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Surviving Black Swans II: Timing the 2020–2022 Roller Coaster

Author

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  • Pankaj Topiwala

    (FastVDO LLC, 3097 Cortona Dr., Melbourne, FL 32940, USA)

Abstract

Unbeknownst to the public, most investment funds actually underperform the broader market. Yet, millions of individual investors fare even worse, barely treading water. Algorithmic trading now accounts for over 80% of all trades and is the domain of professionals. Can it also help the small investor? In a previous paper, we laid the foundations of a simple algorithmic market timing approach based on the moving average crossover concept which can indeed both outperform the broader market and reduce drawdowns, in a way that even the retail investor can benefit. In this paper, we extend our work to study the recent volatile time period, 2020–2022, and especially the unexpected market roller coaster of 2022, to see how our ideas hold up. While our methods overall would not have made gains in 2022, they would have suffered lessor drawdowns than the market, and made consistent gains over longer periods, including the volatile 2020–2022 period. In addition, at least one of our algorithms would have made handsome profits even in 2022, and can generally negotiate black swans well.

Suggested Citation

  • Pankaj Topiwala, 2023. "Surviving Black Swans II: Timing the 2020–2022 Roller Coaster," JRFM, MDPI, vol. 16(2), pages 1-26, February.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:2:p:106-:d:1063150
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    References listed on IDEAS

    as
    1. Pankaj Topiwala & Wei Dai, 2022. "Surviving Black Swans: The Challenge of Market Timing Systems," JRFM, MDPI, vol. 15(7), pages 1-25, June.
    2. Graham, John R. & Harvey, Campbell R., 1996. "Market timing ability and volatility implied in investment newsletters' asset allocation recommendations," Journal of Financial Economics, Elsevier, vol. 42(3), pages 397-421, November.
    3. Chen, Yong & Liang, Bing, 2007. "Do Market Timing Hedge Funds Time the Market?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(4), pages 827-856, December.
    4. Merton, Robert C, 1981. "On Market Timing and Investment Performance. I. An Equilibrium Theory of Value for Market Forecasts," The Journal of Business, University of Chicago Press, vol. 54(3), pages 363-406, July.
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    Cited by:

    1. ChanKyu Paik & Jinhee Choi & Ivan Ureta Vaquero, 2024. "Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator, Williams%R, and Trading Volume for the S&P 500," JRFM, MDPI, vol. 17(11), pages 1-20, November.
    2. Pankaj Topiwala, 2023. "Surviving Black Swans III: Timing US Sector Funds," JRFM, MDPI, vol. 16(5), pages 1-18, May.

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