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Expected Subjective Value Theory (ESVT): A Representation of Decision Under Risk and Certainty

Agnieszka Anna Tymula, University of Sydney - School of Economics, New York University (NYU) - Center for Neuroeconomics
Paul W. Glimcher, New York University (NYU) - Center for Neuroeconomics

Prediction of Trading Profit of Transnational Company Using Artificial Neural Networks: A Case Study of Nestle in Europe

Svitlana Galeshchuk, Ternopil National Economic University


NEUROECONOMICS eJOURNAL

"Expected Subjective Value Theory (ESVT): A Representation of Decision Under Risk and Certainty" Free Download

AGNIESZKA ANNA TYMULA, University of Sydney - School of Economics, New York University (NYU) - Center for Neuroeconomics
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PAUL W. GLIMCHER, New York University (NYU) - Center for Neuroeconomics
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We present a descriptive model of choice that incorporates neurobiological constraints, representational structures and costs into a traditional economic framework. An individual's behavior is fully described by two, in principle observable, primitives: an individual's neural/mental capacity and an endogenous rational expectation. The model captures the phenomena captured by Prospect Theory: reflection in risk attitudes and loss aversion, but unlike Prospect Theory accounts for individual heterogeneity in each and employs fewer parameters. Our theory provides an alternative explanation for endowment effect and makes a series of novel predictions amenable to future testing.

"Prediction of Trading Profit of Transnational Company Using Artificial Neural Networks: A Case Study of Nestle in Europe" 
Journal of Global Economics, Management and Business Research, Vol. 7(2): 96-102, 2016

SVITLANA GALESHCHUK, Ternopil National Economic University
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Application of artificial neural networks for economic forecasting is described and empirically examined with Nestle financial reporting data. For the experiments, panel data of the exchange rates as well as trading profit, volume of sales, currency retranslations, and effects of exchange rate changes are used to predict future quarterly profits with neural networks. The best neural network model is found with the best forecasting abilities, based on a mean absolute percentage error measure. Values of prediction errors (mean and maximum errors for 8 quarters of 2013-2014 do not exceed 5.4% and 8.7% respectively) show that artificial neural networks can provide accurate prediction results for international firms’ profit. Accurate prediction results can provide improved strategic management of international companies that conduct operations in foreign currencies.

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About this eJournal

This eJournal distributes working and accepted paper abstracts focused on research where economic outcomes are the product of many individual decisions, constrained by scarcity, and equilibrium forces that simultaneously shape a person's social networks and the institutionally defined rules of the game. Decisions are made by computations in the brain which produce action-choices that directly affect the homeostatic wellbeing of the individual and choices that indirectly change wellbeing by changing an individual's future constraints, the scope of their social networks, and their message sending rights within the institutions they participate. Neuroeconomics broadly speaking is interested in the study of these computations and the resulting choices they produce. This includes experiments that attempt to understand the mechanisms of neuronal computations that produce action-choices, theories which predict how neuronal computations in socio-economic environments produce decisions, outcomes and wellbeing, and policy which use our understanding of neuoroeconomic behavior to either build or defend better solutions to societal problems.

Editors: Michael C. Jensen, Harvard University, and Kevin A. McCabe, George Mason University

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Social Science Electronic Publishing (SSEP), Inc., Harvard Business School, National Bureau of Economic Research (NBER), European Corporate Governance Institute (ECGI)
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Neuroeconomics eJournal

ANDREW W. LO
Harris & Harris Group Professor, Massachusetts Institute of Technology (MIT) - Sloan School of Management, National Bureau of Economic Research (NBER)

P. READ MONTAGUE
Professor, Baylor University - Department of Neuroscience

VERNON L. SMITH
Professor of Economics and Law, Chapman University - Economic Science Institute, Chapman University School of Law