Evolution And Time Horizons In An Agent-Based Stock Market
Recent research has shown the importance of time horizons in models of learning in finance. The dynamics of how agents adjust to believe that the world around them is stationary may be just as crucial in the convergence to a rational-expectations equilibrium as getting parameters and model specifications correct in the learning process. This paper explores the process of this evolution in learning and time horizons in a simple agent-based financial market. Trading is done in a market with a single stock in finite supply, paying a stochastic dividend. A risk free asset is available in infinite supply. Agents maximize an infinite-horizon time-separable utility function in each period's consumption. They are required to select from a set of given forecasting/trading rules optimized to past data. Heterogeneity is introduced through the time horizon that they believe is relevant to use in deciding over trading rules. Long horizon agents build relative performance measures looking back into the distant past, while those with short horizons believe that only recent measures of performance are useful for decision making. The price of the risky asset is set to balance current agent demand with its fixed supply at each period. Once the price is endogenously determined, returns are calculated and dividends paid. Agents make consumption decisions and wealth is calculated. Relative wealth affects the market in two ways. First, wealthier individuals are able to move prices by larger amounts. Second, evolution takes place in which less wealthy agents are dropped out of the market and replaced with new ones drawn according to current wealth levels. The horizon lengths of wealthier agents are given more weight in the generation of new agents. The primary objectives of this paper are to understand better the convergence properties of learning with heterogeneous horizons. Several benchmark cases are explored in which a stationary rational-expectations equilibrium exists, and agents sh
(This abstract was borrowed from another version of this item.)
Volume (Year): 5 (2001)
Issue (Month): 02 (April)
|Contact details of provider:|| Postal: Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK|
Web page: http://journals.cambridge.org/jid_MDY
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- J. Doyne Farmer, 1999.
"Market Force, Ecology, and Evolution,"
Computing in Economics and Finance 1999
651, Society for Computational Economics.
- Bullard, James & Duffy, John, 2001.
"Learning And Excess Volatility,"
Cambridge University Press, vol. 5(02), pages 272-302, April.
- Brock, William A & LeBaron, Blake D, 1996.
"A Dynamic Structural Model for Stock Return Volatility and Trading Volume,"
The Review of Economics and Statistics,
MIT Press, vol. 78(1), pages 94-110, February.
- William A. Brock & Blake D. LeBaron, 1995. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," NBER Working Papers 4988, National Bureau of Economic Research, Inc.
- 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.
- Blume, Lawrence & Easley, David, 1992. "Evolution and market behavior," Journal of Economic Theory, Elsevier, vol. 58(1), pages 9-40, October.
- Egenter, E. & Lux, T. & Stauffer, D., 1999. "Finite-size effects in Monte Carlo simulations of two stock market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 268(1), pages 250-256.
- John Y. Campbell & Luis M. Viceira, 1996.
"Consumption and Portfolio Decisions When Expected Returns are Time Varying,"
NBER Working Papers
5857, National Bureau of Economic Research, Inc.
- John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 433-495.
- John Y. Campbell & Luis M. Viceira, 1998. "Consumption and Portfolio Decisions When Expected Returns Are Time Varying," Harvard Institute of Economic Research Working Papers 1835, Harvard - Institute of Economic Research.
- Campbell, John & Viceira, Luis, 1999. "Consumption and Portfolio Decisions When Expected Returns are Time Varying," Scholarly Articles 3163266, Harvard University Department of Economics.
- Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762, November.
- Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, 02.
- Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.
- Evans, George W & Honkapohja, Seppo, 1995. "Local Convergence of Recursive Learning to Steady States and Cycles in Stochastic Nonlinear Models," Econometrica, Econometric Society, vol. 63(1), pages 195-206, January.
- G. Caldarelli & M. Marsili & Y. -C. Zhang, 1997. "A Prototype Model of Stock Exchange," Papers cond-mat/9709118, arXiv.org.
- Brock, W.A., 1995.
"A Rational Route to Randomness,"
9530, Wisconsin Madison - Social Systems.
- Michael W. Brandt, 1999. "Estimating Portfolio and Consumption Choice: A Conditional Euler Equations Approach," Journal of Finance, American Finance Association, vol. 54(5), pages 1609-1645, October.
- Rajesh Chakrabarti, 1999. "Just Another Day in the Inter-bank Foreign Exchange Market," Computing in Economics and Finance 1999 652, Society for Computational Economics.
- C. Busshaus & H. Rieger, 1999. "A prognosis oriented microscopic stock market model," Papers cond-mat/9903079, arXiv.org.
- Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-81, September.
- Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
- Bußhaus, Christian & Rieger, Heiko, 1999. "A prognosis oriented microscopic stock market model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 267(3), pages 443-452.
- Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
When requesting a correction, please mention this item's handle: RePEc:cup:macdyn:v:5:y:2001:i:02:p:225-254_01. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Keith Waters)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.