Multivariate stochastic dominance applied to sector-based portfolio selection

2020 ◽  
Author(s):  
Noureddine Kouaissah ◽  
Sergio Ortobelli Lozza
Keyword(s):  
Stochastic Dominance ◽  
Degrees Of Freedom ◽  
Equity Market ◽  
Risk Averse ◽  
Dispersion Parameters ◽  
Symmetric Distributions ◽  
Tail Behaviour ◽  
The Us ◽  
Student’S T ◽  
Stability Indices

Abstract In this study, we investigate whether sector-weighted portfolios based on alternative parametric assumptions are consistent with multivariate stochastic dominance (MSD) conditions for a class of non-satiable risk-averse investors. Focusing specifically on stable symmetric and Student’s t distributions, we propose and motivate an MSD rule to determine a partial order among sectors, based on a comparison between (i) location, (ii) dispersion parameters and (iii) either stability indices (for stable symmetric distributions) or degrees of freedom (for Student’s t distributions). The proposed MSD rule is applied to the US equity market to evaluate whether and how the derived stochastic dominance conditions are relevant to investors’ decisions. The empirical study confirms that the proposed MSD rule is effective and that the tail behaviour of returns is relevant to the optimization of portfolios for non-satiable investors.

scholarly journals Copulaesque Versions of the Skew-Normal and Skew-Student Distributions

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 815
Author(s):  
Christopher Adcock
Keyword(s):  
Distribution Function ◽  
Normal Distribution ◽  
Degrees Of Freedom ◽  
Special Functions ◽  
Normal Distribution Function ◽  
Skew Normal Distribution ◽  
Marginal Distributions ◽  
Student’S T ◽  
Normal Copula ◽  
Skew Normal

A recent paper presents an extension of the skew-normal distribution which is a copula. Under this model, the standardized marginal distributions are standard normal. The copula itself depends on the familiar skewing construction based on the normal distribution function. This paper is concerned with two topics. First, the paper presents a number of extensions of the skew-normal copula. Notably these include a case in which the standardized marginal distributions are Student’s t, with different degrees of freedom allowed for each margin. In this case the skewing function need not be the distribution function for Student’s t, but can depend on certain of the special functions. Secondly, several multivariate versions of the skew-normal copula model are presented. The paper contains several illustrative examples.

scholarly journals The disappearance of style in the US equity market

2007 ◽  
Vol 17 (8) ◽  
pp. 597-613 ◽  
Author(s):  
Soosung Hwang ◽  
Stephen E. Satchell
Keyword(s):  
Equity Market ◽  
The Us

scholarly journals International portfolio diversification: United States and south Asian equity markets

2014 ◽  
Vol 61 (2) ◽  
pp. 241-252 ◽  
Author(s):  
Rizwan Mushtaq ◽  
Zulfiqar Shah
Keyword(s):  
Stock Market ◽  
South Asian ◽  
Equity Markets ◽  
Equity Market ◽  
Causality Test ◽  
Market Index ◽  
International Portfolio Diversification ◽  
The Us ◽  
Short And Long Term

This paper explores the dynamic liaison between US and three developing South Asian equity markets in short and long term. To gauge the long-term relationship, we applied Johansen co-integration procedure as all the representative indices are found to be non-stationary at level. The findings illustrate that the US equity market index exhibits a reasonably different movement over time in contrast to the three developing equity markets under consideration. However, the Granger-causality test divulge that the direction of causality scamper from US equity market to the three South Asian markets. It further indicates that within the three developing equity markets the direction of causality emanates from Bombay stock market to Karachi and Colombo. Overall, the results of the study suggest that the American investors can get higher returns through international diversification into developing equity markets, while the US stock market would also be a gainful upshot for South Asian investors.

scholarly journals January effect: 200 years of evolution in the us stock market

2018 ◽  
Vol 2 (1) ◽  
pp. 27-33
Author(s):  
Alex Plastun ◽  
Vyacheslav Plastun
Keyword(s):  
Stock Market ◽  
January Effect ◽  
Simulation Approach ◽  
Comprehensive Investigation ◽  
Average Analysis ◽  
The Us ◽  
Student’S T ◽  
Xix Century ◽  
Trading Simulation ◽  
Student’S T Test

This paper is a comprehensive investigation of the January Effect evolution in the US stock market over the period 1791–2015. It employs various statistical techniques (average analysis, Student’s t-test, ANOVA, Mann-Whitney test) and a trading simulation approach to analyze the evolution of this anomaly. The results suggest that January effect during the XVIII–XXI century passed the way from rise to fall. The rise of the January Effect starts in the end of the XIX century and this anomaly mostly disappeared in middle of the XX century. Nowadays the January Effect is not present in the US stock market, but even today January stays one of the best months for purchases in the US stock market.

