A groundbreaking new study has introduced a quantum model that sheds light on the dynamics of stock market fluctuations during periods of economic uncertainty. The research, conducted by an international team of experts from Korea, Canada, and the UK, utilizes principles from quantum mechanics to explain the power law distribution and herding behavior observed in stock returns. By bridging the gap between macroeconomic factors and investor mimetic behavior, this study provides valuable insights into the origins and consequences of stock market anomalies.
Quantum mechanics, a branch of physics that focuses on the behavior of subatomic particles, serves as the basis for the researchers’ model. Dr. Kwangwon Ahn, associate professor of Industrial Engineering at Yonsei University and the study’s lead author, explains that stock returns can be understood as a result of external market forces that pull short-term fluctuations toward long-term equilibrium. By incorporating a diffusion coefficient to capture stock return volatility and applying the Schrödinger equation, which is central to quantum mechanics, the team was able to identify a power law distribution in the tail of stock returns.
The power law distribution indicates that extreme events, such as stock market crashes, are more likely to occur compared to what would be expected from a normal distribution. Importantly, the researchers also discovered that the power law exponent, which measures the fatness of the tail, is inversely related to both the diffusion coefficient and the external potential. This suggests that higher volatility and slower reversion to equilibrium contribute to increased herding behavior among investors during times of uncertainty and information asymmetry.
To validate their model, the researchers analyzed empirical data from the US stock market. They used the growth rate of gross domestic product (GDP) as a proxy for business cycles and forecaster uncertainty as a measure of economic uncertainty. The findings confirmed their theoretical predictions, revealing a positive association between the power law exponent and the GDP growth rate, as well as a negative association with forecaster uncertainty. The study also highlighted economic uncertainty as the intermediary that connects business cycles to herding behavior in stock returns.
Dr. Daniel Sungyeon Kim, associate professor of Finance at Chung-Ang University and the corresponding author, emphasizes the significance of this study’s outcomes. He believes that quantum mechanics can provide valuable tools for understanding the complexities of the stock market and hopes that this interdisciplinary approach will inspire further research in the field. Ultimately, the study’s insights into the relationship between economic uncertainty and herding behavior can have meaningful implications for investors and policymakers alike.