the current study addresses an estimation of investor's optimal portfolio under conditions of uncertainty by using a combination of artificial neural network and markowitz models. for this purpose, such assets as stock prices, house prices, coin and bonds price are used with monthly data over the period 1378-1392. three variables including inflation uncertainty, oil uncertainty and free ma...

Let the random (stock market) vector X 2 0 be drawn according to a known distribution function F(x), x E R ". A log-optimal portfolio b* is any portfolio b achieving maximal expected log return W* = sup,, E In b'X, where the supremum is over the simplex b 2 0, Cr, b, = 1. An algorithm is presented for finding b*. The algorithm consists of replacing the portfolio b by the expected portfolio b', ...

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...

The growth-optimal portfolio optimization strategy pioneered by Kelly is based on constant portfolio rebalancing which makes it sensitive to transaction fees. We examine the effect of fees on an example of a risky asset with a binary return distribution and show that the fees may give rise to an optimal period of portfolio rebalancing. The optimal period is found analytically in the case of log...

Investor decision making has always been affected by two factors: risk and returns. Considering risk, the investor expects an acceptable return on the investment decision horizon. Accordingly, defining goals and constraints for each investor can have unique prioritization. This paper develops several approaches to multi criteria portfolio optimization. The maximization of stock returns, the pow...

Mean-variance criterion has long been the main stream approach in the optimal portfolio theory. The investors try to make a balance between the risk and return on their portfolio. In this paper, the deviation of the asset return from the investor’s expectation in the worst scenario is taken as the measure of risk for portfolio selection. One important advantage of this approach is that the inve...

The evaluation of a portfolio and its risk exposure with respect to market movements become di cult as soon as contingent claims are involved. In case only the performance of a portfolio has to be determined, practitioners use the mark-to-market pricing each trading day and observe the value changes of the underlying portfolio ex post. A price series becomes available which reveals not only the...

Robust portfolio optimization aims to maximize the worst-case portfolio return given that the asset returns are allowed to vary within a prescribed uncertainty set. If the uncertainty set is not too large, the resulting portfolio performs well under normal market conditions. However, its performance may substantially degrade in the presence of market crashes, that is, if the asset returns mater...

In this paper we consider the robust portfolio selection problem involving two types of uncertainties; the uncertainty in the distribution of exit time and the uncertainty in the distribution of portfolio return conditional on exit time. To deal with these uncertainties, we propose a tractable approach by applying worst-case VaR strategy to the case where partial information on the exit time di...

T paper proposes a generalized measure of riskiness that nests the original measures pioneered by Aumann and Serrano (Aumann, R. J., R. Serrano. 2008. An economic index of riskiness. J. Political Econom. 116(5) 810–836) and Foster and Hart (Foster, D. P., S. Hart. 2009. An operational measure of riskiness. J. Political Econom. 117(5) 785–814). The paper introduces the generalized options’ impli...