multivariate skew densities, with application to generalized autoregressive conditional heteroscedasticity models
Luc Bauwens;Sébastien Laurent.
Research Papers in Economics (2005)
Market risk in commodity markets: a VaR approach
Pierre Giot;Sébastien Laurent.
Energy Economics (2003)
Jumps, cojumps and macro announcements
Jerome Lahaye;Sebastien Laurent;Christopher J. Neely.
Research Papers in Economics (2007)
Modelling financial time series using GARCH-type models with a skewed student distribution for the innovations
Philippe Lambert;Sébastien Laurent.
Optically driven spin memory in n-doped InAs-GaAs quantum dots.
Cortez S;Krebs O;Laurent S;Senes M.
Physical Review Letters (2002)
A mixture of Bose and Fermi superfluids
I. Ferrier-Barbut;M. Delehaye;S. Laurent;A. T. Grier.
Multivariate GARCH Models: A Survey
Luc Bauwens;Sébastien Laurent;J. V. K. Rombouts.
Social Science Research Network (2003)
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