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A note on stochastic volatility, GARCH models, and hyperbolic distributions

Jaschke, Stefan R. - 1997

We establish a relation between stochastic volatility models and the class of generalized hyperbolic distributions. These distributions have been found to fit exceptionally well to the empirical distribution of stock returns. We review the background of hyperbolic distributions and prove...

Persistent link: https://www.econbiz.de/10009577459

Nonparametric autoregression with multiplicative volatility and additive mean

Yang, Lijian; Härdle, Wolfgang; Nielsen, Jens Perch - 1998

For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...

Persistent link: https://www.econbiz.de/10009578559

Higher order forward rate agreements and the smoothness of the term structure

Jaschke, Stefan R. - 1998

This paper proposes linear higher order conditions on the term structure that allow to compute valuation bounds for any deterministic cash stream. Starting from bounds on the forward rate curve and its derivatives, which are nonlinear in the discount factors, we derive linear conditions that are...

Persistent link: https://www.econbiz.de/10009579185

Nonparametric lag selection for time series

Tschernig, Rolf; Yang, Lijian - 1997

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater...

Persistent link: https://www.econbiz.de/10009659069

M robustified additive nonparametric regression

Tamine, Julien; Härdle, Wolfgang; Yang, Lijian - 2002

Additive modelling has been widely used in nonparametric regression to circumvent the "curse of dimensionality", by reducing the problem of estimating a multivariate regression function to the estimation of its univariate components. Estimation of these univariate functions, however, can suffer...

Persistent link: https://www.econbiz.de/10009626746

R robustified additive nonparametric regression

Tamine, Julien; Härdle, Wolfgang; Yang, Lijian - 2002

Additive modelling is known to be useful for multivariate nonparametric regression as it reduces the complexity of problem to the level of univariate regression. This usefulness could be compromised if the data set was contaminated by outliers whose detection and removal are particularly...

Persistent link: https://www.econbiz.de/10009627283

Hazard regression

Grund, Birgit; Yang, Lijian - 1999

Persistent link: https://www.econbiz.de/10009581089

Coherent risk measures, valuation bounds, and (my,p)-portfolio optimization

Jaschke, Stefan R.; Küchler, Uwe - 1999

This paper presents a general theory that works out the relation between coherent risk measures, valuation bounds, and … theory presented seems to fill a gap between arbitrage valuation on the one hand and single agent utility maximization or … full-fledged equilibrium theory on the other hand. "Coherent" valuation bounds strike a balance in that the bounds can be …

Persistent link: https://www.econbiz.de/10009581108

Hazard regression

Grund, Birgit; Yang, Lijian - 2000

Persistent link: https://www.econbiz.de/10009611555

Quantile-VaR is the wrong measure to quantify market risk for regulatory purposes

Jaschke, Stefan R. - 2001

Starting from the objective of banking supervision - to minimize the overall costs of banking to the general public - we show that the current standard of quantifying market risk is flawed. It is perfectly aligned with the interests of banks' shareholders and management, but not with the...

Persistent link: https://www.econbiz.de/10009614286