Quantifying Stock Return Distributions in Financial Markets

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Botta, Federico ; Moat, Helen Susannah ; Stanley, H. Eugene ; Preis, Tobias (2015)

Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales.
  • References (48)
    48 references, page 1 of 5

    1. Sornette D. Why stock markets crash: critical events in complex financial systems. Princeton, NJ: Princeton University Press; 2004.

    2. Farmer JD, Joshi S. The price dynamics of common trading strategies. J Econ Behav Organ. 2002; 49: 149-171 doi: 10.1016/S0167-2681(02)00065-3

    3. Voit J. The statistical mechanics of financial markets. Heidelberg: Springer; 2005.

    4. Paul W, Baschnagel J. Stochastic processes: from physics to finance. Switzerland: Springer International Publishing; 2013.

    5. Abergel F, Chakrabarti BK, Charaborti A, Mitra M. Econophysics of order-driven markets. Milan: Springer; 2011.

    6. Lux T, Westerhoff F. Economics crisis. Nat Phys. 2009; 5: 2-3 doi: 10.1038/nphys1163

    7. Farmer JD, Foley D. The economy needs agent-based modeling. Nature. 2009; 460: 685-686 doi: 10. 1038/460685a PMID: 19661896.

    8. Feng L, Baowen L, Podobnik B, Preis T, Stanley HE. Linking agent-based models and stochastic models of financial markets. Proc Natl Acad Sci USA. 2012; 109: 8388-8393 doi: 10.1073/pnas. 1205013109 PMID: 22586086.

    9. Petersen AM, Wang F, Havlin S, Stanley HE. Market dynamics immediately before and after financial shocks: quantifying the Omori, productivity, and Bath laws. Phys Rev E. 2010; 82: 036114 doi: 10. 1103/PhysRevE.82.036114

    10. Hommes CH. Modeling the stylized facts in finance through simple nonlinear adaptive systems. Proc Natl Acad Sci USA. 2002; 99: 7221-7228 doi: 10.1073/pnas.082080399 PMID: 12011401.

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