The mean-variance theory of Markowitz (1952) indicates that large investment portfolios naturally provide better risk diversification than small ones. However, due to parameter estimation errors, one may find ambiguous results in practice. Hence, it is essential to identify relevant stocks to alleviate the impact of estimation error in portfolio selection. To this end, we propose a linkage condition to link the relevant and irrelevant stock returns via their conditional regression relationship. Subsequently, we obtain a BIC selection criterion that enables us to identify relevant stocks consistently. Numerical studies indicate that BIC outperforms commonly used portfolio strategies in the literature. (C) 2011 Elsevier B.V. All rights reserv...
One of the main issues in portfolio selection models consists in assessing the effect of the estimat...
How investors should allocate assets to their portfolios in the presence of predictable components i...
Bayesian model selection is a fundamental part of the Bayesian statistical modeling process. The qua...
This paper deals with a traditional method for creating portfolios of financial assets known as the ...
We employ a statistical criterion (out-of-sample hit rate) and a financial market measure (portfolio...
Summarization: In 1952, Markowitz published his famous paper on portfolio selection that transformed...
This paper contributes to portfolio selection methodology using a Bayesian fore-cast of the distribu...
Model selection starts with a dataset and a number of candidate models that can explain that data. T...
In this article, we consider the portfolio selection problem as a Bayesian decision problem. We comp...
This thesis concerns portfolio theory from a Bayesian perspective and it includes two papers related...
This thesis began with an introduction and literature review in Chapter 1. In Chapter 2, I propose a...
Markowitz portfolio selection is challenged by huge implementation barriers. This paper addresses th...
Preliminary and incomplete The mean-variance principle of Markowitz (1952) for portfolio selection g...
In this paper, we introduce a new portfolio selection method. Our method is innovative and flexible....
We model portfolio weights as a function of latent factors that summarize the information in a large...
One of the main issues in portfolio selection models consists in assessing the effect of the estimat...
How investors should allocate assets to their portfolios in the presence of predictable components i...
Bayesian model selection is a fundamental part of the Bayesian statistical modeling process. The qua...
This paper deals with a traditional method for creating portfolios of financial assets known as the ...
We employ a statistical criterion (out-of-sample hit rate) and a financial market measure (portfolio...
Summarization: In 1952, Markowitz published his famous paper on portfolio selection that transformed...
This paper contributes to portfolio selection methodology using a Bayesian fore-cast of the distribu...
Model selection starts with a dataset and a number of candidate models that can explain that data. T...
In this article, we consider the portfolio selection problem as a Bayesian decision problem. We comp...
This thesis concerns portfolio theory from a Bayesian perspective and it includes two papers related...
This thesis began with an introduction and literature review in Chapter 1. In Chapter 2, I propose a...
Markowitz portfolio selection is challenged by huge implementation barriers. This paper addresses th...
Preliminary and incomplete The mean-variance principle of Markowitz (1952) for portfolio selection g...
In this paper, we introduce a new portfolio selection method. Our method is innovative and flexible....
We model portfolio weights as a function of latent factors that summarize the information in a large...
One of the main issues in portfolio selection models consists in assessing the effect of the estimat...
How investors should allocate assets to their portfolios in the presence of predictable components i...
Bayesian model selection is a fundamental part of the Bayesian statistical modeling process. The qua...