Stochastic Dominance Method Research Articles

PENGUKURAN RISIKO PORTOFOLIO SAHAM JAKARTA ISLAMIC INDEX DENGAN STOCHASTIC DOMINANCE

Stocks is one of the assets which has a high level of liquidity. Optimizing stock investment can be done by diversifying the portfolio. Stochastic Dominance is a portfolio formation method that looks at the amount of dominance of each stock pair. This study’s purpose is to apply the Stochastic Dominance method to create an optimal portfolio on sharia index called JII from April 2018 to March 2022. This study indicate that out of the 5 selected stocks, there are 4 stocks that dominate each stock pair, including ADRO, ICBP, PTBA, UNTR. ADRO proportion are 57,14% while ADRO, PTBA, and UNTR’s proportion are each 14,28%. The level of risk on this research is measured by a VaR with historical simulation method. Using this method, the maximum potential loss of the formed portfolio for the next month is 8.5% at a 95% confidence level.

Risk-involved dominant optimization of multi-energy CCHP-P2G-based microgrids integrated with a variety of storage technologies

Environmental problems arising from fossil-based generation units in a microgrid (MG) are a pressing concern due to their contribution to air pollution and greenhouse gas emissions. This paper investigates an integrated MG with combined cooling, heating, and power (CCHP) systems, designed to efficiently supply energy demands while considering the environmental impacts of generation units associated with CO2 emissions. To mitigate these environmental impacts and promote sustainability, the proposed CCHP-based MG incorporates a power-to-gas (P2G) technology, aimed at CO2 absorbing and recycling. This integration not only optimizes system performance but enhances the environmental aspects of the microgrid. Moreover, the uncertainties related to energy demands, wholesale prices, and renewable generation poses potential challenges for the system operation. In response, the second-order stochastic dominance (SOSD) method is employed to address these uncertainties and ensure robust decision-making. Results show that the P2G system enables a 15 % reduction in carbon emissions, highlighting the eco-friendly nature of the system. However, its incorporation introduces an additional 6 % to the overall system operation cost due to its relatively high cost. In addition, it is important to note that the operator has further conservativeness in the With-SOSD operation mode leading to an approximate 30 % increase in the operation costs compared to the NO-SOSD mode.

Double-Exponential-X Family of Distributions: Properties and Applications

A new family of distribution named Double-Exponential-X family is proposed. The proposed family is generated from the double exponential distribution. The forms of the probability densities and hazard functions of two distinct subfamilies of the proposed family are examined and reported. Generalproperties such as moment, survival, order statistics, probability weighted moments and quartile functions of the models are investigated. A sub family of the developed family of double –Exponential-X family of the distribution known as double-Exponential-Pareto distribution was used to fit a real life data on the use of antiretroviral drugs. Molecular simulation of efficacy of antiretroviral drugs is conducted to evaluate the performance of the model. The models were tested using some models diagnostic tests and it was revealed that the proposed model was better than the ones proposed before it from the same family and also, stochastic dominance method was used to affirm the best antiretroviral drugs used in the study.

Market efficiency of Asian stock markets during the financial crisis and non-financial crisis periods

We examine the semi-strong form market efficiency level for the 12 major Asian markets with the stochastic dominance (SD) method during the financial crisis and non-financial crisis periods. Five famous value premium (VP) indicators, including book-to-market, cash flow-to-price, earnings-to-price, dividend-to-price, and sales-to-price ratios, are employed to examine the market efficiency during the two examination periods, respectively. The results of the SD test for performance between value (V) and growth (G) portfolios can be categorized into three sets: V=G (efficiency), V≻G (inefficiency, VP), and V≺G (inefficiency, reversal VP). Our main results show that the market efficiency or inefficiency level is not significantly different between the financial crisis and non-financial crisis periods. However, the evidence of further exploration of market inefficiency level shows that the different anomaly returns pattern exists in the two examination periods.

