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Distributionally Robust Portfolio Optimization under Marginal and Copula Ambiguity

Fan, Zhengyang; Ji, Ran; Lejeune, Miguel - 2022

We investigate a new family of distributionally robust optimization problem under marginal and copula ambiguity with applications to portfolio optimization problems. The proposed model considers the ambiguity set of portfolio return in which the marginal distributions and their copula are close...

Persistent link: https://www.econbiz.de/10014256348

Where is the Distribution Tail Threshold? A Tale on Tail and Copulas in Financial Risk Measurement

González Sánchez, Mariano; Nave, Juan Miguel - 2022

Estimating the market risk is conditioned by the fat tail of the distribution of returns. But the tail index depends on …, from this decomposition, we estimate extreme depence correlation matrix which is used in the measurement of portfolio risk …-Smirnov distance, and its unnecessary capital consumption is lower. Also, in the measurement of the risk of a portfolio, the results of …

Persistent link: https://www.econbiz.de/10013492616

Modeling multivariate extreme events using self-exciting point processes

Grothe, Oliver; Korniichuk, Volodymyr; Manner, Hans - In: Journal of econometrics 182 (2014) 2, pp. 269-289

Persistent link: https://www.econbiz.de/10010497083

Continuous multivariate distributions

Kotz, Samuel; Balakrishnan, Narayanaswamy; Johnson, … - 2000

Persistent link: https://www.econbiz.de/10001433283

Prediction by Regression in Multivariate Normal Distributions

Sclove, Stanley L. - 2011

In the context of the multivariate Normal regression model, a mean squared error of prediction is developed for making the choice of subset of explanatory variables for predicting the response variable in future samples

Persistent link: https://www.econbiz.de/10014186189

The Calculation of Multivariate Normal Probabilities Using a Re-Summed Tetrachoric Series Approximation

Clayton, Michael A. - 2017

Persistent link: https://www.econbiz.de/10012968358

Nonparametric Forecasting of Multivariate Probability Density Functions

Guégan, Dominique - 2018

The study of dependence between random variables is the core of theoretical and applied statistics. Static and dynamic copula models are useful for describing the dependence structure, which is fully encrypted in the copula probability density function. However, these models are not always able...

Persistent link: https://www.econbiz.de/10012917229

Multivariate Tweedie Distributions and Some Related Capital-at-Risk Analysis

Furman, Edward - 2010

unstudied so far. We investigate various properties of MTwF and discuss its possible applications to financial risk management …

Persistent link: https://www.econbiz.de/10013139810

Bayesian Inference in Multivariate Stable Distributions

Tsionas, Efthymios G. - 2013

In this paper we take up Bayesian inference in general, multivariate stable distributions. We use approximate Bayesian computation (ABC) along with carefully crafted proposal distributions for the implementation of MCMC. The problem of selecting summary statistics in ABC is resolved through the...

Persistent link: https://www.econbiz.de/10013087020

Topological Features of Multivariate Distributions : Dependency on the Covariance Matrix

Leaverton, Lloyd; Katz, Yuri A.; Vives, Josep - 2021

Topological data analysis provides a new perspective on many problems in the domain of complex systems. Here, we establish the dependency of the mean value of functional $p$-norms of 'persistence landscapes' on a uniform scaling of the underlying multivariate distribution. Furthermore, we...

Persistent link: https://www.econbiz.de/10013231130