A Potential-Field Approach to Financial Time Series Modelling
We present a new approach to the problem of time series modelling that captures the invariant distribution of time series data within the model. This is particularly relevant in modelling economic and financial time series, such as oil prices, that exhibit clustering around a few preferred market modes. We propose a potential function approach which determines the function that governs the underlying time series process. This approach extends naturally to modelling multivariate time series. We show how to estimate the potential function for dimensions one and higher and use it to model statistically the evolution of the time series. An illustration of the procedure shows that testing the resulting model against historical data of oil prices captures the essential price behavior remarkably well. The model allows the generation of copies of the observed time series as well as providing better predictions by reducing uncertainty about the future behavior of the time series. Copyright Kluwer Academic Publishers 2003
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Volume (Year): 22 (2003)
Issue (Month): 2 (October)
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References listed on IDEAS
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- Brock, William A. & Hommes, Cars H., 1998.
"Heterogeneous beliefs and routes to chaos in a simple asset pricing model,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 22(8-9), pages 1235-1274, August.
- Brock, W.A. & Hommes, C.H., 1996. "Hetergeneous Beliefs and Routes to Chaos in a Simple Asset Pricing Model," Working papers 9621, Wisconsin Madison - Social Systems.
- Brock,W.A. & Hommes,C.H., 2001. "Evolutionary dynamics in financial markets with many trader types," Working papers 7, Wisconsin Madison - Social Systems.
- Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2001. "Evolutionary Dynamics in Financial Markets With Many Trader Types," CeNDEF Working Papers 01-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- W.A. Brock, C.H. Hommes and F.O.O. Wagener, 2001. "Evolutionary dynamics in financial markets with many trader types," Computing in Economics and Finance 2001 119, Society for Computational Economics.
- C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
- Hommes, C.H., 2000. "Financial Markets as Nonlinear Adaptive Evolutionary Systems," CeNDEF Working Papers 00-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Cars H. Hommes, 2001. "Financial Markets as Nonlinear Adaptive Evolutionary Systems," Tinbergen Institute Discussion Papers 01-014/1, Tinbergen Institute.
- Gaunersdorfer, A. & Hommes, C.H. & Wagener, F.O.O., 2000. "Bifurcation Routes to Volatility Clustering," CeNDEF Working Papers 00-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Andrea Gaunersdorfer & Cars Hommes & Florian O.O. Wagener, 2001. "Bifurcation Routes to Volatility Clustering," Tinbergen Institute Discussion Papers 01-015/1, Tinbergen Institute.
- Brock, W.A. & Hommes, C.H., 1997. "Models of Compelxity in Economics and Finance," Working papers 9706, Wisconsin Madison - Social Systems. Full references (including those not matched with items on IDEAS)
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