scholarly journals Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Function (Erratum)

2007 ◽  
Vol 2007 ◽  
pp. 1-1
Author(s):  
Sukanto Bhattacharya ◽  
Kuldeep Kumar
Keyword(s):  
Utility Function ◽  
Expected Utility ◽  
Biological Basis ◽  
Black Scholes ◽  
Computational Exploration

scholarly journals Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Function

2007 ◽  
Vol 2007 ◽  
pp. 1-15 ◽  
Author(s):  
Sukanto Bhattacharya ◽  
Kuldeep Kumar
Keyword(s):  
Genetic Algorithm ◽  
Utility Function ◽  
Expected Utility ◽  
Functional Form ◽  
Biological Basis ◽  
Black Scholes ◽  
Computational Exploration ◽  
Evolutionary Optimality ◽  
Successive Generations ◽  
Genetic Algorithm Model

It has often been argued that there exists an underlying biological basis of utility functions. Taking this line of argument a step further in this paper, we have aimed to computationally demonstrate the biological basis of the Black-Scholes functional form as applied to classical option pricing and hedging theory. The evolutionary optimality of the classical Black-Scholes function has been computationally established by means of a haploid genetic algorithm model. The objective was to minimize the dynamic hedging error for a portfolio of assets that is built to replicate the payoff from a European multi-asset option. The functional form that is seen to evolve over successive generations which best attains this optimization objective is the classical Black-Scholes function extended to a multiasset scenario.Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Function

A Bayesian method to estimate the optimal threshold of a marker used to select patients' treatment

2019 ◽  
Vol 29 (1) ◽  
pp. 29-43
Author(s):  
Yoann Blangero ◽  
Muriel Rabilloud ◽  
René Ecochard ◽  
Fabien Subtil
Keyword(s):  
Utility Function ◽  
Expected Utility ◽  
Treatment Options ◽  
Growth Factor Receptor ◽  
Credible Interval ◽  
Optimal Threshold ◽  
Selection Marker ◽  
Large Sample Size ◽  
Marker Distribution ◽  
Definition Of

The use of a quantitative treatment selection marker to choose between two treatment options requires the estimate of an optimal threshold above which one of these two treatments is preferred. Herein, the optimal threshold expression is based on the definition of a utility function which aims to quantify the expected utility of the population (e.g. life expectancy, quality of life) by taking into account both efficacy (success or failure) and toxicity of each treatment option. Therefore, the optimal threshold is the marker value that maximizes the expected utility of the population. A method modelling the marker distribution in patient subgroups defined by the received treatment and the outcome is proposed to calculate the parameters of the utility function so as to estimate the optimal threshold and its 95% credible interval using the Bayesian inference. The simulation study found that the method had low bias and coverage probability close to 95% in multiple settings, but also the need of large sample size to estimate the optimal threshold in some settings. The method is then applied to the PETACC-8 trial that compares the efficacy of chemotherapy with a combined chemotherapy + anti-epidermal growth factor receptor in stage III colorectal cancer.

Command Decisions

2010 ◽  
Vol 34 (4) ◽  
pp. 499-522
Author(s):  
Scott Martin
Keyword(s):  
Decision Making ◽  
Utility Function ◽  
Indigenous Peoples ◽  
Expected Utility ◽  
Interdisciplinary Approach ◽  
Socioeconomic Class ◽  
The Relationship ◽  
Insight Into ◽  
Conquest Of Mexico

The interaction of Spanish and indigenous peoples during the conquest of Mexico yielded a wide variety of actions and decisions. Native groups sometimes battled the Spanish but in other instances cooperated. The Spaniards often attacked when facing overwhelming odds but in other situations retreated with meager gains. Insight into those decisions and actions is gained by looking at human wants and preferences. The Friedman-Savage utility function is applied to specific important events of the conquest of Mexico to clarify the decision making of the participants. An interdisciplinary approach is employed in constructing the expected utility of wealth model, where the maximization of the expected utility of wealth and movement between socioeconomic classes is critically analyzed. Evidence from the Juan de Grijalva expedition, interactions with coastal villages, Hernán Cortés's approach to Tenochtitlan, and the Tlaxcalan decision to ally with the Spaniards are used to clearly illustrate the relationship between the utility of wealth and decision making. Looking through the lens of the Friedman-Savage utility function at events up to Cortés's meeting with Moteucçoma, it is clear that the utility of wealth and the unprecedented opportunities to move to a new socioeconomic class were strong factors in the decision making of the participants.

scholarly journals A rationalist explanation of Russian risk-taking

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Frank Lehrbass ◽  
Valentin Weinhold
Keyword(s):  
Utility Function ◽  
Expected Utility ◽  
Risk Taking ◽  
Utility Maximization ◽  
Strictly Convex ◽  
Forward Market ◽  
Expected Utility Maximization ◽  
Russian Politics ◽  
Open Position

Three seemingly unrelated topics of Russian politics are investigated. It is shown that under expected utility maximization the assumptions of an unbiased oil forward market and a risk-acceptant attitude (strictly convex utility function) are sufficient to explain Russia’s open position in oil and the bailout of Rosneft. The risk-acceptant attitude of the Russian leader also causes a shrunken bargaining range for the conflict in Ukraine, which can be enlarged by sanctions but not necessarily by the proliferation of weapons. This gives sanctions a clear edge over the proliferation of weapons.

Alternative Decision Criteria

2012 ◽  
Author(s):  
Christian Gollier
Keyword(s):  
Utility Function ◽  
Expected Utility ◽  
Decision Criteria ◽  
Good For ◽  
Alternative Decision ◽  
Consumption Habits

This chapter describes a sample of the alternative decision criteria that have features which are normatively attractive. A standard critique made to the discounted expected utility (DEU) model that has been used in this volume is that the concavity of the utility function expresses at the same time the aversion to inequalities and the aversion to risk. Moreover, it does not take into account the possibility of an aversion to ambiguity on probabilities, or the formation of consumption habits. Such issues imply that the DEU model is not very good for explaining, or predicting, actual behaviors under uncertainty. However, as this book aims for normative rather than positive arguments, this chapter focuses not on what people actually do, but instead on determining what they should do.

From Chicago to Paris

2018 ◽  
pp. 177-192
Author(s):  
Ivan Moscati
Keyword(s):  
Decision Making ◽  
Utility Function ◽  
Expected Utility ◽  
Economic Model ◽  
Expected Utility Theory ◽  
Second Phase ◽  
Cardinal Utility ◽  
Decision Making Under Risk ◽  
The Face

Chapter 11 studies the second phase of the debate on expected utility theory (EUT), which commenced in May 1950, when Paul Samuelson, Leonard J. Savage, Jacob Marschak, Milton Friedman, and William Baumol initiated an intense exchange of letters. These economists argued about the exact assumptions underlying EUT, quarreled over whether these assumptions are compelling requisites for rational behavior under risk, and debated the nature of the cardinal utility function u featured in EUT. This correspondence modified the views of all five economists and transformed Samuelson into a supporter of EUT. In a prominent conference in Paris in May 1952, Friedman, Savage, Marschak, and Samuelson advocated EUT in the face of attacks from Maurice Allais and other opponents of the theory. The Paris conference and the publication of an Econometrica symposium on EUT in October 1952 marked the emergence of EUT as the mainstream economic model of decision-making under risk.

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