Mean-risk models using two risk measures: A multi-objective approach

This paper proposes a model for portfolio optimisation, in which distributions are characterised and compared on the basis of three statistics: the expected value, the variance and the CVaR at a specified confidence level. The problem is multi-objective and transformed into a single objective problem in which variance is minimised while constraints are imposed on the expected value and CVaR. In the case of discrete random variables, the problem is a quadratic program. The mean-variance (mean-CVaR) efficient solutions that are not dominated with respect to CVaR (variance) are particular efficient solutions of the proposed model. In addition, the model has efficient solutions that are discarded by both mean-variance and mean-CVaR models, although they may improve the return distribution. The model is tested on real data drawn from the FTSE 100 index. An analysis of the return distribution of the chosen portfolios is presented

Whole Farm Income Insurance in a Canadian Context

This paper employs mean-variance and mean-skewness optimization to investigate farmers’ crop choices under Gross Revenue Insurance (GRIP), Whole Farm Income Insurance, the Canadian Agricultural Income Stabilization program, and its modified 2008 program AgrInvest. To our knowledge this paper is the first to fully consider the endogenous optimization of whole farm insurance in a farm optimization model. The results indicate that farmers will alter farm plans significantly in response to the type of insurance offered and the level of subsidy. Farmers will take on production risks that they would not otherwise take and this risk taking behavior is exacerbated by subsidy.Agricultural Insurance, Skewness Maximization, Mean-Variance, Farm Income Insurance, GRIP, CAIS, AgrInvest, Agricultural Finance,

Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach

This paper proposes a nonparametric efficiency measurement approach for the static portfolio selection problem in mean-variance-skewness space. A shortage function is defined that looks for possible increases in return and skewness and decreases in variance. Global optimality is guaranteed for the resulting optimal portfolios. We also establish a link to a proper indirect mean-variance-skewness utility function. For computational reasons, the optimal portfolios resulting from this dual approach are only locally optimal. This framework permits to differentiate between portfolio efficiency and allocative efficiency, and a convexity efficiency component related to the difference between the primal, non-convex approach and the dual, convex approach. Furthermore, in principle, information can be retrieved about the revealed risk aversion and prudence of investors. An empirical section on a small sample of assets serves as an illustration.shortage function, efficient frontier, mean-variance-skewness, portfolios, risk aversion, prudence

Local Search Techniques for Constrained Portfolio Selection Problems

We consider the problem of selecting a portfolio of assets that provides the investor a suitable balance of expected return and risk. With respect to the seminal mean-variance model of Markowitz, we consider additional constraints on the cardinality of the portfolio and on the quantity of individual shares. Such constraints better capture the real-world trading system, but make the problem more difficult to be solved with exact methods. We explore the use of local search techniques, mainly tabu search, for the portfolio selection problem. We compare and combine previous work on portfolio selection that makes use of the local search approach and we propose new algorithms that combine different neighborhood relations. In addition, we show how the use of randomization and of a simple form of adaptiveness simplifies the setting of a large number of critical parameters. Finally, we show how our techniques perform on public benchmarks.Comment: 22 pages, 3 figure

Downside risk optimization in securitized real estate markets

Optimization of international securitized real estate portfolios has been a key topic for several decades. However, most previous analysis has focused on regional diversification by applying the traditional mean-variance (MV) framework suggested by Markowitz (1952) even if the limitations of this approach are well-known. Thus, we focus on a more suitable and appealing downside risk (DR) framework suggested by Estrada (2008), which applies a similar optimization algorithm as the MV framework. The analysis covers the eight largest securitized real estate markets from January 1990 to December 2009 and thus captures a more global perspective. The main findings are as follows: first, the return distributions are non-normally distributed and negatively skewed. Second, optimal portfolio weights differ substantially between the MV and DR approach. Third, portfolio weights are shifted from the U.S. and Australian market to the Dutch and the French market when applying the DR framework instead of the MV framework. Fourth, the dominance of the DR framework is well-documented by comparing out-of-sample performance. The empirical results are remarkable and emphasize the practical merit of the presented DR framework for investors and portfolio managers. --Downside Risk Analysis,International Real Estate Markets,Portfolio Management,Portfolio Optimization,Out-of-Sample Analysis

Does Portfolio Optimization Pay?

All HARA-utility investors with the same exponent invest in a single risky fund and the risk-free asset. In a continuous time-model stock proportions are proportional to the inverse local relative risk aversion of the investor (1/γ-rule). This paper analyses the conditions under which the optimal buy and holdportfolio of a HARA-investor can be approximated by the optimal portfolio of an investor with some low level of constant relative risk aversion using the 1/γ-rule. It turns out that the approximation works very well in markets without approximate arbitrage opportunities. In markets with high equity premiums this approximation may be of low quality.HARA-utility, portfolio choice, certainty equivalent, approximated choice

Different Risk Measures: Different Portfolio Compositions?

Traditionally, the measure of risk used in portfolio optimisation models is the variance. However, alternative measures of risk have many theoretical and practical advantages and it is peculiar therefore that they are not used more frequently. This may be because of the difficulty in deciding which measure of risk is best and any attempt to compare different risk measures may be a futile exercise until a common risk measure can be identified. To overcome this, another approach is considered, comparing the portfolio holdings produced by different risk measures, rather than the risk return trade-off. In this way we can see whether the risk measures used produce asset allocations that are essentially the same or very different. The results indicate that the portfolio compositions produced by different risk measures vary quite markedly from measure to measure. These findings have a practical consequence for the investor or fund manager because they suggest that the choice of model depends very much on the individual’s attitude to risk rather than any theoretical and/or practical advantages of one model over another.alternative risk models, portfolio compositions, simalarity indices

Hedging the exchange rate risk in international portfolio diversification : currency forwards versus currency options

As past research suggest, currency exposure risk is a main source of overall risk of international diversified portfolios. Thus, controlling the currency risk is an important instrument for controlling and improving investment performance of international investments. This study examines the effectiveness of controlling the currency risk for international diversified mixed asset portfolios via different hedge tools. Several hedging strategies, using currency forwards and currency options, were evaluated and compared with each other. Therefore, the stock and bond markets of the, United Kingdom, Germany, Japan, Switzerland, and the U.S, in the time period of January 1985 till December 2002, are considered. This is done form the point of view of a German investor. Due to highly skewed return distributions of options, the application of the traditional mean-variance framework for portfolio optimization is doubtful when options are considered. To account for this problem, a mean-LPM model is employed. Currency trends are also taken into account to check for the general dependence of time trends of currency movements and the relative potential gains of risk controlling strategies