By Stefano Zambelli, Donald A.R. George
The "great crash of 2008" and its linked banking predicament have printed the restrictions of mainstream economics. whereas exposing the expanding irrelevance of the sector, they've got pressured a few economists to re–examine their self-discipline. The monetary meltdown additionally confirmed how conventional linear or linearised versions with well–behaved additive stochastic disturbances, in line with orthodox "microeconomic foundations", should not sufficient to house the complexities of today′s international. Nonlinearity, Complexity and Randomness in Economics provides a number of innovative papers by means of prime economists, scientists, and philosophers.
Topics explored comprise nonlinear macroeconomic modelling, agent–based modelling, information–theoretic modelling of monetary markets, bounded rationality, and emergent complexity. using an interdisciplinary technique, Nonlinearity, Complexity and Randomness in Economics unearths how real highbrow rigour in economics calls for a foundation in algorithmic, computable mathematical foundations.
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Extra info for Nonlinearity, Complexity and Randomness in Economics: Towards Algorithmic Foundations for Economics (Surveys of Recent Research in Economics)
In B. Engquist and W. Schmid (eds), Mathematics Unlimited – 2001 and Beyond (pp. 919–936). Berlin, Germany: Springer-Verlag. Moschoavakis, Yiannis N. and Vasilis Paschalis (2008) Elementary algorithms and their implementations. In S. Barry Cooper, Benedikt L¨owe and Andrea Sorbi (eds), New Computational Paradigms: Changing Conceptions of What is Computable (pp. 87–118). New York: Springer Science and Business Media LLC. Newell, Allen and Herbert A. Simon (1972) Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall, Inc.
Proceedings of the Fifth International Congress of Mathematicians (11–28 August, 1912, Vol. 2, pp. 501–504). Cambridge, UK: Cambridge University Press. P1: TIX/XYZ JWST133-c02 P2: ABC JWST133-Zambelli 10-13-2011 :1270 Printer Name: Yet to Come P1: TIX/XYZ JWST133-c03 P2: ABC JWST133-Zambelli 10-13-2011 :1273 Printer Name: Yet to Come 3 AN ALGORITHMIC INFORMATIONTHEORETIC APPROACH TO THE BEHAVIOUR OF FINANCIAL MARKETS Hector Zenil and Jean-Paul Delahaye 1. Introduction One of the main assumptions regarding price modelling for option pricing is that stock prices in the market behave as stochastic processes, that is, that price movements are log-normally distributed.
Velupillai, K. Vela (2006) The algorithmic foundations of computable general equilibrium theory. Applied Mathematics and Computation 179(1): 360–369. Velupillai, K. Vela (2009) Uncomputability and undecidability in economic theory. Applied Mathematics and Computation 215(4): 1404–1416. Velupillai, K. Vela (2009a) A computable economist’s perspective on computational complexity, J. Barkley Rosser, Jr. ), The Handbook of Complexity Research (Chapter 4, pp. 36–83). Cheltenham, Gloucestershire, UK: Edward Elgar Publishing Ltd.