Dimension reduction techniques for functional data analysis model and approximate smooth random functions by lower dimensional objects. In many applications the focus of interest lies not only in dimension reduction but also in the dynamic behaviour of the lower dimensional objects. The most...

Recently, Frittelli and Scandolo ([9]) extend the notion of risk measures, originally introduced by Artzner, Delbaen, Eber and Heath ([1]), to the risk assessment of abstract financial positions, including pay offs spread over different dates, where liquid derivatives are admitted to serve as...

This paper may be understood as a continuation of Topsøe’s seminal paper ([16]) to characterize, within an abstract setting, compact subsets of finite inner regular measures w.r.t. the weak topology. The new aspect is that neither assumptions on compactness of the inner approximating lattices...

Let W denote a family of probability distributions with parameter space t, and WG be a subfamily of W depending on a mapping G : O -- t. Extremum estimations of the parameter vector v e O are considered. Some sufficient conditions are presented to ensure the uniqueness with probability one. As...

Supported by several recent investigations the empirical pricing kernel paradox might beconsidered as a stylized fact. In Chabi-Yo et al. (2008) simulation studies have been presentedwhich suggest that this paradox might be caused by regime switching of stock prices in financialmarkets....

In this paper we develop several regression algorithms for solvinggeneral stochastic optimal control problems via Monte Carlo. Thistype of algorithms is particularly useful for problems with a highdimensionalstate space and complex dependence structure of the underlyingMarkov process with...

The problem of pricing Bermudan options using Monte Carlo anda nonparametric regression is considered. We derive optimal nonasymptoticbounds for a lower biased estimate based on the suboptimalstopping rule constructed using some estimates of continuationvalues. These estimates may be of...

We consider the problem of estimating the fractional order of a L´evyprocess from low frequency historical and options data. An estimationmethodology is developed which allows us to treat both estimation andcalibration problems in a unified way. The corresponding procedureconsists of two steps:...

In this paper we propose a Libor model with a high-dimensional speciallystructured system of driving CIR volatility processes. A stablecalibration procedure which takes into account a given local correlationstructure is presented. The calibration algorithm is FFT based, so fastand easy to implement.

In this article we propose several pathwise and finite difference basedmethods for calculating sensitivities of Bermudan options using regressionmethods and Monte Carlo simulation. These methods rely on conditionalprobabilistic representations which allow, in combination with aregression...