McCauley, Joseph L. (2004): Making dynamic modelling effective in economics. Published in: Physica A , Vol. 355, (2005): pp. 19.

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Abstract
Mathematics has been extremely effective in physics, but not in economics beyond finance. To establish economics as science we should follow the Galilean method and try to deduce mathematical models of markets from empirical data, as has been done for financial markets. Financial markets are nonstationary. This means that 'value' is subjective. Nonstationarity also means that the form of the noise in a market cannot be postulated a priroi, but must be deduced from the empirical data. I discuss the essence of complexity in a market as unexpected events, and end with a biological speculation about market growth.
Item Type:  MPRA Paper 

Institution:  University of Houston 
Original Title:  Making dynamic modelling effective in economics 
Language:  English 
Keywords:  Economics; fniancial markets; stochastic process; Markov process; complex systems 
Subjects:  C  Mathematical and Quantitative Methods > C0  General G  Financial Economics > G0  General A  General Economics and Teaching > A2  Economic Education and Teaching of Economics 
Item ID:  2130 
Depositing User:  Joseph L. McCauley 
Date Deposited:  09 Mar 2007 
Last Modified:  03 Oct 2019 04:55 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/2130 