Abstract
A statistical method is proposed for detecting stock market bubbles that occur when speculative funds concentrate on a small set of stocks. The bubble is defined by stock price diverging from the fundamentals. A firm’s financial standing is certainly a key fundamental attribute of that firm. The law of one price would dictate that firms of similar financial standing share similar fundamentals. We investigate the variation in market capitalization normalized by fundamentals that is estimated by Lasso regression of a firm’s financial standing. The market capitalization distribution has a substantially heavier upper tail during bubble periods, namely, the market capitalization gap opens up in a small subset of firms with similar fundamentals. This phenomenon suggests that speculative funds concentrate in this subset. We demonstrated that this phenomenon could have been used to detect the dot-com bubble of 1998–2000 in different stock exchanges.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Numbers 18H05217, 16H05904 and the Center of Advanced Research in Finance (CARF), University of Tokyo.
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Mizuno, T., Ohnishi, T., Watanabe, T. (2020). Detecting Stock Market Bubbles Based on the Cross-Sectional Dispersion of Stock Prices. In: Sato, H., Iwanaga, S., Ishii, A. (eds) Proceedings of the 23rd Asia Pacific Symposium on Intelligent and Evolutionary Systems. IES 2019. Proceedings in Adaptation, Learning and Optimization, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-37442-6_18
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DOI: https://doi.org/10.1007/978-3-030-37442-6_18
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