The purpose of this paper is to investigate the recent global economic downturn. Particularly, the study explores the utilization of the concept of Brownian motion in financial risk management in organizations in the USA.
The three assumptions, namely, independence, stationarity, and normal distribution that underlie the concept of Brownian motion are examined.
It is concluded that the widely used risk management strategies predicated on Brownian motion fail to provide a rational understanding of financial turmoil. Consequently, prescriptive insights are offered to aid the industry in developing an apposite mechanism for risk management.
This paper offers new and improved risk management strategies that need to be undertaken to augment our understanding and prediction of financial scenarios.
The paper is useful for managers in all financial organizations, which employ computer models using Brownian motions. Specifically, this study contends that static models are unsuitable and dynamic models are more useful for risk assessment.
The paper reveals the weaknesses of the key assumptions of the risk management models used in financial organizations, namely, normal distribution of stock market price fluctuations, statistical stationarity, and efficient market assumption. Valuable guidelines are provided for financial managers who either do not have the inclination or time to sift through the voluminous literature related to the risk management models and computer software designed on these models.
