ORDINARY AND GENERALIZED STOCHASTIC DOMINANCE: A PRIMER

Research Methods/ Statistical Methods,

Two-moment decision model for location-scale family with background asset

This paper studies the impact of background risk on the indifference curve. We first study the shape of the indifference curves for the investment with background risk for risk averters, risk seekers, and risk-neutral investors. Thereafter, we study the comparative statics of the change in the shapes of the indifference curves when the means and the standard deviations of the returns of the financial asset and/or the background asset change. In addition, we draw inference on risk vulnerability and investment decisions in financial crises and bull and bear markets

Expected Utility Maximization and Conditional Value-at-Risk Deviation-based Sharpe Ratio in Dynamic Stochastic Portfolio Optimization

In this paper we investigate the expected terminal utility maximization approach for a dynamic stochastic portfolio optimization problem. We solve it numerically by solving an evolutionary Hamilton-Jacobi-Bellman equation which is transformed by means of the Riccati transformation. We examine the dependence of the results on the shape of a chosen utility function in regard to the associated risk aversion level. We define the Conditional value-at-risk deviation ($CVaRD$) based Sharpe ratio for measuring risk-adjusted performance of a dynamic portfolio. We compute optimal strategies for a portfolio investment problem motivated by the German DAX 30 Index and we evaluate and analyze the dependence of the $CVaRD$-based Sharpe ratio on the utility function and the associated risk aversion level

Conservation Payments under Risk: A Stochastic Dominance Approach

Conservation payments can be used to preserve forest and agroforest systems. To explain landowners’ land-use decisions and determine appropriate conservation payments, it is necessary to focus on revenue risk. Marginal conditional stochastic dominance rules are used to derive conditions for determining the conservation payments required to guarantee that the environmentally-preferred land use dominates. An empirical application to shaded-coffee protection in the biologically important Chocó region of West-Ecuador shows that conservation payments required for preserving shaded-coffee areas are much higher than those calculated under risk-neutral assumptions. Further, the extant distribution of land has strong impacts on the required payments.agroforest systems, conservation payments, land allocation, portfolio diversification, risk, stochastic dominance

TESTS FOR THE ROLE OF RISK AVERSION ON INPUT USE

Agricultural inputs can create negative externalities. For risk averting agents, risk will alter production decisions while the existence of institutions to insure against adverse states of nature will likely restore decisions toward levels under risk neutrality. In this paper, conditions are identified on a stochastic technology to test that risk averters choose smaller input levels than risk neutral agents, and that an increase in risk aversion reduces input use. A robust statistical method (Klecan, McFadden, and McFadden) to test for dominance is adapted to stochastic production relations. It is found that the first hypothesis is likely true for nitrogen application on Iowa corn. Weaker evidence is found in favor of the second hypothesis.dominance tests, incomplete risk markets, ollution, stochastic technology, Farm Management, Risk and Uncertainty,

Testing for Third-Order Stochastic Dominance with Diversification Possibilities

We derive an empirical test for third-order stochastic dominance that allows fordiversification between choice alternatives. The test can be computed usingstraightforward linear programming. Bootstrapping techniques and asymptoticdistribution theory can approximate the sampling properties of the test results and allowfor statistical inference. Our approach is illustrated using real-life US stock market data.efficiency;stochastic dominance;portfolio selection;linear programming;portfolio evaluation

STOCHASTIC TECHNOLOGY, RISK PREFERENCES AND ADOPTION OF SITE-SPECIFIC TECHNOLOGIES

This paper develops a model of farmer decision-making to examine the extent to which uncertainties about the performance of site-specific technologies (SSTs) and about the weather impact the value of these technologies. The model uses the jointly estimated risk and technology parameters to examine the impacts of SSTs on returns and nitrogen pollution. The availability of uncertain soil information and production uncertainty can lead risk-averse farmers to apply more fertilizers and generate more pollution. Ignoring the impact of uncertainty and risk preferences of farmers leads to a significant overestimation of the economic and environmental benefits of SSTs and underestimation of the required subsidy for inducing adoption of SSTs. The model that accounts for uncertainties about soil conditions and production as well as risk preferences of farmers provides an explanation for the low observed adoption rates of SSTs. Improvements in the accuracy of SSTs have the potential to increase the incentives for adoption.spatial variability, risk preferences, joint estimation, uncertainty, technology adoption, nitrogen runoff, Research and Development/Tech Change/Emerging Technologies,

Stochastic Dominance Efficiency Tests under Diversification

This paper focuses on Stochastic Dominance (SD) efficiency in a finite empirical panel data. We analytically characterize the sets of unsorted time series that dominate a given evaluated distribution by the First, Second, and Third order SD. Using these insights, we develop simple Linear Programming and 0-1 Mixed Integer Linear Programming tests of SD efficiency. The advantage to the earlier efficiency tests is that the proposed approach explicitly accounts for diversification. Allowing for diversification can both improve the power of the empirical SD tests, and enable SD based portfolio optimization. A simple numerical example illustrates the SD efficiency tests. Discussion on the application potential and the future research directions concludes.Stochastic Dominance, Protfolio Choice, Efficiency, Diversification, Mathematical Programming

Stochastic Dominance: Convexity and Some Efficiency Tests

This paper points out the importance of Stochastic Dominance (SD) efficient sets being convex. We review classic convexity and efficient set characterization results on SD efficiency of a given portfolio relative to a diversified set of assets and generalize them in the following aspects. First, we broaden the class of individual utilities in Rubinstein (1974) that lead to two-fund separation. Secondly, we propose a linear programming SSD test that is more efficient than that of Post (2003) and expand the SSD efficiency criteria developed by Dybvig and Ross (1982) onto the Third Order Stochastic Dominance and further to Decreasing Absolute and Increasing Relative Risk Aversion Stochastic Dominance. The efficient sets for those are finite unions of convex sets

Testing for Stochastic Dominance with Diversification Possibilities

We derive empirical tests for stochastic dominance that allow for diversification betweenchoice alternatives. The tests can be computed using straightforward linearprogramming. Bootstrapping techniques and asymptotic distribution theory canapproximate the sampling properties of the test results and allow for statistical inference.Our results could provide a stimulus to the further proliferation of stochastic dominancefor the problem of portfolio selection and evaluation (as well as other choice problemsunder uncertainty that involve diversification possibilities). An empirical application forUS stock market data illustrates our approach.stochastic dominance;portfolio selection;linear programming;portfolio diversification;portfolio evaluation