Stochastic Dominance Approach Research Articles

A comparison of the gold-oil portfolio and oil portfolio: A stochastic dominance approach

Using the stochastic dominance (SD) approach, this paper examines whether the gold-oil portfolio return stochastically dominates the oil portfolio return. The SD results show that the gold-oil portfolio stochastically dominates the one without gold at the SSD and TSD orders. We also find that portfolio risk decreases as we add more gold into the oil portfolios. This indicates that risk-averse investors in the oil market should include gold in their portfolios to maximize their expected utilities. The findings of this paper suggest that investors may design appropriate investments with gold to diversify their oil portfolios.

A Stochastic Dominance Approach to Evaluating Pro-Poor Growth—An Application to the Spanish Case

In this paper, we analyze, in a novel way, the nature of economic growth in Spain after the Great Recession, in relation to its effect on poverty reduction. We use a statistical test to analyze the pro-poorness nature of economic growth using a stochastic dominance approach, not used in this context so far. We decompose changes in the difference in generalized Lorenz ordinates into a growth effect and an inequality effect and apply this to formal Spanish income data statistical tests based on dominance methods. We found that growth was pro-poor in Spain as a whole between 2013 and 2017. As regards regional growth effects, we conclude that growth was weakly pro-poor in seven of Spain’s 17 regions, it was neither pro-poor nor anti-poor in nine regions, and only weakly anti-poor in one region.

Should Investors Choose Both the Highest-Return and Small-Variance Assets When the Mean-Variance Rule Says No? A Study of Health Care and T-Bill in the Investment

The high-speed growth of the health care sector has given this sector an increasingly important role in the stock market. This sector however has the highest mean in our study and a low correlation with the business cycle. On the other hand, T-Bill is also an important asset in investment because of its positive return and low variance. In this paper, we examine the conjecture of whether investors should choose both the highest-return and small-variance assets even when the mean-variance rule says “NO”. This conjecture is explored by making a comparison of the performance of portfolios with and without health care and 6-M T-bill in the U.S. market using portfolio optimization, mean-variance and stochastic dominance approaches. Our findings imply that all risk averters prefer to invest in portfolios with both health care and 6-M T-bill, regardless of whether they buy long or sell short in the market. Our findings do not support the existence of any arbitrage opportunity in the markets we studied but do support market efficiency. We also show that risk averters as well as investors with components of both risk aversion and risk seeking will choose both the highest-return and small-variance assets even when the mean-variance rule says NO.

Gold and portfolio diversification: A stochastic dominance analysis of the Dow Jones Islamic indices

This study examines the role of gold in diversification of eight Dow Jones Islamic stock index portfolios from 1996 to 2017. Using stochastic dominance (SD) approach, it tests the null hypothesis that gold-Islamic stock portfolio return does not dominate (outperform) non-gold Islamic stock portfolio return. The results show that a gold-Islamic stock portfolio stochastically dominates one without gold at the FSD, SSD, and TSD orders in all Islamic stock indices. Moreover, the level of SD order increases when we add more gold to the portfolio. We find that the SD order is manifest during the financial crisis (2007–2009) at all percentage holdings of gold. This indicates that risk-averse investors in Islamic stock indices should include gold in their portfolios to maximize their expected utilities. Furthermore, the results of mean variance (MV) analysis are consistent with the ones of SD. Our findings suggest that investors may design appropriate investments with gold to diversify their Islamic stock portfolios.

Are the Combinations of Health Care Sector and T-Bill One of the Best Choices for Investment?

