We show that if an agent is uncertain about the precise form of his utility function, his actual relative risk aversion may depend on wealth even if he knows his utility function lies in the class of constant relative risk aversion (CRRA) utility functions. We illustrate the consequences of this...

This paper considers two alternative formulations of the linear factor model (LFM) with nontraded factors. The first formulation is the traditional LFM, where the estimation of risk premia and alphas is performed by means of a cross-sectional regression of average returns on betas. The second...

Reliable estimates of variances and covariances are crucial for portfolio management and risk controlling. This paper investigates alternative methods to estimate time varying variance-covariance matrices: ordinary estimates and exponentially weighted moving averages in comparison to Markov...

Portfolio choice is usually modelled by von Neumann-Morgenstern utility. Risk-value models are more general and permit the derivation of risk-value efficient frontiers. A behaviorally based risk measure with an endogenous or exogenous benchmark is used to derive efficient portfolios and to...

The current discussion about stability of the European money demand function is flawed by a confusion of two different concepts of stability (adjustment speed versus error variance). The meaning and importance of the underlying notions of stability is clarified. It is demonstrated that necessary...

In der Makroökonomik werden Liquiditätsfallen ohne Mikrofundierung als existent angenommen und die Japan-Krise hat Liquiditätsfallen wieder zum Diskussionsthema gemacht. Deshalb wird die Frage der Existenz von Liquiditätsfallen hier portfolio-theoretisch untersucht im Rahmen eines...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...