The 3rd Days of Econometrics for Finance
(Troisièmes Journées d’Économétrie de la Finance, JEF'2016)
Rabat, November 18-19, 2016
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The 3rd Days of Econometrics for Finance Conference, hosted by Mohammed V University and organized by the Faculty of Law, Economics and Social Sciences (Souissi) in Rabat, aims to bring together academics, practitioners and policymakers sharing interest in econometric modeling for finance. It provides a forum for presenting new research results as well as discussing current and challenging issues in econometric modeling and related topics.
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Important Dates
- Extended deadline for submission:
September 15, 2016
- Notification to authors: September 30, 2016
- Deadline for registration: November 4, 2016
- Conference event: November 18-19, 2016
Sponsors
Organizer
Keynote Speakers
CREST-ENSAE and Université de Lille 3, France
Christian Francq is member of the laboratory CREST and professor of applied mathematics at Lille 3 University and ENSAE, where he teaches time series analysis and financial econometrics. He is associate editor of Journal of Time Series Analysis and Statistical Inference for Stochastic Processes. His main research interests include financial and time series econometrics, and theoretical econometrics. In these areas, his current research focuses on risk estimation, the estimation of volatility models and conditional ellipticity testing. He is co-author of a book entitled “GARCH models: Structure, Statistical Inference and Financial Applications” and of recent research articles published in Econometrica, Annals of Statistics and JRSS-B.
Title of the Talk: “ESTIMATION RISK FOR THE VaR OF PORTFOLIOS DRIVEN BY SEMI-PARAMETRIC MULTIVARIATE MODELS”
Summary: Joint estimation of market and estimation risks in portfolios is investigated, when the individual returns follow a semi-parametric multivariate dynamic model and the asset composition is time-varying. Under ellipticity of the conditional distribution, asymptotic theory for the estimation of the conditional Value-at-Risk (VaR) is developed. An alternative method – the Filtered Historical Simulation - which does not rely on ellipticity, is also studied. Asymptotic confidence intervals for the conditional VaR, which allow to simultaneously quantify the market and estimation risks, are derived. The particular case of minimum variance portfolios is analyzed in more detail. Potential usefulness, feasibility and drawbacks of the two approaches are illustrated via Monte-Carlo experiments and an empirical study based on stock returns.
CREST-ENSAE and Université de Lille 3, France
Title of the Talk: “BUBBLE MODELLING BY NON-CAUSAL PROCESSES” (joint work with C. Gouriéroux)
Summary: The noncausal autoregressive process with heavy-tailed errors possesses a nonlinear causal dynamics, which allows for bubbles (local explosion) or asymmetric cycles often observed in economic and financial time series. It provides a new model for multiple local explosions in a strictly stationary framework. The causal predictive distribution displays surprising features, such as the existence of higher moments than for the marginal distribution, or the presence of a unit root in the Cauchy case. Aggregating such models can yield complex dynamics with local and global explosion as well as variation in the rate of explosion. The asymptotic behavior of a vector of sample autocorrelations is studied in a semi-parametric noncausal AR(1) framework with Pareto-like tails, and diagnostic tests are proposed. Empirical results based on the Nasdaq composite price index are provided.
[1] The conference languages will be English and French.
“tba”: To be announced
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