Health care sector plays an increasingly important role in the stock market because it is growing nearly in the entire period and has low correlation with the business cycle. On the other hand, T-Bill is also an important asset in investment because it has positive return and small variance. In this paper, we employ the mean-variance (MV) rules and stochastic dominance (SD) approach to investigate the portfolio performance with and without both health care sector and T-Bill in the US over the period from September 1986 to May 2017. The results show that all the portfolios with health care asset and 6-M TB significantly dominate the corresponding portfolios without health care and 6-M TB, regardless whether short sale is allowed. This study also concludes that the combinations of health care sector and 6-M TB not only reduce risk but also gain better return and all risk-averse investors prefer to invest in portfolios with health care sector and 6-M TB, regardless whether they buy long or sell short the market. By employing the mean-variance (MV) rules and stochastic dominance (SD) approach, this paper investigates the portfolio performance with and without both health care sector and T-Bill in the U.S. market over the period from September 1986 to May 2017. The results show that all the portfolios with health care asset and 6-m TB significantly dominate the corresponding portfolios without health care and 6-m TB, regardless whether short sale is allowed. This study also concludes that the combinations of health care sector and 6-m TB not only reduce risk but also gain better return; all risk-averse investors prefer to invest in portfolios with health care sector and 6-m TB, regardless whether they buy long or sell short the market.

A practical assessment of risk-averse approaches in production lot-sizing problems

ABSTRACTThis paper presents an empirical assessment of four state-of-the-art risk-averse approaches to deal with the capacitated lot-sizing problem under stochastic demand. We analyse two mean-risk models based on the semideviation and on the conditional value-at-risk risk measures, and alternate first and second-order stochastic dominance approaches. The extensive computational experiments based on different instances characteristics and on a case-study suggest that CVaR exhibits a good trade-off between risk and performance, followed by the semideviation and first-order stochastic dominance approach. For all approaches, enforcing risk-aversion helps to reduce the cost-standard deviation substantially, which is usually accomplished via increasing production rates. Overall, we can say that very risk-averse decision-makers would be willing to pay an increased price to have a much less risky solution given by CVaR. In less risk-averse settings, though, semideviation and first-order stochastic dominance can be appealing alternatives to provide significantly more stable production planning costs with a marginal increase of the expected costs.

Eastern Halloween Effect: A Stochastic Dominance Approach

The Eastern market wisdom of “May is poor, June is bleak, and July will turn around” unveils an international stock markets dynamic that lower returns in May followed by even worse return in June but rebounding back to an upward trend in July. This wisdom is termed as “Eastern Halloween” effect in this paper which has some similarities with the traditional Halloween Effect. However, the traditional risk approach both fail to explain this Eastern Halloween effect satisfactorily. We apply Stochastic Dominance method to examine the Eastern Halloween effect and provide a solid evidence of existence of Eastern Halloween effect.

Testing the Monthly Calendar Anomaly of Stock Returns in Pakistan: A Stochastic Dominance Approach

In this paper, we first examine the presence of monthly calendar anomaly in Pakistan Stock Exchange (PSX) using aggregate and firm-level monthly stock returns. Secondly, we classify the sample firms into low-beta, medium-beta, and high-beta firms to examine the monthly anomaly of stock returns for firms having different level of systematic risk. By considering the stochastic dominance approach (SDA), we employ the simulation based method of Barrett and Donald (2003) to identify the dominant month over the period from January 2000 to December 2017. We find significant evidence of the existence of the January effect in both firm and market stock returns. We also find that the January effect exists more prominently in both low-risk and high-risk firms categorised based on their systematic risk. On the other end of the continuum, for moderately risky firms, there is strong evidence of the presence of the December effect. One of possible explanations of the January effect is the yearend bonus received in the month of January. Such bonuses are generally used to purchase stocks, causing the bullish trend of stock prices in January. However, the evidence of the January anomaly in both low-beta and high-beta portfolios returns is puzzling, suggesting that investors may invest in both low- and high-risk stocks when enthusiastically investing in stock market. The findings of the paper suggest that investors may get abnormal returns by forecasting stock return patterns and designing their investment strategies by taking into account the January and December effects and the level of systematic risk associated with the firms. JEL Classification: G02, G12, G14 Keywords: Behavioural Finance, Stochastic Dominance Approach, Monthly Anomaly, January Effect, December Effect, TOY Anomaly, Abnormal Returns, KS Type Test, PSX

