A Nash Bargaining Solution for a Multi Period Competitive Portfolio Optimization Problem: Co-Evolutionary Approach

2021 ◽  
pp. 115509
Author(s):  
Behnaz Pourvalikhan Nokhandan ◽  
Kaveh Khalili-Damghan ◽  
Ashkan Hafezalkotob ◽  
Hosein Didehkhani
Keyword(s):  
Portfolio Optimization ◽  
Optimization Problem ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Evolutionary Approach ◽  
Bargaining Solution ◽  
Portfolio Optimization Problem

BARGAINING POWER IN THE NASH DEMAND GAME AN EVOLUTIONARY APPROACH

2009 ◽  
Vol 11 (01) ◽  
pp. 87-97 ◽  
Author(s):  
JUANA SANTAMARIA-GARCIA
Keyword(s):  
Stochastic Stability ◽  
Bargaining Power ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Evolutionary Approach ◽  
Bargaining Solution ◽  
Nash Demand Game ◽  
Population Sizes ◽  
A Share

A population of buyers and a population of sellers meet repeatedly in order to exchange a good. The price is fixed through a variant of the Nash demand game. This paper analyzes the prices that are robust to experimentation in the sense of stochastic stability. Under some conditions only one price is selected and it gives a share of the surplus to each side of the market that corresponds to the generalized Nash bargaining solution. The bargaining power of each party depends on the division of the unclaimed surplus and the population sizes. The bargaining power of a given population will increase either with a reduction in its fraction of the unclaimed surplus or with a decrease in its own size.

scholarly journals Modeling and Optimizing the Multi-Objective Portfolio Optimization Problem with Trapezoidal Fuzzy Parameters

2021 ◽  
Vol 26 (2) ◽  
pp. 36
Author(s):  
Alejandro Estrada-Padilla ◽  
Daniela Lopez-Garcia ◽  
Claudia Gómez-Santillán ◽  
Héctor Joaquín Fraire-Huacuja ◽  
Laura Cruz-Reyes ◽  
...  
Keyword(s):  
Steady State ◽  
Portfolio Optimization ◽  
Optimization Problem ◽  
Solution Process ◽  
Density Estimator ◽  
Nsga Ii ◽  
Spatial Spread ◽  
Multi Objective ◽  
Significant Difference ◽  
Portfolio Optimization Problem

A common issue in the Multi-Objective Portfolio Optimization Problem (MOPOP) is the presence of uncertainty that affects individual decisions, e.g., variations on resources or benefits of projects. Fuzzy numbers are successful in dealing with imprecise numerical quantities, and they found numerous applications in optimization. However, so far, they have not been used to tackle uncertainty in MOPOP. Hence, this work proposes to tackle MOPOP’s uncertainty with a new optimization model based on fuzzy trapezoidal parameters. Additionally, it proposes three novel steady-state algorithms as the model’s solution process. One approach integrates the Fuzzy Adaptive Multi-objective Evolutionary (FAME) methodology; the other two apply the Non-Dominated Genetic Algorithm (NSGA-II) methodology. One steady-state algorithm uses the Spatial Spread Deviation as a density estimator to improve the Pareto fronts’ distribution. This research work’s final contribution is developing a new defuzzification mapping that allows measuring algorithms’ performance using widely known metrics. The results show a significant difference in performance favoring the proposed steady-state algorithm based on the FAME methodology.

The (Stabilized) Nash Bargaining Solution as a Principle of Distributive Justice

Utilitas ◽  
2010 ◽  
Vol 22 (4) ◽  
pp. 447-473 ◽  
Author(s):  
MICHAEL MOEHLER
Keyword(s):  
Distributive Justice ◽  
Moral Reasoning ◽  
Bargaining Power ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Original Position ◽  
Bargaining Solution ◽  
Moral Intuitions ◽  
Instrumental Reasoning ◽  
Relative Bargaining Power

It is argued that the Nash bargaining solution cannot serve as a principle of distributive justice because (i) it cannot secure stable cooperation in repeated interactions and (ii) it cannot capture our moral intuitions concerning distributive questions. In this article, I propose a solution to the first problem by amending the Nash bargaining solution so that it can maintain stable cooperation among rational bargainers. I call the resulting principle the stabilized Nash bargaining solution. The principle defends justice in the form ‘each according to her basic needs and above this level according to her relative bargaining power’. In response to the second problem, I argue that the stabilized Nash bargaining solution can serve as a principle of distributive justice in certain situations where moral reasoning is reduced to instrumental reasoning. In particular, I argue that rational individuals would choose the stabilized Nash bargaining solution in Rawls’ original position.

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