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How to compare market efficiency? The Sharpe ratio based on the ARMA-GARCH forecast

Author

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  • Lin Liu

    (Peking University)

  • Qiguang Chen

    (Peking University)

Abstract

This paper derives a new method for comparing the weak-form efficiency of markets. The author derives the formula of the Sharpe ratio from the ARMA-GARCH model and finds that the Sharpe ratio just depends on the coefficients of the AR and MA terms and is not affected by the GARCH process. For empirical purposes, the Sharpe ratio can be formulated with a monotonic increasing function of R-squared if the sample size is large enough. One can utilize the Sharpe ratio to compare weak-form efficiency among different markets. The results of stochastic simulation demonstrate the validity of the proposed method. The author also constructs empirical AR-GARCH models and computes the Sharpe ratio for S&P 500 Index and the SSE Composite Index.

Suggested Citation

  • Lin Liu & Qiguang Chen, 2020. "How to compare market efficiency? The Sharpe ratio based on the ARMA-GARCH forecast," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-21, December.
    • Handle: RePEc:spr:fininn:v:6:y:2020:i:1:d:10.1186_s40854-020-00200-6
    DOI: 10.1186/s40854-020-00200-6
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    References listed on IDEAS

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    1. Mech, Timothy S., 1993. "Portfolio return autocorrelation," Journal of Financial Economics, Elsevier, vol. 34(3), pages 307-344, December.
    2. John M. Griffin & Patrick J. Kelly & Federico Nardari, 2010. "Do Market Efficiency Measures Yield Correct Inferences? A Comparison of Developed and Emerging Markets," The Review of Financial Studies, Society for Financial Studies, vol. 23(8), pages 3225-3277, August.
    3. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    4. Wen, Fenghua & Xu, Longhao & Ouyang, Guangda & Kou, Gang, 2019. "Retail investor attention and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 65(C).
    5. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    6. John H. Cochrane, 1999. "Portfolio advice of a multifactor world," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 59-78.
    7. Huang, Dashan & Zhou, Guofu, 2017. "Upper Bounds on Return Predictability," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(2), pages 401-425, April.
    8. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Analysis and comparison of the multifractality and efficiency of Chinese stock market: Evidence from dynamics of major indexes in different boards," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C).
    9. Potì, Valerio, 2018. "A new tight and general bound on return predictability," Economics Letters, Elsevier, vol. 162(C), pages 140-145.
    10. Kewei Hou & Tobias J. Moskowitz, 2005. "Market Frictions, Price Delay, and the Cross-Section of Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 981-1020.
    11. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Analysis and comparison of the multifractality and efficiency of Chinese stock market: Evidence from dynamics of major indexes in different boards," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C), pages 1-1.
    12. Fang, Yue & Xu, Daming, 2003. "The predictability of asset returns: an approach combining technical analysis and time series forecasts," International Journal of Forecasting, Elsevier, vol. 19(3), pages 369-385.
    13. Kirby, Chris, 1998. "The Restrictions on Predictability Implied by Rational Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 11(2), pages 343-382.
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    Cited by:

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    2. Umara Noreen & Attayah Shafique & Usman Ayub & Syed Kashif Saeed, 2022. "Does the Adaptive Market Hypothesis Reconcile the Behavioral Finance and the Efficient Market Hypothesis?," Risks, MDPI, vol. 10(9), pages 1-14, August.
    3. Yan Meng & Lingyun Xiong & Lijuan Xiao & Min Bai, 2023. "The effect of overseas investors on local market efficiency: evidence from the Shanghai/Shenzhen–Hong Kong Stock Connect," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-32, December.
    4. Subhasis Dasgupta & Pratik Satpati & Ishika Choudhary & Jaydip Sen, 2024. "Understanding the Impact of News Articles on the Movement of Market Index: A Case on Nifty 50," Papers 2412.06794, arXiv.org.
    5. Thibaut Mastrolia & Tianrui Xu, 2024. "Clearing time randomization and transaction fees for auction market design," Papers 2405.09764, arXiv.org, revised Oct 2024.
    6. Chunying Wu & Xiong Xiong & Ya Gao, 2022. "Does ESG Certification Improve Price Efficiency in the Chinese Stock Market?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(1), pages 97-122, March.

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    More about this item

    Keywords

    ARMA; GARCH; Measurement of market efficiency; Sharpe ratio; Stochastic simulation;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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