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Stylized facts in internal rates of return on stock index and its derivative transactions

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  • Pichl, Lukáš
  • Kaizoji, Taisei
  • Yamano, Takuya

Abstract

Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in normalized log returns, the probability distributions for such single asset encounters incorporate the time factor by means of the internal rate of return, defined as the continuous compound interest. Resulting stylized facts are shown in the probability distributions derived from the daily series of TOPIX, S & P 500 and FTSE 100 index close values. The application of the above analysis to minute-tick data of NIKKEI 225 and its futures market, respectively, reveals an interesting difference in the behavior of the two probability distributions, in case a threshold on the minimal duration of the long position is imposed. It is therefore suggested that the probability distributions of the internal rates of return could be used for causality mining between the underlying and derivative stock markets. The highly specific discrete spectrum, which results from noise trader strategies as opposed to the smooth distributions observed for fundamentalist strategies in single encounter transactions may be useful in deducing the type of investment strategy from trading revenues of small portfolio investors.

Suggested Citation

  • Pichl, Lukáš & Kaizoji, Taisei & Yamano, Takuya, 2007. "Stylized facts in internal rates of return on stock index and its derivative transactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 219-227.
    • Handle: RePEc:eee:phsmap:v:382:y:2007:i:1:p:219-227
    DOI: 10.1016/j.physa.2007.03.042
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    References listed on IDEAS

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    1. McCauley, Joseph L., 2003. "Thermodynamic analogies in economics and finance: instability of markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 329(1), pages 199-212.
    2. H. E. Stanley & V. Plerou, 2001. "Scaling and universality in economics: empirical results and theoretical interpretation," Quantitative Finance, Taylor & Francis Journals, vol. 1(6), pages 563-567.
    3. Frantisek Slanina, 1999. "On the possibility of optimal investment," Papers cond-mat/9905050, arXiv.org, revised May 1999.
    4. McCauley, Joseph l., 2004. "Thermodynamic analogies in economics and finance: instability of markets," MPRA Paper 2159, University Library of Munich, Germany.
    5. Slanina, František, 1999. "On the possibility of optimal investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(2), pages 554-563.
    6. Fengzhong Wang & Kazuko Yamasaki & Shlomo Havlin & H. Eugene Stanley, 2005. "Scaling and memory of intraday volatility return intervals in stock market," Papers physics/0511101, arXiv.org.
    7. J. Doyne Farmer & Martin Shubik & Eric Smith, 2005. "Economics: the next physical science?," Cowles Foundation Discussion Papers 1520, Cowles Foundation for Research in Economics, Yale University.
    8. Chen, Shu-Heng & Lux, Thomas & Marchesi, Michele, 2001. "Testing for non-linear structure in an artificial financial market," Journal of Economic Behavior & Organization, Elsevier, vol. 46(3), pages 327-342, November.
    9. Lux, Thomas & Schornstein, Sascha, 2005. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 169-196, February.
    10. Carbone, A. & Castelli, G. & Stanley, H.E., 2004. "Time-dependent Hurst exponent in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 267-271.
    Full references (including those not matched with items on IDEAS)

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