An explanation for the distribution characteristics of stock returns

TL;DR

This paper explains the non-normal distribution of stock returns by modeling market reactions to information, highlighting overreaction, underreaction, and asymmetry in responses across different markets and time scales.

Contribution

It introduces a reaction function model that accounts for market overreaction and underreaction, providing a new explanation for return distribution characteristics.

Findings

Markets tend to underreact to minor events.

Markets overreact to significant events.

Positive information elicits slightly stronger reactions.

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 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.