New Frontiers in Applied Quantitative Management and Finance: Nonlinear Econometric Models, Fractional Cointegration and Econophysics

This project addresses the study of financial markets (and other) using some relatively new tools based on nonlinear time series modelling and econophysics. Nonlinear models used in econometrics are usually constructed in order to address some specific issues of the nonlinear behaviour observed in real markets. One such type of model is the threshold class, useful to study asymmetries in the data. Other forms of nonlinearity and assumptions concerning distributional aspects of the error terms have been also analysed by econometricians. Conditional heteroskedasticity and fractional volatility are amongst these lines of research. Much less attention, however, has been paid to the nonlinear characteristics of the original integrated data, at least in what concerns stock market analyses. Another line of research on financial markets, originally addressed by physicists, lies on the concept of entropy used in the context of econophysics. Several measures of entropy appeared in the literature, but the most widely used when applied to stock markets are the Tsallis and the Shannon entropies. Trying to find links between concepts based on traditional econometrics and econophysics, in line with other authors, is one of the goals of the research work conducted under this project. Extensions of these models to other research fields such as industrial economics and marketing may also prove to be useful, and will be pursued by our team. The work involved in the project includes writing articles and communications in the selected field, organizing international meetings dedicated to the theme, and constructing PhD and Master theses, which will be encouraged to address these issues.