The behavior of a hedge-fund manager naturally depends on her compensation scheme, her preferences, and constraints on her risk-taking. We propose a numerical method which can be used to analyze the impact of these influences. The model leads to several interesting and novel results concerning...

The problem of predicting 0-1-events is considered under general conditions, including stationary processes with short and long memory as well as processes with changing distribution patterns. Nonparametric estimates of the probability function and prediction intervals are obtained.

We consider the demand for state contingent claims in the presence of a zero-mean, nonhedgeable background risk. An agent is defined to be generalized risk averse if he/she reacts to an increase in background risk by choosing a demand function for contingent claims with a smaller slope. We show...

In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet- ric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are...

This paper considers estimation of the regression function and its derivatives in nonparametric regression with fractional time series errors. We focus on investigating the properties of a kernel dependent function V (delta) in the asymptotic variance and finding closed form formula of it, where...

This paper investigates dynamically optimal risk-taking by an expected-utility maximizing manager of a hedge fund. We examine the effects of variations on a compensation structure that includes a percentage management fee, a performance incentive for exceeding a specified highwater mark, and...