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Time series momentum in the US stock market: Empirical evidence and theoretical analysis

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  • Zakamulin, Valeriy
  • Giner, Javier

Abstract

There is much controversy in the academic literature on the presence of short-term trends in financial markets and the trend-following strategy’s profitability. We restrict our attention to studying the time series momentum in the S&P Composite stock price index. Our contributions are both empirical and theoretical. On the empirical side, we present compelling evidence of the presence of short-term momentum. For the first time, we suppose that the returns follow a p-order autoregressive process and evaluate this process’s parameters. On the theoretical side, we develop a tractable theoretical model that contributes to our fundamental understanding of the trend-following strategy’s risk, return, and performance. Using our model, we also estimate the power of statistical tests on the trend-following strategy’s profitability and find that these tests suffer from the low power problem.

Suggested Citation

  • Zakamulin, Valeriy & Giner, Javier, 2022. "Time series momentum in the US stock market: Empirical evidence and theoretical analysis," International Review of Financial Analysis, Elsevier, vol. 82(C).
  • Handle: RePEc:eee:finana:v:82:y:2022:i:c:s1057521922001363
    DOI: 10.1016/j.irfa.2022.102173
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    Citations

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    Cited by:

    1. Bing Xiao, 2023. "The Size Effect and the Value Effect in the American Stock Market," Post-Print hal-04194510, HAL.
    2. Day, Min-Yuh & Ni, Yensen, 2023. "Do clean energy indices outperform using contrarian strategies based on contrarian trading rules?," Energy, Elsevier, vol. 272(C).
    3. Giner, Javier & Zakamulin, Valeriy, 2023. "A regime-switching model of stock returns with momentum and mean reversion," Economic Modelling, Elsevier, vol. 122(C).
    4. Marco Corazza & Claudio Pizzi & Andrea Marchioni, 2024. "A financial trading system with optimized indicator setting, trading rule definition, and signal aggregation through Particle Swarm Optimization," Computational Management Science, Springer, vol. 21(1), pages 1-29, June.
    5. Zakamulin, Valeriy & Giner, Javier, 2023. "Optimal trend-following with transaction costs," International Review of Financial Analysis, Elsevier, vol. 90(C).
    6. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Economics Discussion Papers em-dp2022-10, Department of Economics, University of Reading.
      • Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
    7. Ming, Lei & Song, Wuqi & Dong, Minyi, 2023. "Revisiting time series momentum in China's commodity futures market: Evidence on sources of momentum profits," Economic Modelling, Elsevier, vol. 128(C).
    8. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.

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    More about this item

    Keywords

    Time series momentum; Trend-following; Profitability; Statistical power;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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