Evaluating the Efficiency of Portfolio-Hedging Strategies by Incorporating Third Degree Stochastic Dominance Criteria and Data Envelopment Analysis

2021 ◽  
pp. 22-46
Author(s):  
Margareta Gardijan Kedžo
Keyword(s):  
Data Envelopment Analysis ◽  
Stochastic Dominance ◽  
Data Envelopment ◽  
Risk Averse ◽  
Super Efficiency ◽  
Risk Hedging ◽  
The Third ◽  
Positive Skewness ◽  
Hedging Strategies ◽  
Efficient Hedging

The chapter investigates chosen hedging strategies with options as useful risk hedging instruments. Assuming that average investor prefers greater return, is risk-averse, and prefers greater positive skewness, the performance of different hedged and unhedged portfolios is evaluated using stochastic dominance (SD) criteria and data envelopment analysis (DEA). The SD is examined up to the third degree (TSD) using Davidson-Duclos (DD) test. In the DEA, a super efficiency BCC model is used. It is investigated how these two methodologies can be combined and how the TSD criteria can be integrated into DEA in order to simplify the analysis of determining efficient hedging strategies with options.

Nitrogen-Fixing Winter Cover Crops and Production Risk: A Case Study for No-Tillage Corn

1998 ◽  
Vol 30 (1) ◽  
pp. 163-174 ◽  
Author(s):  
James A. Larson ◽  
Roland K. Roberts ◽  
Donald D. Tyler ◽  
Bob N. Duck ◽  
Stephen P. Slinsky
Keyword(s):  
Cover Crops ◽  
Stochastic Dominance ◽  
Nitrogen Fertilization ◽  
Risk Averse ◽  
Production Risk ◽  
Risk Seeking ◽  
Wide Range ◽  
Seeking Behavior ◽  
Net Revenue ◽  
Applied Nitrogen

AbstractWinter legumes can substitute for applied nitrogen fertilization of corn. Stochastic dominance was used to order net revenues from legume and applied nitrogen alternatives. Stochastic dominance orderings indicate that systems combining vetch with low applied nitrogen fertilization (50 and 100 pounds/acre, respectively) were risk inefficient. By contrast, vetch and 150 pounds/acre applied nitrogen maximized expected net revenue and was risk efficient for a wide range of risk-averse and risk-seeking behavior. Farmers with these risk attitudes may not reduce applied nitrogen if they switch to a vetch cover. Extremely risk-averse or risk-seeking farmers would not prefer winter legumes.

Fractional Degree Stochastic Dominance

2020 ◽  
Vol 66 (10) ◽  
pp. 4630-4647 ◽  
Author(s):  
Rachel J. Huang ◽  
Larry Y. Tzeng ◽  
Lin Zhao
Keyword(s):  
Lower Bound ◽  
Risk Aversion ◽  
Stochastic Dominance ◽  
Absolute Risk ◽  
Comparative Statics ◽  
Risk Averse ◽  
Absolute Risk Aversion ◽  
Risk Apportionment ◽  
Lottery Choices ◽  
Increase In Risk

We develop a continuum of stochastic dominance rules for expected utility maximizers. The new rules encompass the traditional integer-degree stochastic dominance; between adjacent integer degrees, they formulate the consensus of individuals whose absolute risk aversion at the corresponding integer degree has a negative lower bound. By extending the concept of “uniform risk aversion” previously proposed in the literature to high-order risk preferences, we interpret the fractionalized degree parameter as a benchmark individual relative to whom all considered individuals are uniformly no less risk averse in the lottery choices. The equivalent distribution conditions for the new rules are provided, and the fractional degree “increase in risk” is defined. We generalize the previously defined notion of “risk apportionment” and demonstrate its usefulness in characterizing comparative statics of risk changes in fractional degrees. This paper was accepted by David Simchi-Levi, decision analysis.

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