Modern portfolio theory is based on the relationship between risk and return and in this paper, specific uncertainty conditions are introduced as ambiguity which affects the asset pricing. Also, the relationship between risk, ambiguity and return is examined. First, ambiguity is estimated by the means of three-variable and main component method, trading volume, ask-bid spread, error of earnings...

Abstract. The portfolio optimization problem is formulated as a multi-objective mixed integer program. The problem considered is based on a single period model of investment. The problem objective is to allocate wealth on different assets to maximize the weighted difference of the portfolio expected return, the threshold of the probability that the return is not less than a required level and t...

Existing studies find that size, book-to-market, momentum and liquidity explain the crosssection of average returns, but debate continues over whether these variables are risk factors. We propose a new test of whether a candidate variable is a priced risk factor. Specifically, we test whether there is a relationship between the conditional mean and conditional variance of the return on the cand...

We propose a new multiple-benchmark tracking-error model for portfolio selection problem. The tracking error of a portfolio from a set of benchmark portfolios is defined as the difference between its return and the highest return from the set of benchmarks. We derive closedform solution of our portfolio strategy, whose main component is the sum of the benchmark portfolios weighted by their resp...

modern portfolio theories are based on markowitz’s portfolio optimization model that involves the assumption of mean variance behavior and therefore require the asymmetry and normality of returns. this issue also affects the capital asset pricing model that estimates systematic risk and uses it in pricing securities. this article analyzes the various measures of risk. the main purpose of this r...

Genetic algorithms (GA) are stochastic search techniques based on the mechanics of natural selection and natural genetics. In this paper, the adaptive genetic algorithms are applied to solve the portfolio selection problem in which there exist both probability constraint on the lowest return rate of portfolio and lower and upper bounds constraints on the investment rates to assets. First, the s...

Motivated by the fact that hedge funds staffs more often than not face the problem of optimal asset allocation for large portfolios of investable stocks, In this study we propose a new theoretical framework based on the large deviations theory to select an optimal investment strategy for a large portfolio such that the risk, which is defined as the probability that the portfolio return underper...

One of the most important duties of financial economy is modeling and forecasting the volatilities of price of risky assets. From analysts and policy makers’ view, price volatility is a key variable contributing to perception of market volatilities. Therefore, analysts need to have an appropriate of forecast of price volatility as a necessary input to perform duties such as risk management, por...

We propose a new approach to portfolio optimization by separating asset return distributions into positive and negative half-spaces. The approach minimizes a so-called Partitioned Value-atRisk (PVaR) measure by using half-space statistical information. Using simulated and real data, the PVaR approach generates better risk-return tradeoffs in the optimal portfolios when compared to Markowitz mea...

this research aims to design the portfolio entrepreneurship model and to analyze the effect of social capital, prior experience and knowledge, the entrepreneur’s financial resources, as well as human capital on portfolio entrepreneurship and also to investigate the effect of portfolio entrepreneurship on recognition of new opportunities, as well as business growth and development. the research ...