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Path integral for equities: Dynamic correlation and empirical analysis

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  • Baaquie, Belal E.
  • Cao, Yang
  • Lau, Ada
  • Tang, Pan

Abstract

This paper develops a model to describe the unequal time correlation between rate of returns of different stocks. A non-trivial fourth order derivative Lagrangian is defined to provide an unequal time propagator, which can be fitted to the market data. A calibration algorithm is designed to find the empirical parameters for this model and different de-noising methods are used to capture the signals concealed in the rate of return. The detailed results of this Gaussian model show that the different stocks can have strong correlation and the empirical unequal time correlator can be described by the model’s propagator. This preliminary study provides a novel model for the correlator of different instruments at different times.

Suggested Citation

  • Baaquie, Belal E. & Cao, Yang & Lau, Ada & Tang, Pan, 2012. "Path integral for equities: Dynamic correlation and empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1408-1427.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:4:p:1408-1427
    DOI: 10.1016/j.physa.2011.09.039
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    References listed on IDEAS

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    1. 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.
    2. 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.
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    Citations

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    Cited by:

    1. Baaquie, Belal E. & Cao, Yang, 2014. "Option volatility and the acceleration Lagrangian," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 337-363.
    2. Belal E. Baaquie, 2012. "Statistical Microeconomics," Papers 1211.7172, arXiv.org.
    3. Xiangyi Meng & Jian-Wei Zhang & Jingjing Xu & Hong Guo, 2014. "Quantum spatial-periodic harmonic model for daily price-limited stock markets," Papers 1405.4490, arXiv.org.
    4. Baaquie, Belal E. & Du, Xin & Tanputraman, Winson, 2015. "Empirical microeconomics action functionals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 19-37.
    5. Pan Tang & Belal E. Baaquie & Xin Du & Ying Zhang, 2016. "Linearized Hamiltonian of the LIBOR market model: analytical and empirical results," Applied Economics, Taylor & Francis Journals, vol. 48(10), pages 878-891, February.
    6. Meng, Xiangyi & Zhang, Jian-Wei & Xu, Jingjing & Guo, Hong, 2015. "Quantum spatial-periodic harmonic model for daily price-limited stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 154-160.
    7. Baaquie, Belal E., 2013. "Statistical microeconomics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4400-4416.
    8. Belal Ehsan Baaquie & Muhammad Mahmudul Karim, 2023. "Pricing risky corporate bonds: An empirical study," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 90-121, January.
    9. Baaquie, Belal E. & Du, Xin & Bhanap, Jitendra, 2014. "Option pricing: Stock price, stock velocity and the acceleration Lagrangian," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 564-581.

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