Making dynamic modelling effective in economics
AbstractMathematics 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 2130.
Date of creation: Mar 2004
Date of revision:
Economics; fniancial markets; stochastic process; Markov process; complex systems;
Find related papers by JEL classification:
- C0 - Mathematical and Quantitative Methods - - General
- G0 - Financial Economics - - General
- A2 - General Economics and Teaching - - Economic Education and Teaching of Economics
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Research in Economics
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