Stochastic Dominance Approach to Measuring Child Development

We measure global performance when it comes to child development outcomes based on Save the Children UK’s Child Development Index, a composite measure comprising health, education, and nutrition. We rely on consistent tests of stochastic dominance efficiency to derive the most optimistic scenario for measured child development where more countries achieve better measured outcomes based on the least variable combination of components of the index. Using the same approach, we also derive the most pessimistic scenario where more countries achieve worse measured outcomes. This approach presents an opportunity to study the sensitivity of the Child Development Index and allows us to better understand the aspects of child development by offering a glimpse into the index components most responsible for driving or hindering improvements in measured child development across countries. To gain a sense of the evolution of the dimensions, we consider four time periods: 1995 - 1999, 2000 - 2004, 2005 - 2010, and 2011 - 2016. We find that in the most optimistic scenario for measured child development, increasing the weight attached to the education dimension over time allows more countries to achieve better measured outcomes. On the other hand, shifting majority of the weight towards health results in the most pessimistic scenario. These results indicate that improvements in children’s education outcomes have outpaced health and nutrition. That is, relative to health and nutrition, more countries find it easier to achieve better education outcomes.

Is wine a good choice for investment?

We extend our understanding on the role of wine investment within a portfolio of different assets (US/UK equities, bonds, gold, and housing) by considering a rich methodology based, among others, on the mean-variance and stochastic-dominance approaches. The main findings suggest that wine is the best investment among all individual assets under study, and investors prefer to invest in with-wine portfolios than without-wine portfolios to gain higher expected utility when short selling is not allowed. However, investors are indifferent between portfolios with and without wine when short-selling is allowed. In addition, with-wine portfolios generally either dominate individual assets or investors are indifferent in choosing between individual assets. Interestingly, the with-wine portfolios first-order stochastically dominate housing in both the long-only and short-allowed strategies, pointing towards market inefficiency. Finally, we reveal that investors prefer the low-risk with-wine portfolios to the equal-weighted portfolios but are indifferent between the high-risk with-wine portfolios and the naïve portfolios for both long-only and short-allowed strategies. Our findings can be used by investors in their investment processes, and reveal the possibility of earning abnormal returns when wine is included in the investment.

An interval-based stochastic dominance approach for decision making in forward contracts of electricity market

virtually, all decisions in financial markets are made in the presence of uncertainty. Stochastic dominance is a well-known concept that is broadly implemented for decision making under uncertainty. Thanks to the advantages of this approach, a decision maker is able to exploit available information related to uncertainties with stochastic nature. In this paper, to cope with the uncertainties in the procedure of decision making for forward contracts in an electricity market, a modified stochastic dominance approach is proposed. In the suggested framework, instead of considering a single value for desirable goal in each scenario of benchmark, a profit interval has been allocated to reflect the economic targets of decision maker. In the next step, the allocated profit interval is utilized for decision making problem in the stochastic dominance framework. In order to find the optimal profit profile in such a setting, a two level optimization structure is suggested. To this end, at the lower level of optimization, three different methods namely the prospect stochastic dominance, conditional value at risk (CvaR) and hypothesis testing are applied to find the optimal profit profiles for a number of benchmarks, those are stochastically generated in an interval around a pre-specified profit benchmark. In the upper level, the optimal profit profile is computed by using the Mean-CvaR method. To show the practical aspects and generalizability of our proposed approach, the methods are applied to two different cases, including a retailer and an electricity producer’s decision making problems to determine their involvement in the futures market by maximizing their expected profit over a given planning horizon, while controlling the risk of profit volatility in the electricity market, raised from the uncertainties in the spot market price and the consumer demand. The performance of suggested framework is evaluated through simulation results and relevant conclusions are drawn.

Dispersion in Analysts’ Earnings Forecasts and Market Efficiency

AbstractRecent studies show that firms with higher analysts’ earnings forecasts dispersion subsequently have lower returns than firms with lower forecasts dispersion. This paper evaluates alternative explanations for the dispersion–return relation using a stochastic dominance approach. We aim to discriminate between the hypothesis that some asset pricing models can explain the puzzling negative relation between dispersion and stock returns, and the alternative hypothesis that the dispersion effect is mainly driven by investor irrationality and thus is an evidence of a failure of efficient markets. We find that low dispersion stocks dominate high dispersion stocks by second‐ and third‐order stochastic dominance over the period from 1976 to 2012. Our results imply that any investor who is risk‐averse and prefers positive skewness would unambiguously prefer low dispersion stocks to high dispersion stocks. We conclude that the dispersion effect is more likely evidence of market inefficiency, rather than a result of omitted risk factors.

