Comparison of Risk Minimizing and Return Maximizing Portfolio Models

1 . Bayesian Network Models of Portfolio Risk and Return

A Bayesian network is a tool for modeling large multivariate probability models and for making inferences from such models. A Bayesian network combines traditional quantitative analysis with expert judgement in an intuitive, graphical representation. In this paper, we show how to use Bayesian networks to model portfolio risk and return. Traditional financial models emphasize the historical rela...

Risk-Return Optimization of the Bank Portfolio

In an intensifying competition banks are forced to develop and implement enterprise wide integrated risk-return management systems. Financial risks have to be limited and managed from a bank wide portfolio perspective. Risk management rules must be accomplished from internal and regulatory points of view. Expected returns need to be maximized subject to these constraints, leading to a generaliz...

Bond Portfolio Optimization: A Risk-Return Approach

In this paper, we apply Markowitz’s approach of portfolio selection to government bond portfolios. As a main feature of our analysis, we use term structure models to estimate expected returns, return variances, and covariances of different bonds. Our empirical study for the German market shows that a small number of risky bonds is sufficient to reach very promising predicted risk-return profile...

Minimizing Breaks by Maximizing

Stock Return Predictability, Conditional Asset Pricing Models and Portfolio Selection

I examine an investor’s portfolio allocation problem across multiple risky assets in the presence of return predictability when, in addition to the predictability evidence, the investor uses conditional asset pricing models to guide him in the portfolio selection decision. I also explore how the uncertainty associated with the model dynamics affects the investor’s optimal portfolio. To analyze ...