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An Early Indicator for Anomalous Stock Market Performance

Author

Listed:
  • Marlon Fritz

    (Paderborn University)

  • Thomas Gries

    (Paderborn University)

  • Lukas Wiechers

    (Paderborn University)

Abstract
We propose an indicator for detecting anomalous stock market valuation in real time such that market participants receive timely signals so as to be able to take stabilizing action. Unlike existing approaches, our anomaly indicator introduces three methodological novelties. First, we use an endogenous, purely data-driven, nonparametric trend identification method to separate long-term market movements from more short-term ones. Second, we apply SETAR models that allow for asymmetric expansions and contractions around the long-term trend and find systematic stock price cycles. Third, we implement these findings in our indicator and conduct real time market forecasts, which have so far been neglected in the literature. Simulations of our indicator using monthly S&P 500 stock data from 1970 to 2019 show that short-term anomalous market movements can be identified in real time up to one year ahead. We predict all major anomalies, including the 1987 Bubble and the initial phase of the Financial Crisis that began in 2007. In total, our anomaly indicator identifies more than 80% of all — even minor — anomalous episodes. Thus, smoothing market exaggerations through early signaling seems possible.

Suggested Citation

  • Marlon Fritz & Thomas Gries & Lukas Wiechers, 2022. "An Early Indicator for Anomalous Stock Market Performance," Working Papers CIE 153, Paderborn University, CIE Center for International Economics.
    • Handle: RePEc:pdn:ciepap:153
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    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/ciepap/WP153.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Financial Indicator; Nonparametric Trend; Stock Price Cycle; Stock Pricing; Valuation Ratio;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises

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