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Price-Volume Relations in Financial Market

Author

Listed:
  • Weihong HUANG

    (Division of Economics, Nanyang Technological University, Singapore 637332, Singapore)

  • Wanying Wang

    (Division of Economics, Nanyang Technological University, Singapore 637332, Singapore)

Abstract

Though the price-volume relations are widely documented by practitioners and empirical studies, few theoretical models can reproduce these relations and provide persuasive arguments. By simply generalizing the classical market maker framework, our heterogeneous agent model not only simulates satisfactorily the seemingly chaotic fluctuations in price and volume in a way that is highly compatible with the real market, but replicates patterns in the movements of price-volume, particularly those patterns used in technical analysis. Most importantly, based on this model, plausible economic arguments are provided to support the rationale of correlations between asset returns and volumes.

Suggested Citation

  • Weihong HUANG & Wanying Wang, 2012. "Price-Volume Relations in Financial Market," Economic Growth Centre Working Paper Series 1209, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    • Handle: RePEc:nan:wpaper:1209
    as

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    References listed on IDEAS

    as
    1. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
    2. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    3. Mendel, Brock & Shleifer, Andrei, 2012. "Chasing noise," Journal of Financial Economics, Elsevier, vol. 104(2), pages 303-320.
    4. Carl Chiarella & Mauro Gallegati & Roberto Leombruni & Antonio Palestrini, 2003. "Asset Price Dynamics among Heterogeneous Interacting Agents," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 213-223, October.
    5. Morgan, I G, 1976. "Stock Prices and Heteroscedasticity," The Journal of Business, University of Chicago Press, vol. 49(4), pages 496-508, October.
    6. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    7. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, August.
    8. Silvapulle, Param & Choi, Jong-Seo, 1999. "Testing for linear and nonlinear granger causality in the stock price-volume relation: Korean evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 39(1), pages 59-76.
    9. Anirut Pisedtasalasai & Abeyratna Gunasekarage, 2007. "Causal and Dynamic Relationships among Stock Returns, Return Volatility and Trading Volume: Evidence from Emerging markets in South-East Asia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(4), pages 277-297, December.
    10. Jennings, Robert H. & Barry, Christopher B., 1983. "Information Dissemination and Portfolio Choice," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 18(1), pages 1-19, March.
    11. Huang, Weihong & Zheng, Huanhuan & Chia, Wai-Mun, 2010. "Financial crises and interacting heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1105-1122, June.
    12. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    13. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    14. Berrada, Tony & Hugonnier, Julien & Rindisbacher, Marcel, 2007. "Heterogeneous preferences and equilibrium trading volume," Journal of Financial Economics, Elsevier, vol. 83(3), pages 719-750, March.
    15. Grammatikos, Theoharry & Saunders, Anthony, 1986. "Futures Price Variability: A Test of Maturity and Volume Effects," The Journal of Business, University of Chicago Press, vol. 59(2), pages 319-330, April.
    16. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    17. Massimo Guidolin & Allan Timmermann, 2008. "International asset allocation under regime switching, skew, and kurtosis preferences," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 889-935, April.
    18. Beja, Avraham & Goldman, M Barry, 1980. "On the Dynamic Behavior of Prices in Disequilibrium," Journal of Finance, American Finance Association, vol. 35(2), pages 235-248, May.
    19. Snehal Banerjee & Ilan Kremer, 2010. "Disagreement and Learning: Dynamic Patterns of Trade," Journal of Finance, American Finance Association, vol. 65(4), pages 1269-1302, August.
    20. Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.
    21. Crouch, R L, 1970. "A Nonlinear Test of the Random-Walk Hypothesis," American Economic Review, American Economic Association, vol. 60(1), pages 199-202, March.
    22. Huang, Weihong & Zheng, Huanhuan, 2012. "Financial crises and regime-dependent dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 445-461.
    23. Saatcioglu, Kemal & Starks, Laura T., 1998. "The stock price-volume relationship in emerging stock markets: the case of Latin America," International Journal of Forecasting, Elsevier, vol. 14(2), pages 215-225, June.
    24. Epps, Thomas W, 1975. "Security Price Changes and Transaction Volumes: Theory and Evidence," American Economic Review, American Economic Association, vol. 65(4), pages 586-597, September.
    25. Lokman Gündüz & Abdulnasser Hatemi-J, 2005. "Stock Price and Volume Relation in Emerging Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 41(1), pages 29-44, January.
    26. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    27. Harris, Lawrence E & Gurel, Eitan, 1986. "Price and Volume Effects Associated with Changes in the S&P 500 List: New Evidence for the Existence of Price Pressures," Journal of Finance, American Finance Association, vol. 41(4), pages 815-829, September.
    28. Alexander David, 2008. "Heterogeneous Beliefs, Speculation, and the Equity Premium," Journal of Finance, American Finance Association, vol. 63(1), pages 41-83, February.
    29. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    30. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
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    More about this item

    Keywords

    Price-volume relations; Heterogeneous beliefs; Technical analysis; Deterministic nonlinear dynamics;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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