scholarly journals TWO-CRITERIA APPROACH IN GAMES WITH NATURE AND ITS APPLICATION TO STOCK INVESTMENT

2020 ◽  
pp. 158-169
Author(s):  
Виктор Александрович Горелик ◽  
Татьяна Валерьяновна Золотова
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Standard Deviation ◽  
Mathematical Programming ◽  
Mathematical Expectation ◽  
Mixed Strategy ◽  
Statistical Data ◽  
Investment Strategies ◽  
Stock Investment ◽  
Decision Making Model

Предложена модель принятия решений в задачах фондового инвестирования как игра с природой с известными вероятностями состояний. Целью исследования является разработка новых принципов принятия решений в играх с природой и их применение для анализа статистических данных и выбора стратегий фондового инвестирования. В качестве оценки эффективности принимается математическое ожидание выигрыша инвестора, а в качестве оценки риска - среднеквадратическое отклонение. Эта двухкритериальная задача формализуется путем перевода оценки риска в ограничение. Научная новизна результатов исследования заключается в получении аналитического метода решения возникающей нелинейной задачи математического программирования и алгоритма поиска оптимальной смешанной стратегии. Приведен практический пример применения предложенных методов нахождения стратегий инвестирования на базе реальных статистических данных. A decision-making model in stock investment problems is proposed as a game with nature with known state probabilities. The aim of the study is to develop new principles of decision-making in games with nature and their application for the analysis of statistical data and the choice of stock investment strategies. The mathematical expectation of the investor's payoff is taken as an assessment of efficiency, and the standard deviation as a risk assessment. This two-criteria problem is formalized by translating risk assessment into a constraint. The scientific novelty of the research results lies in obtaining the analytical method for solving an arising nonlinear problem of mathematical programming and the algorithm for finding the optimal mixed strategy. The practical example of the application of the proposed methods for finding investment strategies based on real statistical data is given.

scholarly journals THE CORRELATION DEPENDENCE OF PAYOFFS FOR MIXED STRATEGIES IN GAMES WITH NATURE

2021 ◽  
pp. 139-149
Author(s):  
Виктор Александрович Горелик ◽  
Татьяна Валерьяновна Золотова
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Standard Deviation ◽  
Analytical Solution ◽  
Statistical Data ◽  
Mixed Strategies ◽  
Correlation Dependence ◽  
Solution Methods ◽  
Pure Strategies ◽  
Decision Making Model

Цель исследования состоит в развитии и применении к задачам инвестирования методов принятия решений в играх с природой, учитывающих корреляцию случайных значений выигрышей для каждой пары чистых стратегий. При этом рассматриваются два критерия: математическое ожидание выигрыша и среднеквадратическое отклонение как оценка риска. Двухкритериальная модель принятия решений формализована путем перевода оценки риска в ограничение. Для такой обобщенной задачи квадратичного программирования получены аналитические методы решения. Приведен пример применения предложенного метода на реальных статистических данных. The aim of the research is to develop and apply to investment problems the methods of decision-making in games with nature, considering the correlation of random values of payoffs for each pair of pure strategies. In this case, two criteria are considered: the mathematical expectation of a payoff and the standard deviation as a risk assessment. The two-criteria decision-making model is formalized by translating the risk assessment into a constraint. For such a generalized quadratic programming problem, analytical solution methods are obtained. An example of applying the proposed method to real statistical data is given.

scholarly journals Using Statistical Estimates in the Game with Nature as an Investment Model

2020 ◽  
Vol 17 (6) ◽  
pp. 64-72
Author(s):  
V. A. Gorelik ◽  
T. V. Zolotova
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Initial Data ◽  
Mathematical Expectation ◽  
Statistical Data ◽  
Lagrange Function ◽  
Analysis Tool ◽  
Mixed Strategies ◽  
Probabilistic Uncertainty ◽  
Stock Investment

