An exotic long-term pattern in stock price dynamics.

Abstract

BACKGROUND: To accurately predict the movement of stock prices is always of both academic importance and practical value. So far, a lot of research has been reported to help understand the behavior of stock prices. However, some of the existing theories tend to render us the belief that the time series of stock prices are unpredictable on a long-term timescale. The question arises whether the long-term predictability exists in stock price dynamics. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we analyze the price reversals in the US stock market and the Chinese stock market on the basis of a renormalization method. The price reversals are divided into two types: retracements (the downward trends after upward trends) and rebounds (the upward trends after downward trends), of which the intensities are described by dimensionless quantities, R(t) and R(b), respectively. We reveal that for both mature and emerging markets, the distribution of either retracements R(t) or rebounds R(b) shows two characteristic values, 0.335 and 0.665, both of which are robust over the long term. CONCLUSIONS/SIGNIFICANCE: The methodology presented here provides a way to quantify the stock price reversals. Our findings strongly support the existence of the long-term predictability in stock price dynamics, and may offer a hint on how to predict the long-term movement of stock prices.