Reaction Function for Financial Market Reacting to Events or Information

Bo Li () and Guangle Du ()
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Bo Li: Wuhan City Polytechnic
Guangle Du: University of Chinese Academy of Sciences

Annals of Data Science, 2024, vol. 11, issue 4, No 7, 1265-1290

Abstract: Abstract Observations indicate that the distributions of stock returns in financial markets usually do not conform to normal distributions, but rather exhibit characteristics of high peaks, fat tails and biases. In this work, we assume that the effects of events or information on prices obey normal distribution, while financial markets often overreact or underreact to events or information, resulting in non normal distributions of stock returns. Based on the above assumptions, we for the first time propose a reaction function for a financial market reacting to events or information, and a model based on it to describe the distribution of real stock returns. Our analysis of the returns of China Securities Index 300 (CSI 300), the Standard & Poor’s 500 Index (SPX or S &P 500) and the Nikkei 225 Index (N225) at different time scales shows that financial markets often underreact to events or information with minor impacts, overreact to events or information with relatively significant impacts, and react slightly stronger to positive events or information than to negative ones. In addition, differences in financial markets and time scales of returns can also affect the shapes of the reaction functions.

Keywords: Stock returns; Normal distribution; Overreaction; Investor behavior (search for similar items in EconPapers)
JEL-codes: C02 G02 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s40745-024-00565-w

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