In this paper we present a two-component portfolio selection problem under two types of uncertainties, i.e., probabilistic risk and possibilistic risk. We study the portfolio selection problem in mergers and acquisitions, M&As, and show the usability of the presented mixed model in portfolio selection of corporate acquisition targets. We view the total M&A value consisting of a stand-alone of a...

This paper addresses the issue of portfolio risk exposure as a function of age, and it focuses the debate by presenting detailed cross-sectional evidence about individual portfolios. It provides new empirical results that characterized the relationship between age and the risk exposure ofindividual portfolios. The evidence from cross-sectional data suggests that individuals do not follow behavi...

I introduce dynamic option trading and non-linear views into the classical portfolio selection problem. The optimal dynamic option portfolio is characterized explicitly in terms of its expected sensitivities (Greeks) and the role of the meanvariance efficient portfolio is played by the “Greek-efficient” portfolio. This is the portfolio that has the optimal sensitivities to chosen risk factors. ...

In this paper, we consider the problem of finding optimal portfolios in cases when the underlying probability model is not perfectly known. For the sake of robustness, a maximin approach is applied which uses a ”confidence set” for the probability distribution. The approach shows the tradeoff between return, risk and robustness in view of the model ambiguity. As a consequence, a monetary value ...

This paper discusses how to introduce liquidity into the well known mean-variance framework of portfolio selection using a representative sample of Spanish equity portfolios. Either by estimating mean-variance liquidity constrained frontiers or directly estimating optimal portfolios for alternative levels of risk aversion and preference for liquidity, we obtain strong effects of liquidity on op...

On the basis of Markowitz mean-variance framework, a new optimal portfolio selection approach is presented. The portfolio selection model proposed in the approach includes the expected return, the risk, and especially a quadratic type transaction cost of a portfolio. Using this model may yield an optimal portfolio solution that maximizes return, and minimizes risk, as well as also minimizes tra...

In this article, I explicitly solve dynamic portfolio choice problems, up to the solution of an ordinary differential equation (ODE), when the asset returns are quadratic and the agent has a constant relative risk aversion (CRRA) coefficient. My solution includes as special cases many existing explicit solutions of dynamic portfolio choice problems. I also present three applications that are no...

In this paper, two kinds of possibility distributions, namely, upper and lower possibility distributions are identi®ed to re ̄ect experts' knowledge in portfolio selection problems. Portfolio selection models based on these two kinds of distributions are formulated by quadratic programming problems. It can be said that a portfolio return based on the lower possibility distribution has smaller po...

Reinforcement learning algorithm has been successfully used in prediction and decision making [5,11]. The main contribution of this paper is to provide decision making using reinforcement learning approach to allocate resources optimally in stochastic conditions in a well known example; in the portfolio selection. The modern theories of portfolio selection consider some presumptions. But if the...

The business environment is full of uncertainty. Allocating the wealth among various asset classes may lower the risk of overall portfolio and increase the potential for more benefit over the long term. In this paper, we propose a mixed singlestage R&D projects and multi-stage securities portfolio selection model. Specifically, we present a bi-objective mixed-integer stochastic programming mode...