Abstract

Stock transaction data typically present a time series that exhibits a somewhat confusing trend, making it difficult to issue any form of crisis warning. This study employs Fourier spectrum analysis to clearly show manic and irrational investors chasing prices. When clustering generates an enormous amount of unstable power, the result is a stock market collapsing into a danger area that can be taken as a warning signal. We thus take the Dow Jones Index as a typical stock market and employ daily data from 1994–2015. This study finds the investors’ purchasing power through certain thresholds, analyses the performance characteristics of the spectrum, and denotes when a stock market is in a most serious crisis stage and in a second most serious correction stage. The result of our study indicates that the warning signal accurately measures a stock market crash that can be applicable to the Dow Jones Index, Nasdaq Index, and Germany ADX Index and to the emerging markets of Bovespa Index (Brazil) and Shanghai Index (China). Furthermore, this study provides a quantitative reference concerning the depth of market crashes.

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