An Early Indicator for Anomalous Stock Market Performance

Marlon Fritz (), Thomas Gries and Lukas Wiechers ()
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Marlon Fritz: Paderborn University
Lukas Wiechers: Paderborn University

No 153, Working Papers CIE from Paderborn University, CIE Center for International Economics

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.

Keywords: Financial Indicator; Nonparametric Trend; Stock Price Cycle; Stock Pricing; Valuation Ratio (search for similar items in EconPapers)
JEL-codes: C14 C22 E44 G01 (search for similar items in EconPapers)
Date: 2022-12
New Economics Papers: this item is included in nep-fmk
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