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With suitable optimization criteria, hybrid models have proven to be efficient for preparing portfolios in capital markets of developed countries. This study adapts and investigates these methods for a developing country, thus providing a novel approach to the application of banking and finance. Our specific objectives are to employ a stochastic dominance criterion to evaluate the performances of over-the-counter (OTC) companies in a developing country and to analyze them with a hybrid model involving particle swarm optimization and artificial neural networks.

In order to achieve these aims, the authors conduct a case study of OTC companies in Iran. Weekly and daily returns of 36 companies listed in this market are calculated for one year during 2014–2015. The hybrid model is particularly interesting, and the results of the study identify first-, second- and third-order stochastic dominances among these companies. The study’s chosen model uses the best performing combination of activation functions in our analysis, corresponding to TPT, where T represents hyperbolic tangent transfers and P represents linear transfers.

Our portfolios are based on the shares of companies ranked with respect to the stochastic dominance criterion. Considering the minimum and maximum numbers of shares to be 2 and 10 for each portfolio, an eight-share portfolio is determined to be optimal. Compared with the index of Iran OTC during the research period of this study, our selected portfolio achieves a significantly better performance. Moreover, the methods used in this analysis are shown to be as efficient as they were in the capital markets of developed countries.

The problem of optimizing investment portfolios has to allow for correlations among returns from the financial maintenance period under consideration if an asymmetric distribution of returns exists (Babaei et al., 2015). Therefore, it is desirable to select an appropriate criterion in order to prepare an optimal portfolio and prioritize investment options. Although a back propagation technique is very popular in artificial neural (ANN) training, it is time-consuming to train a network in this way, and other methods such as particle swarm optimization (PSO) should be considered instead. In the hybrid combination of PSO and ANN, it is not the structure of a neural network that changes. Rather, the weighting method and the training technique chosen for the network are the important aspects, and these relate to PSO, so the only role ANN plays in this process is to reduce the errors.

The hybrid model combining ANN and PSO is seen to be considerably successful for generating optimal results and appropriate activation functions. These results are consistent with the theoretical findings of Das et al. (2013) and an application of the simple PSO in a study conducted by Pederson and Chipperfield (2010). Our research results also confirm the efficiency of stochastic dominance criteria as noted in the studies conducted by Roman et al. (2013), ANN as in a study carried out by Kristijanpoller et al. (2014) and PSO as in studies conducted by Liu et al. (2015) and Deng et al. (2012). These studies were carried out in the capital markets of developed countries, whereas the authors’ analysis relates to a developing country.

The authors deduce that the tools and methods whose efficiency was proven in the capital markets of developed countries also apply to, and demonstrate efficiency in, two novel applications of portfolio optimization within developing countries. The first of these is gaining familiarity with the theory and practice of these research tools and the methods that enrich financial knowledge of investors in developing countries. The second of these is the application of tools and methods identified by investors in the capital markets of developing countries, which enables optimal allocation of financial resources and growth of the markets. The authors expect that these findings will contribute to improving the economies of developing countries and thus help with economic development and facilitation of improving trends.

Anchoring vignettes have become a popular method to adjust self-assessed data for systematic differences in reporting behaviour to aid comparability, for example, of cross-country analyses. The method relies on the two fundamental assumptions of response consistency and vignette equivalence. Evidence on the validity of these assumptions is equivocal. This chapter considers the utility of the vignette approach by considering how successful the method is in moving self-assessed reports of health mobility towards objective counterparts. We draw on data from the Survey of Health, Ageing and Retirement in Europe (SHARE) and undertake pairwise country comparisons of cumulative distributions of self-reports, their objective counterparts and vignette adjusted reports. Comparison of distributions is based on tests for stochastic dominance. Multiple cross-country comparisons are undertaken to assess the consistency of results across contexts and settings. Both non-parametric and parametric approaches to vignette adjustment are considered. In general, we find the anchoring vignette methodology poorly reconciles self-reported data with objective counterparts.

The purpose of this paper is to use a stochastic dominance test to examine the relative performance of value vs growth stocks based on multiple value-growth proxies in the Taiwan stock market.

This work examines whether the return distribution of a value portfolio stochastically dominates that of a growth portfolio using a test proposed by Linton et al. (2005).

By applying stochastic dominance analysis on the full-sample period, the sub-sample period and the state of the world’s economic conditions, the authors find that the earnings-to-price or dividend-to-price ratio is better than the book-to-market ratio as a value-growth proxy in Taiwan. There are robust results even after adjusting for data frequency, a sampling method and sample excluding financial services.

This study makes the first attempt to examine value vs growth strategies based on multiple value-growth proxies in the emerging market of Taiwan by administering the stochastic dominance test.

Choice under risk has a large stochastic (unpredictable) component. This chapter examines five stochastic models for binary discrete choice under risk and how they combine with “structural” theories of choice under risk. Stochastic models are substantive theoretical hypotheses that are frequently testable in and of themselves, and also identifying restrictions for hypothesis tests, estimation and prediction. Econometric comparisons suggest that for the purpose of prediction (as opposed to explanation), choices of stochastic models may be far more consequential than choices of structures such as expected utility or rank-dependent utility.