Risk assessment of integrated concentrated solar system and biomass using stochastic dominance method

Generally, due to the greenhouse gas emission level getting bigger and bigger every year, there is an essential need to use renewable energy resources and other environmentally friendly methods for electricity generation in the power industry. In this regard, the concentrated solar system integrated with biomass boiler and thermal storage could be applied to generate dispatchable power and raise the principles of renewable-based networks. In this paper, for an integrated biomass-concentrated solar (IBCS) system, a day-ahead and intra-day dispatch procedure are provided with the aim of maximizing the obtained profit of the system by manipulating the association of the system components in a cooperative manner. In addition, some uncertainties impose financial threats in the system performance and are needed to be assessed. In this regard, by using a stochastic optimization approach called the stochastic dominance (SD) method, the assessment of the IBCS system is performed. In the mentioned approach, the function of the system components is recorded under two strategies called risk-averse and risk-neutral. According to the obtained results, the represented procedure for day-ahead and intra-day dispatch is a profitable method for the system operator. For example, $2800 of profit is acquired for the decision-maker in the risk-neutral model and $2500 in the risk-averse model, which indicates that the decision-maker needs to devote 9% more of his currency in order to keep the safety of the system in an acceptable level.

A New Life of Pearson’s Skewness

In this work, we show how coupling and stochastic dominance methods can be successfully applied to a classical problem of rigorizing Pearson’s skewness. Here, we use Fréchet means to define generalized notions of positive and negative skewness that we call truly positive and truly negative. Then, we apply a stochastic dominance approach in establishing criteria for determining whether a continuous random variable is truly positively skewed. Intuitively, this means that the scaled right tail of the probability density function exhibits strict stochastic dominance over the equivalently scaled left tail. Finally, we use the stochastic dominance criteria and establish some basic examples of true positive skewness, thus demonstrating how the approach works in general.

Four-Objective Optimal Scheduling of Energy Hub Using a Novel Energy Storage, Considering Reliability and Risk Indices

Energy hub as a novel model which has provided more efficiency, flexibility, and reliability. Also, due to using different multi carriers as renewable and non-renewable sources and storage devices in energy hubs, optimal operation scheduling becomes more challenging. In this paper, the day-ahead scheduling of energy hub is studied in the presence of wind turbine, electrical, thermal, and a novel water-based storage called Pico hydel energy storage. A useful method using the Monte-Carlo and k-mines clustering method is developed to estimate the uncertainty associated with wind speed, load, and market price. On the other hand, Conditional Value at Risk and Second-Order Stochastic Dominance (SSD) method are applied as a risk-averse method. To find the best operation performance of energy hub, multiple objectives consist of economic, emission pollution, electrical, and load profile deviation are defined. As well, the demand response program for gas, electricity, water, and thermal are implemented to improve the energy hub performance. Mixed-integer non-linear program formulation for the day-ahead scheduling of energy hub has been solved by executing CPLEX solver of GAMS optimization software in five different cases. Simulation results show that the hub's operation cost and emission reduce up to 4.8% and 5.6% by implementing four objective functions in the presence of the Pico hydel energy storage and demand response programing.

Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China

This paper aims to compare Bitcoin with gold in the diversification of Chinese portfolios using daily data over the 2010–2020 period. We propose a new development of copula-based joint distribution function of returns to simulate the Value-at-Risk and expected shortfall of portfolios including Bitcoin (or gold) and those without it. The stochastic dominance method is also used to compare the return distributions of the three types of portfolios. Empirical results show that gold is a better portfolio diversifier than Bitcoin as it helps better reduce the risk of portfolios. On the other hand, Bitcoin better increases the return but also increases the risk. The stochastic dominance results further show that portfolios diversified by gold dominate those diversified by Bitcoin. Based on these findings, we conclude that in China, gold is a better portfolio diversifier than Bitcoin for risk-averse investors. However, for risk-seeking investors, Bitcoin can be a better choice. This result is found to be robust to the time, frequency and currency effects.

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 approaches fail to explain this Eastern Halloween effect satisfactorily. We apply stochastic dominance method to examine the Eastern Halloween effect and provide solid evidence of existence of Eastern Halloween effect.

