This paper introduces a behavioural model and an algorithm that allow define classes of investors and draw the size each of them from financial data. The nonparametric pricing kernel estimated from stocks and options quotes allows to derive an estimate of the market utility. At the micro level...

Diese Dissertation entwickelt neue lokal adaptive Methoden zur Schaetzung und Vorhersage von Zeitreihendaten. Diese Methoden sind fuer die Volatilitaetsschaetzung von Finanzmarktrenditen und fuer Regressions- und Autoregressionsprobleme konstruiert worden. Die vorgeschlagenen Ansaetze werden als...

This paper offers a new method for estimation and forecasting of the volatility of financial time series when the stationarity assumption is violated. Our general, local parametric approach particularly applies to general varying-coefficient parametric models, such as GARCH, whose coefficients...

We consider univariate nonparametric regression. Two standard nonparametric regression function estimates are kernel estimates and nearest neighbor estimates. Mack (1981) noted that both methods can be defined with respect to a kernel or weighting function, and that for a given kernel and a...