The paper considers the evolution of portfolio rules in incomplete markets with stationary returns and endogenous prices. The ultimate success of a portfolio rule is measured by the wealth share the rule is eventually able to conquer in competition with other portfolio rules. We give necessary and sufficient conditions for portfolio rules to be evolutionary stable in an incomplete market. In th...

In conventional mean-variance model of portfolio optimization problem the expected return is taken as the mean of the past returns. This assumption is not correct and hence the method leads to poor portfolio optimization performance. Hence an alternative but efficient method is proposed in which the mean and variance of expected return are first predicted with a low complexity functional link a...

Credit allocation through the usage of Portfolio optimization mainly seeks tomaximize return and minimize the risk of the portfolio; but there are other importantissues including sustainable development which is important for government/publicsectors. This paper presents a novel credit allocation approach based on portfoliooptimization and investigates the effects of selected indicators of sust...

This paper will investigate the optimum portfolio for an investor, taking into account 5 criteria. The mean variance model of portfolio optimization that was introduced by Markowitz includes two objective functions; these two criteria, risk and return do not encompass all of the information about investment; information like annual dividends, S&P star ranking and return in later years which is ...

The DASH model for Power Portfolio Optimization provides a tool which helps decision-makers coordinate production decisions with opportunities in the wholesale power market. The methodology is based on a stochastic programming model which selects portfolio positions that perform well on a variety of scenarios generated through statistical modeling and optimization. When compared with a commonly...

This paper presents an approach for portfolio selection using evolutionary programming as a tool for optimization. The goal is to find the mix of stocks that minimize risk expressed as standard deviation for a certain expected return. Two alternatives approaches are developed (Hillclimbing and Random) to measure the performance of the modified genetic algorithm. Key-Words: Evolutionary Computin...

We study the uniqueness of viscosity solutions of a Hamilton-Jacobi-Bellman equation which arises in a portfolio optimization problem in which an investor maximizes expected utility of terminal wealth in the presence of proportional transaction costs. Our main contribution is that the comparison theorem can be applied to prove the uniqueness of the value function in the portfolio optimization p...

Portfolio optimization under downside risk while preserving the upside is of crucial importance to asset managers. In the Black-Scholes setting, we consider one such particular measure given by the notion of capital-at-risk. This paper generalizes the work of Emmer et al., 2001, to the case of time dependent parameters and investment strategies, i.e., continuous-time portfolio optimization, and...

We consider some further applications of martingale pricing to problems in financial engineering. In particular, we will show how dynamic portfolio optimization problems in complete markets may be solved using martingale pricing methods. We will see, as a result, how the problems of security pricing and portfolio optimization are very closely related. We then introduce real options and discuss ...