Improving stochastic analysis for tradeoffs in multi‐criteria value models

AbstractIn multi‐criteria value modelling (MCVM), uncertainty clouds decision making by complicating choices that inevitably must be made among an offering of competing alternatives. In stochastic MCVM settings involving value versus cost (risk) tradeoffs, exposing and communicating ramifications that choice instigates becomes increasingly difficult directly in response to the increased sophistication of mathematical methods needed to distinguish between alternatives, leaving the decision maker potentially unprepared for eventual opportunity or disaster. This article introduces an approach called realization analysis that leverages stochastic simulation, probability theory and tradespace geometry to estimate full spectrum outcome probabilities in an effort to enrich decision making and reduce the potential for surprise or regret, demonstrating its effectiveness when competing alternatives are tightly co‐mingled in their potential realizations causing issues for traditional stochastic dominance methods. The approach is surprisingly straightforward to implement, with results easily communicated to technical and non‐technical decision makers. A brief acquisition case study involving competing alternatives is presented to illustrate how this approach offers advantages for multi‐criteria decision analysis practice.

Studi Komparatif Pembentukan Portofolio Optimal Dengan Stochastic Dominance dan Single Index Model

Purpose- The study aims to see whether there is a difference between the stochastic dominance method and the single index method in forming an optimal portfolio. and seeing which method is more optimal.
 Methods- The sample used in the study was a real estate and property company listed on jakarta stock exchange for five years period (2013 - 2017). sampling technique in research using purposive sampling and analysis sampling techniques using average difference test (t-test). after being tested with each method both the stochastic model and the single index model,
 Finding- The results show that there is a difference in return from the formation of an optimal portfolio with the results of the test which results in 0.048 below the significant level of 0.05. and the results of the calculation of portfolio return formed by the stochastic method is 0.0079 smaller than the portfolio return formed by the single index method of 0.0173 which means that the single index method is more optimal than the stochastic model.

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.

Analisis Pembentukan Portofolio Optimal dengan Metode Stochastic Dominance dan Single Index Model Pada Saham Industri Real Estate and Property diBursa Efek Indonesia

This study aims to see whether there is a difference between the stochastic dominance method and the single index method in forming an optimal portfolio. And see which method is more optimal. The sample used in the study was a real estate and property company listed on the IDX period (2013 -2017) using purposive sampling and analysis sampling techniques using the average difference test. After being tested with each method both modelstochastic and single index model, the results showed that there were differences in returns from the formation of an optimal portfolio with the test results which obtained the results of 0.048 under a significant level of 0.05. And the results of the portfolio return calculation formed by the stochastic method smaller 0.0079 than the portfolio return formed by the single index method of 0.0173 which means that the single index method is more optimal than the stochastic method.

Stochastic Dominance Analysis for the Poverty in Tabalong Regency 2013 and 2017

Although its issue could be addressed from of various perspectives over the years, poverty is the object of the government’s policy programs to be alleviated since the Indonesian independence. With the advancement of technology and science in the recent decades, the availability and the completeness of poverty data in Indonesia getting better. In fact, the policy-makers can assess the effectivity of their public-oriented programs easier by effectively utilizing the complete and up-to-date poverty data. However, in various approaches to poverty measurement, the Indonesian poverty data should be accompanied by another approach. This paper aims to evaluate the change of welfare of particular region over a period of several years by using the stochastic dominance method. This method also incorporates the price level impact into its poverty assessment through the extrapolated CPIs. To conduct the measurement, the National Socioeconomic Survey of Tabalong regency data, as well as the Tanjung city’s inflation in the period from 2013 to 2017, are employed. The results indicate that the welfare in 2017 is better than in 2013 since the distribution in 2017 stochastically dominates the distribution in 2013 at the first and second order at any possible level of poverty lines. Therefore, this result could also be the additional input for the poverty alleviation’s evaluation in order to provide a solid conclusion about the welfare changes.

Dynamics of Multidimensional Poverty and Uni-dimensional Income Poverty: An Evidence of Stability Analysis from China

In this paper, we construct an illustrative multidimensional poverty index for China and compare it with income poverty using the panel data from multiple waves of the China Health and Nutrition Survey. We use first order stochastic dominance method and regression analysis to test the stability of multidimensional poverty measures and probe the often-observed mis-match between multidimensional measures and income measures. We find as expected that China’s multidimensional poverty is significantly higher in rural areas and in the less developed western provinces. But relative to the income poverty, the multidimensional poverty is less volatile. Also, the ranking of provinces by income and multidimensional poverty varies. The multidimensional poverty measures are somewhat sensitive to the large change of weight, but if we control the indicators’ weight, then the multidimensional poverty measures are stable to a change of indicators.