Moral Uncertainty for Deontologists

Defenders of deontological constraints in normative ethics face a challenge: how should an agent decide what to do when she is uncertain whether some course of action would violate a constraint? One common response to this challenge proposes a threshold principle on which it is subjectively permissible to act iff the agent’s credence that her action would be constraint-violating is below some threshold t. But the threshold approach seems arbitrary and unmotivated: where does the threshold come from, and why should it take any one value rather than another? Threshold views also seem to violate “ought” agglomeration, since a pair of actions each of which is below the threshold for acceptable moral risk can, in combination, exceed that threshold. In this paper, I argue that stochastic dominance reasoning can vindicate and lend rigor to the threshold approach: given characteristically deontological assumptions about the moral value of acts, it turns out that morally safe options will stochastically dominate morally risky alternatives when and only when the likelihood that the risky option violates a moral constraint is greater than some precisely definable threshold (in the simplest case, .5). The stochastic dominance approach also allows a principled, albeit intuitively imperfect, response to the agglomeration problem. Thus, I argue, deontologists are better equipped than many critics have supposed to address the problems of decision-making under uncertainty.

Socially Responsible Investing Portfolio: An Almost Stochastic Dominance Approach

This study investigates whether socially responsible investing (SRI) portfolio performs better than the market indexes using the utility-based nonparametric approach. The results from realized return distribution show that SRI portfolio outperforms the market indexes in term of almost stochastic dominance. The outperformance of SRI portfolio is robust to various robustness tests. Overall, our findings indicate that the SRI strategy indeed generates better performance. It is also suggested that past SRI ratings are valuable information for investors to incorporate socially responsible firms into their investment decision and yield a high return.

Efficient farming options for German apple growers under risk – a stochastic dominance approach

For a sustainable economic performance of apple production, the determination of efficient farming options considering production risk is crucial. Relying on a permanent crop, apple producers are less flexible to react upon disturbances. Based on data of 134 apple producers operating in the two main production areas in Germany, we compare and determine efficient production options. Furthermore, appropriate risk management instruments (RMIs) are identified using stochastic dominance criteria. In addition, we use Stochastic Efficiency with Respect to a Function to evaluate farming options for defined ranges of relative risk aversion. The results indicate that Red Prince is the most efficient variety in the north and subsidized hail insurance with frost irrigation is superior to frost irrigation as single RMI. In the south Braeburn should be chosen by rational decision makers, but the tested insurance solutions are not as efficient as the common practice of producing apple under hail nets.

Is Wine a Good Choice for Investment?

We extend our understanding on the role of wine investment within a portfolio of different assets (US/UK equities, bonds, gold, and housing) by considering a rich methodology based, among others, on the mean-variance and stochastic-dominance approaches. The main findings suggest that wine is the best investment among all individual assets under study, and investors prefer to invest in with-wine portfolios than without-wine portfolios to gain higher expected utility when short sale is not allowed. However, investors are indifferent between portfolios with and without wine when short-selling is allowed. In addition, with-wine portfolios generally either dominate individual assets or are indifferent from individual assets. Interestingly, the with-wine portfolios first-order stochastically dominates housing in both long-only and short-allowed strategies, pointing towards market inefficiency and thus the possibility for an expected arbitrage opportunity. Finally, we reveal that investors prefer the low-risk with-wine portfolios to the equal-weighted portfolio, but are indifferent between the high-risk with-wine portfolios and the naive portfolio for both long-only and short-allowed strategies. Our findings can be used by investors in their investment processes and reveal the possibility of earning abnormal returns when wine is included in the investment.

The State of Female Autonomy in India: A Stochastic Dominance Approach

The promotion of female autonomy is both intrinsically and instrumentally desirable. We document differences in the distribution of female autonomy in India (using the National Family Health Survey 2005–2006) addressing two methodological challenges: the multidimensional nature of the concept and its frequent measurement with ordinal variables (which are not amenable to direct comparisons of social averages). We tackle these challenges with three methods based on stochastic dominance techniques suited for ordinal and dichotomous variables. Whenever these dominance conditions hold for a pairwise comparison, we can conclude that the multidimensional autonomy distribution in one state is more desirable than in another one across a broad range of criteria for the individual and social welfare evaluation of autonomy. Consistently across the three methods, we find that most of the states with better autonomy distributions (in pairwise comparisons) come from the north east and the south, whereas most of the states with worse autonomy distributions come from the north.