We examine the cardinal gap between wage distributions of the incumbents and newly hired workers based on entropic distances which are well-defined welfare theoretic measures. Decomposition of several effects is achieved by identifying several counterfactual distributions of different groups. These go beyond the usual Oaxaca–Blinder decompositions at the (linear) conditional means. Much like quantiles, these entropic distances are well-defined inferential objects and functions whose statistical properties have recently been developed. Going beyond these strong rankings and distances, we consider weak uniform ranking of these wage outcomes based on statistical tests for stochastic dominance. The empirical analysis is focused on employees with at least 35 hours of work in the 1996–2012 monthly Current Population Survey (CPS). Among others, we find incumbent workers enjoy a better distribution of wages, but the attribution of the gap to wage inequality and human capital characteristics varies between quantiles. For instance, highly paid new workers are mainly due to human capital components, and in some years, even better wage structure.

Hypothesis tests for dominance in income distributions has received considerable attention in recent literature. See, for example, Barrett and Donald (2003a, b), Davidson and Duclos (2000) and references therein. Such tests are useful for assessing progress towards eliminating poverty and for evaluating the effectiveness of various policy initiatives directed towards welfare improvement. To date the focus in the literature has been on sampling theory tests. Such tests can be set up in various ways, with dominance as the null or alternative hypothesis, and with dominance in either direction (X dominates Y or Y dominates X). The result of a test is expressed as rejection of, or failure to reject, a null hypothesis. In this paper, we develop and apply Bayesian methods of inference to problems of Lorenz and stochastic dominance. The result from a comparison of two income distributions is reported in terms of the posterior probabilities for each of the three possible outcomes: (a) X dominates Y, (b) Y dominates X, and (c) neither X nor Y is dominant. Reporting results about uncertain outcomes in terms of probabilities has the advantage of being more informative than a simple reject/do-not-reject outcome. Whether a probability is sufficiently high or low for a policy maker to take a particular action is then a decision for that policy maker.

The methodology is applied to data for Canada from the Family Expenditure Survey for the years 1978 and 1986. We assess the likelihood of dominance from one time period to the next. Two alternative assumptions are made about the income distributions – Dagum and Singh-Maddala – and in each case the posterior probability of dominance is given by the proportion of times a relevant parameter inequality is satisfied by the posterior observations generated by Markov chain Monte Carlo.

Dominance techniques are used to analyze and rank inequality, welfare, and poverty across regions in Thailand in the 1990s. Inference-based dominance methods are applied to consumption expenditure microdata from the Household Socio-Economic Surveys (SES) of 1992, 1994, 1996, 1998 and 2000. Attention is focused on the period immediately before and after the economic contraction of 1996–1997. Lorenz dominance is employed to assess inequality, while first-order Engel food share dominance is applied to rank welfare across time and among regions. Poverty is evaluated by comparing truncated food-share quantile functions. The evidence reveals that the economic crisis in 1997 seems to affect inequality in Bangkok (the richest region) more than the Northeast (the poorest region), and most dramatic changes occur in the North and South. Welfare in Bangkok is unambiguously higher than in other regions before and after economic contraction. In fact, the great economic contraction changes the rankings of economic well-being and poverty only in the North, South, and Northeast.

This chapter examines self-assessed health (SAH) data of 29 European countries using Eurostat data for the years 2009 and 2018. It first computes the indices recently introduced by Seth and Yalonetzky (2020) and provides confidence intervals for these indices. The ranking of these countries for the year 2018 is then summarized by Hasse diagrams. The chapter then examines first- and second-order stochastic dominance, based again on the recent work of Seth and Yalonetzky. Here also bootstrap confidence intervals were computed. The ranking of the countries in 2018 is then translated again into Hasse diagrams. It appears that Hungary and Latvia are respectively the poorest and least poor countries, both in 2009 and 2018, in terms of their SAH condition. While countries like Ireland, Luxembourg, Romania and Portugal are in the poorer segment of the distribution of countries, Norway, the United Kingdom, Denmark, the Netherlands and Austria are located on the less poor portion. As expected, the Hasse diagrams show also that there are quite a few instances where some countries cannot be ranked.

Purpose: This paper aims at studying the degree of equality of educational opportunity in the Italian university system.

Methodology: We build on the approaches developed by Peragine (2004, 2005) and Lefranc et al. (2006a, 2006b) and focus on the equality of educational opportunities for individuals of different social background. We propose different definitions of equality of opportunity in education. Then, we provide testable conditions with the aim of (i) testing for the existence of equality of opportunity (EOp) in a given distribution and (ii) ranking distributions on the basis of EOp. Definitions and conditions resort to standard stochastic conditions that are tested by using nonparametric tests developed by Beach and Davidson (1983) and Davidson and Duclos (2000).

Findings: Our empirical results show a strong family effect on the performances of students in the higher education and on the transition of graduates in the labor market. Moreover the inequality of opportunity turns out to be more severe in the South than in the regions of the North-Center.

Originality: This work contributes to the literature in three ways: first, it proposes a definition of equality of educational opportunities. Second, the paper develops a methodology in order to test for the existence of equality of opportunity in a given distribution and to rank distributions according to equality of opportunity. Third, we present empirical evidence on the degree of equality of educational opportunity in the Italian university system.