Dynamics of Multidimensional Poverty and Uni‐dimensional Income Poverty: An Evidence of Stability Analysis from China

In this paper, we construct an illustrative multidimensional poverty index for China and compare it with income poverty using the panel data from multiple waves of the China Health and Nutrition Survey. We use first order stochastic dominance method and regression analysis to test the stability of multidimensional poverty measures and probe the often-observed mis-match between multidimensional measures and income measures. We find as expected that China’s multidimensional poverty is significantly higher in rural areas and in the less developed western provinces. But relative to the income poverty, the multidimensional poverty is less volatile. Also, the ranking of provinces by income and multidimensional poverty varies. The multidimensional poverty measures are somewhat sensitive to the large change of weight, but if we control the indicators’ weight, then the multidimensional poverty measures are stable to a change of indicators.

Portfolio analysis with second order stochastic dominance by the perspective of capital structure: an implementation on BIST-100 index

Purpose- The aim of this paper is to observe whether generating a portfolio having return more than index by investigating the return performance of index’s stocks and capital structure of firms in index in a certain period. The second aim of this paper is to provide portfolio diversification by using the method of this study. In this paper, firms and stocks on BIST-100 index are referenced for empirical study. Method- Stocks are chosen from BIST-100 index with regard to certain capital structure of firms in stocks, and second orderly stochastic dominance test is implemented on these stocks. Dominant stocks are defined to generate a portfolio after stochastic test and this portfolio’s return performance is compared to the index’-s return. Findings- The portfolio, whose stocks are filtered by a certain capital structure and then chosen by second orderly stochastic dominance test, has return performance better than index’s return. Conclusion- This paper is indicating that second orderly stochastic dominance method and capital structure is an important investigation to generate a portfolio having higher returns more than index’s.

Regret theory: State dominance and expected utility

Choices made according to regret theory (RT) may violate the expected utility (EU) model. We propose a stochastic dominance (SD) method for comparing RT and EU paradigms holistically, without focusing on a specific axiom or on a specific numerical example. We show that in some important cases, including the two-state case, e.g., war or peace, Republican or Democratic Party winning the Presidential election etc., RT does not violate both EU and Cumulative Prospect Theory (CPT). Obviously, when EU is not violated by RT the economic results derived under EU are intact also under RT.

Is Gold Different for Islamic and Conventional Portfolios? A Sectorial Analysis

This article investigates the impact of gold in portfolios in distinguishing between Islamic and conventional stocks as well as between risk-averse and risk-seeking investors, while considering sectorial specificities. Using daily data from the Dow Jones indexes and the London gold market over the 2002-2014 period, the results obtained show that the stochastic dominance method is more robust than the mean-risk method to detect the difference between Islamic and conventional portfolios. For most sectors, risk-averters prefer conventional portfolios, while risk-seekers prefer Islamic portfolios. On the other hand, risk-averters prefer portfolios with gold, while risk-seekers prefer portfolios without gold. A robustness check on different sub-periods shows that these results are time-varying following the behavior of gold prices. These findings can provide useful information to investors respecting Sharia and looking for a diversification with commodities such as gold.

Uncertain multi-attributes decision making method based on interval number with probability distribution weighted operators and stochastic dominance degree

In real world decision making problems, real numbers, random numbers, and interval numbers are often used simultaneously to express the attribute values of alternatives. To solve these uncertain multi-attribute decision making problems, we propose a definition of interval number with probability distribution (INPD). This definition gives a uniform form for real numbers, interval numbers, and random numbers. Under certain conditions, an INPD can degrade to one of the three number forms. We then propose three weighted operators that aggregate opinions expressed by INPD. Furthermore, we propose a new stochastic dominance degree (SDD) definition based on the idea of almost stochastic dominance to rank two INPD. The new definition overcomes defects in traditional stochastic dominance methods. It takes all stakeholders’ preferences into account and can measure both standard and almost SDDs. For real numbers and interval numbers, results derived from SDD are consistent with traditional methods. On this basis, a method using INPD weighted operators and SDD is proposed to solve uncertain multi-attribute decision making problems. Finally, three numerical examples are given to illustrate the applicability and effectiveness of the proposed method.