We derive closed-form expressions for risk measures based on partial moments by assuming the Gram-Charlier (GC) density for stock returns. As a result, the lower partial moment (LPM) measures can be expressed as linear functions on both skewness and excess kurtosis. Under this framework, we study the behavior of portfolio rankings with performance measures based on partial moments, that is, both Farinelli-Tibiletti (FT) and Kappa ratios. Contrary to previous results, significant differences are found in ranking portfolios between the Sharpe ratio and the FT family. We also obtain closed-form expressions for LPMs under the semi non-parametric (SNP) distribution which allows higher flexibility than the GC distribution.Angel León would like to...
We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order mo...
We analyze the use of alternative performance measures to rank and select assets. Previous literatur...
In this paper using the expected utility theory and the approxi-mation analysis we derive a formula ...
We derive closed-form expressions for risk measures based on partial moments by assuming the Gram-Ch...
The classical mean-variance investment model is simple, elegant, and popular. As such, it is also su...
In this paper we study an extension of the Gram–Charlier (GC) density in Jondeau and Rockinger (2001...
The classical mean-variance model treats the upside and downside equally as risks. This feature is u...
In this paper, we have developed measures of evaluating portfolio-performance based on LPM (Lower-Pa...
International audienceWe introduce mixtures of probability distributions to model empirical distribu...
International audienceWe introduce mixtures of probability distributions to model empirical distribu...
International audienceWe introduce mixtures of probability distributions to model empirical distribu...
International audiencePerformance analysis is a key process in finance to evaluate or compare invest...
International audiencePerformance analysis is a key process in finance to evaluate or compare invest...
We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order mo...
We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order mo...
We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order mo...
We analyze the use of alternative performance measures to rank and select assets. Previous literatur...
In this paper using the expected utility theory and the approxi-mation analysis we derive a formula ...
We derive closed-form expressions for risk measures based on partial moments by assuming the Gram-Ch...
The classical mean-variance investment model is simple, elegant, and popular. As such, it is also su...
In this paper we study an extension of the Gram–Charlier (GC) density in Jondeau and Rockinger (2001...
The classical mean-variance model treats the upside and downside equally as risks. This feature is u...
In this paper, we have developed measures of evaluating portfolio-performance based on LPM (Lower-Pa...
International audienceWe introduce mixtures of probability distributions to model empirical distribu...
International audienceWe introduce mixtures of probability distributions to model empirical distribu...
International audienceWe introduce mixtures of probability distributions to model empirical distribu...
International audiencePerformance analysis is a key process in finance to evaluate or compare invest...
International audiencePerformance analysis is a key process in finance to evaluate or compare invest...
We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order mo...
We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order mo...
We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order mo...
We analyze the use of alternative performance measures to rank and select assets. Previous literatur...
In this paper using the expected utility theory and the approxi-mation analysis we derive a formula ...