Application of Brownian Motion in Risk Measurement of Bank Wealth Management Products

Abstract

Bank wealth management products have become popular choices for individual investors in recent years, but how to reliably assess the risk of these products remains a challenge for both investors and financial institutions. Geometric Brownian Motion, often referred to as GBM, can also be employed in the above area. The studies reviewed herein apply GBM to Chinese bank wealth products, long-term DJIA data, and 2020 Apple stock, jointly demonstrating its versatility in financial applications. Based on these studies, GBM appears to be a suitable tool for capturing the long-term trend of stock prices in a relatively stable market environment; however, it is not appropriate for sudden fluctuations or abnormal changes in market volatility. The paper will introduce the theory of GBM, present previous empirical results obtained in the aforementioned studies, and discuss the adjustments required for this model before it can be applied to bank wealth management products. In short, GBM is a simple starting point for risk assessment. However, the results obtained from it should be treated with caution, and if there are considerable differences between the current market conditions and those at the time of parameter setting, the reliability of the model will be significantly reduced.