Record Details

Aggregate Portfolio Risk Approximation under Bayesian Setting

Euro-Asian Journal of Economics and Finance

View Archive Info
 
 
Field Value
 
Title Aggregate Portfolio Risk Approximation under Bayesian Setting
 
Creator Habibi, Reza
 
Subject Bayesian CAPM and APT; Copula; Dirichlet distribution; MCMC; Mixture distribution; Model Risk software; Posterior approximation; Stochastic approximation
 
Description In portfolio management, it is too important to consider non-sampling information. In this problem, the non-sampling information may be belief of investor about a special asset obtained of historical data of past economical performance of specified asset. This information forms a prior probability regard keeping the asset in portfolio or dropping it. Therefore, for each asset a binary random variable is induced to the problem which is one if the asset will be kept in portfolio and zero if it will be dropped based on investor prior belief about the asset before observing the actual risk and return. These variables are correlated come from a Dirichlet distribution. Hence, the Bayesian setting is a suitable framework to study this problem. In this paper, the Monte Carlo method is applied to approximate the posterior distribution using Monte Carlo Markov Chain (MCMC) method of binary variables given the past returns which indicates the tendency of investor to keep or drop an asset by using the non-sampling and sampling information simultaneously. ModelRisk software is used to derive the analytical results. Bayesian CAPM and APT are proposed. Stochastic approximations are given.
 
Publisher Academy of Business & Scientific Research
 
Date 2016-04-19
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://absronline.org/journals/index.php/eajef/article/view/664
 
Source Euro-Asian Journal of Economics and Finance; Vol 4 No 2 (2016): April; 27-33
2310-4929
2310-0184
 
Language eng
 
Relation http://absronline.org/journals/index.php/eajef/article/view/664/683
 
Rights Copyright (c) 2016 Euro-Asian Journal of Economics and Finance