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Price equations with symmetric supply/demand; implications for fat tails

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  • Caginalp, Carey
  • Caginalp, Gunduz

Abstract

Implementing a set of microeconomic criteria, we develop price dynamics equations using a function of demand/supply with key symmetry properties. The function of demand/supply can be linear or nonlinear. The type of function determines the nature of the tail of the distribution based on the randomness in the supply and demand. For example, if supply and demand are normally distributed, and the function is assumed to be linear, then the density of relative price change has behavior x−2 for large x (i.e., large deviations). The exponent approaches −1 if the function of supply and demand involves a large exponent. The falloff is exponential, i.e., e−x, if the function of supply and demand is logarithmic.

Suggested Citation

  • Caginalp, Carey & Caginalp, Gunduz, 2019. "Price equations with symmetric supply/demand; implications for fat tails," Economics Letters, Elsevier, vol. 176(C), pages 79-82.
    • Handle: RePEc:eee:ecolet:v:176:y:2019:i:c:p:79-82
    DOI: 10.1016/j.econlet.2018.12.037
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    1. Hirshleifer,Jack & Glazer,Amihai & Hirshleifer,David, 2005. "Price Theory and Applications," Cambridge Books, Cambridge University Press, number 9780521523424, September.
    2. Kirchler, Michael & Huber, Jurgen, 2007. "Fat tails and volatility clustering in experimental asset markets," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1844-1874, June.
    3. Caginalp, Carey & Caginalp, Gunduz, 2018. "The quotient of normal random variables and application to asset price fat tails," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 457-471.
    4. Marsaglia, George, 2006. "Ratios of Normal Variables," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 16(i04).
    5. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2006. "Institutional Investors and Stock Market Volatility," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 461-504.
    6. Charles R. Plott & Kirill Pogorelskiy, 2017. "Call Market Experiments: Efficiency and Price Discovery through Multiple Calls and Emergent Newton Adjustments," American Economic Journal: Microeconomics, American Economic Association, vol. 9(4), pages 1-41, November.
    7. Daníelsson, Jón & Jorgensen, Bjørn N. & Samorodnitsky, Gennady & Sarma, Mandira & de Vries, Casper G., 2013. "Fat tails, VaR and subadditivity," Journal of Econometrics, Elsevier, vol. 172(2), pages 283-291.
    8. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    9. Eloísa Díaz-Francés & Francisco Rubio, 2013. "On the existence of a normal approximation to the distribution of the ratio of two independent normal random variables," Statistical Papers, Springer, vol. 54(2), pages 309-323, May.
    10. Schneeweiss, Ch., 1987. "On a formalisation of the process of quantitative model building," European Journal of Operational Research, Elsevier, vol. 29(1), pages 24-41, April.
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    Cited by:

    1. Jack Sarkissian, 2020. "Quantum coupled-wave theory of price formation in financial markets: price measurement, dynamics and ergodicity," Papers 2002.04212, arXiv.org.
    2. Caginalp, Carey & Caginalp, Gunduz & Swigon, David, 2021. "Stochastic asset flow equations: Interdependence of trend and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    3. Sarkissian, Jack, 2020. "Quantum coupled-wave theory of price formation in financial markets: Price measurement, dynamics and ergodicity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    4. Caginalp, Carey & Caginalp, Gunduz, 2020. "Derivation of non-classical stochastic price dynamics equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    5. Carey Caginalp & Gunduz Caginalp, 2019. "Derivation of non-classical stochastic price dynamics equations," Papers 1908.01103, arXiv.org, revised Aug 2020.
    6. Gunduz Caginalp, 2020. "Fat tails arise endogenously in asset prices from supply/demand, with or without jump processes," Papers 2011.08275, arXiv.org, revised Mar 2021.

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    More about this item

    Keywords

    Price dynamics; Fat tails; Supply/demand; Asset flow equations;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • G4 - Financial Economics - - Behavioral Finance
    • D0 - Microeconomics - - General
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

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