Purpose of the study. The aim of the research is to develop new principles of decision making (principles of optimality) in games with nature and their application to analyze statistical data and choose strategies for stock investment.Materials and methods. We analyze Russian and foreign bibliography on the research problem. A model of decision making in a game with nature with known state probabilities is proposed. The mathematical expectation of the player's payoff is taken as an assessment of efficiency, and the standard deviation or variance is taken as a risk assessment. This two-criterion task is formalized by transferring the efficiency assessment into a constraint. As a result, for the case of mixed strategies, a nonlinear (quadratic) task of mathematical programming arises. To solve it, an approach based on the Lagrange function and the Karush-Kuhn-Tucker optimality conditions is used. As an application of the methods obtained, the problems of stock investment are considered.Results. Analytical methods for solving the indicated optimization problem and an algorithm for finding optimal mixed strategies are obtained. Practical examples of application of the proposed approach on real statistical data are given. As the initial data in this study, we used stock quotes of Russian companies in the electric power industry for the period from 01.07.2020 to 01.10.2020, taken from the website of the FINAM Investment Company. The developed method allows one to find the optimal strategy and the corresponding values of profitability and risk based on only the initial data (statistical characteristics of financial instruments and the threshold value of profitability), i.e. provides, in our opinion, a convenient analysis tool for the investor.Conclusion. The concept of the principle of optimality in decision making problems under conditions of incomplete information is very ambiguous. The decision maker should be able to choose from a range of decision making models that reflect the dependence of the type of rational behavior on the available information and the attitude to risk. The paper proposes a model of this type for the case of probabilistic uncertainty, which leads to the problem of minimizing variance as a risk assessment with a lower bound on the mathematical expectation as an assessment of efficiency.

scholarly journals Hesitant Fuzzy-Sets Based Decision-Making Model for Security Risk Assessment

2022 ◽  
Vol 70 (2) ◽  
pp. 2297-2317
Author(s):  
Ahmed S. Alfakeeh ◽  
Abdulmohsen Almalawi ◽  
Fawaz Jaber Alsolami ◽  
Yoosef B. Abushark ◽  
Asif Irshad Khan ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Fuzzy Sets ◽  
Security Risk ◽  
Hesitant Fuzzy Sets ◽  
Security Risk Assessment ◽  
Decision Making Model

scholarly journals Decision-Making Model under Risk Assessment Based on Entropy

Entropy ◽  
2016 ◽  
Vol 18 (11) ◽  
pp. 404 ◽  
Author(s):  
Xin Dong ◽  
Hao Lu ◽  
Yuanpu Xia ◽  
Ziming Xiong
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Decision Making Model

Transcending the Actuarial Versus Clinical Polemic in Assessing Risk for Violence

2002 ◽  
Vol 29 (5) ◽  
pp. 659-665 ◽  
Author(s):  
Christopher D. Webster ◽  
Stephen J. Hucker ◽  
Hy Bloom
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Prediction ◽  
Statistical Data ◽  
Legal Framework ◽  
Violence Risk ◽  
Scientific Methods ◽  
Assessment Score ◽  
Dynamic Variables

Much energy has been expended over recent years in debating the relative merits of actuarial versus clinical approaches to violence risk prediction. Although it has gradually become apparent that scores based on more or less static factors obtainable from the record do indeed associate with outcome violence over years of follow-up, there is no reason to suppose that, at least potentially, dynamic variables do not hold as much or more promise when it comes to projections over weeks or months. Clinicians involved in release decision-making might wish to consider the following, in order of importance: (a) the legal framework within which the decision is being made, (b) the thoroughness with which scientific methods have been applied to the particular case at issue, (c) the precision of the individualized statement of violence risk being offered, (d) the steps which could be taken to reduce that risk, and (e) if available, the individual's violence risk assessment score in relation to already amassed pertinent statistical data.

scholarly journals On the Diversity-Based Weighting Method for Risk Assessment and Decision-Making about Natural Hazards

Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 269 ◽  
Author(s):  
Pengyu Chen
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Natural Hazards ◽  
Strong Correlation ◽  
Statistical Data ◽  
Weighting Method ◽  
The Difference ◽  
Range Of Values ◽  
Weighting Methods ◽  
Coefficient Method

The entropy-weighting method (EWM) and variation coefficient method (VCM) are two typical diversity-based weighting methods, which are widely used in risk assessment and decision-making for natural hazards. However, for the attributes with a specific range of values (RV), the weights calculated by EWM and VCM (abbreviated as WE and WV) may be irrational. To solve this problem, a new indicator representing the dipartite degree is proposed, which is called the coefficient of dipartite degree (CDD), and the corresponding weighting method is called the dipartite coefficient method (DCM). Firstly, based on a large amount of statistical data, a comparison between the EWM and VCM is carried out. It is found that there is a strong correlation between the weights calculated by the EWM and VCM (abbreviated as WE and WV); however, in some cases the difference between WE and WV is big. Especially when the diversity of attributes is high, WE may be much larger than WV. Then, a comparison of the DCM, EWM and VCM is carried out based on two case studies. The results indicate that DCM is preferred for determining the weights of the attributes with a specific RV, and if the values of attributes are large enough, the EWM and VCM are both available. The EWM is more suitable for distinguishing the alternatives, but prudence is required when the diversity of an attribute is high. Finally, the applications of the diversity-based weighting method in natural hazards are discussed.

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