Competitive balance in a quasi-double knockout tournament

ABSTRACTIn 2001, the All-Ireland Gaelic Football competition changed from being a singleknockout tournament to a quasi-double knockout competition. Similar natural experiments in economics and operational research theory suggest such a change should reduce the competitive balance in the competition. Using a Hirschmann–Herfindahl Index measure of concentration and a bootstrapping approach, we confirm that the new structure leads to a less competitive outcome and, importantly, this outcome is less uncertain. Our bootstrapped results show that in the long run, with larger samples, there is less competitive balance in the new competition structure than in the older structure competition structure. Finally, we also consider a stochastic dominance approach to evaluating the change in tournament structure, but the low power due to the presence of ties in our small sample leads to an inconclusive outcome.

Robust Inference for Inverse Stochastic Dominance

The notion of inverse stochastic dominance is gaining increasing support in risk, inequality, and welfare analysis as a relevant criterion for ranking distributions, which is alternative to the standard stochastic dominance approach. Its implementation rests on comparisons of two distributions’ quantile functions, or of their multiple partial integrals, at fixed population proportions. This article develops a novel statistical inference model for inverse stochastic dominance that is based on the influence function approach. The proposed method allows model-free evaluations that are limitedly affected by contamination in the data. Asymptotic normality of the estimators allows to derive tests for the restrictions implied by various forms of inverse stochastic dominance. Monte Carlo experiments and an application promote the qualities of the influence function estimator when compared with alternative dominance criteria.

Optimal diversification, stochastic dominance, and sampling error

PurposeThe purpose of this paper is to contribute to the literature in three ways: first, the authors investigate the impact of the sampling errors on optimal portfolio weights and on financial investment decision. Second, the authors advance a comparative analysis between various domestic and international diversification strategies to define a stochastic optimal choice. Third, the authors propose a new methodology combining the re-sampling method, stochastic optimization algorithm, and nonparametric stochastic dominance (SD) approach to analyze a stochastic optimal portfolio choice for risk-averse American investors who care about benefits of domestic diversification relative to international diversification. The authors propose a new portfolio optimization model involving SD constraints on the portfolio return rate. The authors define a portfolio with return dominating the benchmark portfolio return in the second-order stochastic dominance (SSD) and having maximum expected return. The authors combine re-sampling procedure and stochastic optimization to establish more flexibility in the investment decision rule.Design/methodology/approachThe authors apply the re-sampling procedure to consider the sampling error in the optimization process. The authors try to resolve the problem of the stochastic optimal investment strategy choice using the nonparametric SD test by Linton et al. (2005) based on sub-sampling simulated p values. The authors apply the stochastic portfolio optimization algorithm with SSD constraints to define optimal diversified portfolios beating benchmark indices.FindingsFirst, the authors find that reducing sampling error increases the dominance relationships between different portfolios, which, in turn, alters portfolio investment decisions. Though international diversification is preferred in some cases, the study’s results show that for risk-averse US investors, in general, there is no difference between the diversification strategies; this implies that there is no increase in the expected utility of international diversification for the period before and after the 2007-2008 financial crisis. Nevertheless, the authors find that stochastic diversification in domestic, global, and Europe, Australasia, and Far East markets delivers better risk returns for the US risk averters during the crisis period.Originality/valueThe originality of the idea in this paper is to introduce a new methodology combining the concept of portfolio re-sampling, stochastic portfolio optimization with SSD constraints, and the nonparametric SD test by Linton et al. (2005) based on subsampling simulated p values to analyze the impact of sampling errors on optimal portfolio returns and to investigate the problem of stochastic optimal choice between international and domestic diversification strategies. The authors try to prove more coherence in the portfolio choice with the stochastically and the uncertainty characters of the paper.