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Prospect Theory Behavioral Assumptions in an Artificial Financial Economy

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Complexity and Artificial Markets

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 614))

Abstract

We present a model of an artificial financial economy, where a number of heterogenous agents, i.e., households, firms, and a commercial bank make endogenous financial decisions which involve portfolio investments for households, capital structure and dividends policy for firms, and lending and borrowing rates for the commercial bank. Labour income for households and earnings for firms are exogenous determined, according to two independent stochastic processes. Economic policy is set by a government which collects taxes and issues government bonds, and by a central bank which fixes the base interest rate. The purpose of the computational experiments presented in this paper is to focus the attention on a particular and very important aspect concerning the way households form their preferences. In order to include psychological traits in household decision making, Prospect Theory have inspired our study. Indeed, Prospect Theory is a well established framework with a rich theoretical and experimental literature. Computational experiments point out that prospect theory psychological assumptions influence many important financial processes, like assets prices formation and portfolio selection. In particular, loss aversion influences the financial market in a not trivial way. The main results of our study is the emergence of a clear relation between the evaluation period of the household and its portfolio composition in terms of the ratio between risky assets, i.e., stocks, and less risky assets, i.e., bonds. Finally, the model offers more elements to interpret the equity premium puzzle, clearly showing that the stocks-bonds ratio does not depend only from risk-aversion but also from households evaluation periods.

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Raberto, M., Teglio, A., Cincotti, S. (2008). Prospect Theory Behavioral Assumptions in an Artificial Financial Economy. In: Schredelseker, K., Hauser, F. (eds) Complexity and Artificial Markets. Lecture Notes in Economics and Mathematical Systems, vol 614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70556-7_5

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