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On the Predictability of the DJIA and S&P500 Indices

Author

Listed:
  • John B. Guerard

    (McKinley Capital Management, LLC)

  • Dimitrios D. Thomakos

    (Department of Business Administration, National and Kapodistrian University of Athens, Athens,10559 Greece; International Centre for Economic Analysis, Canada)

  • Foteini Kyriazi

    (Department of Agribusiness and Supply Chain Management, Agricultural University of Athens)

  • Konstantinos Mamais

    (Department of Business Administration, National and Kapodistrian University of Athens, Athens,10559 Greece)

Abstract

We obtained from Standard and Poor's Corporation, the complete 126-year history of the Dow Jones Industrial Average (DJIA) daily closing prices. We are applying rolling window averaging and adaptive learning methodologies, coupled with robust estimation methods, to examine which are the best forecasting models over a broad range of economic and financial conditions during the life of the index, based on daily and monthly stock index prices and daily, monthly, and semi-annual stock returns. Why is an AR(1) model a reasonable benchmark of stock prices? Why do we have it? What should be our forecasting benchmarks? Let us briefly re-visit the history of stock price research and efficient markets. Do we find forecasting improvements from the Hendry-Castle-Doornik-Clements approach using robust forecasting methodologies and saturation variables in the prices of the index? Given that the DJIA fell over 15% during the first half of 2022, is this one of the worst six-month periods ever? What has happened to the Dow, historically, during such periods in the past with regards to six-month, one-year, and three-year-ahead stock returns? Is capitalism dead or doomed? We report statistically significant forecasting improvement from saturation and robust forecasting techniques during the 1896 -June 2022 period. We report forecasted stock returns for the next 6 months and three years that are bullish. In the King's English, June 30, 2022 was another excellent common stock buying opportunity and capitalism is not dead.

Suggested Citation

  • John B. Guerard & Dimitrios D. Thomakos & Foteini Kyriazi & Konstantinos Mamais, 2023. "On the Predictability of the DJIA and S&P500 Indices," Working Papers 2023-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    • Handle: RePEc:gwc:wpaper:2023-001
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    References listed on IDEAS

    as
    1. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1781-1788.
    2. Ashley, Richard, 2003. "Statistically significant forecasting improvements: how much out-of-sample data is likely necessary?," International Journal of Forecasting, Elsevier, vol. 19(2), pages 229-239.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    forecasting financial prices; forecasting financial returns; leading economic indicator; return volatility; rolling window averaging;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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