The Survival and Thriving of Market Entity - Case Study Example

The survival and thriving of any given market entity must adjust to the rapidly changing demands of customers as well as changing regulations and business risks. Businesses are in an ever-changing environment; thus, the businesses that intend to succeed in such environments must have vast information, or data at their disposal to thrive. The available data should be analyzed against market risks that might pose challenges to the business. The analysis of the same data requires perfect risk management skills; otherwise, wrong information or analysis of such information may lead to dire challenges for the business. Notably, all investments are marveled with investment risks that must be handled in a given way; otherwise, the affected business is headed to collapse. Risk management skills are learned. Therefore, such skills follow a given professional way since they often apply varied different models of problem-solving skills. For instance, the discretionary wealth hypothesis is a perfect model of comprehensive risk management comprising both interim shortfalls constraints and downside risks that are based on ln(w-c) utility. Therefore, every business risk scenario follows a different and distinct way of management or handling.
Jarrod Wilcox’s article, Risk management: Survival of the fittest has represented different scenarios that require different and distinct risk management skills to handle. The first case scenario, Option income funds, is where brokers owned and distrusted stocks or bonds. Moreover, they distributed premiums in form of income (Wilcox, 2004). These activities led to intense disappointment and withdrawal of investors following the gradual decline of opportunity and reduction of money flow. To build investor confidence in this case; the risk manager should apply Kelly’s rule of the stock portfolios. In this case, the investor should confront single-period return distributions. By calculating statistical parameters such as mean and variance and thereafter looking into kurtosis and skewness of the data in distribution data, it is possible to predict the data distribution. This process will enable managers to restrict or regulate rockers’ distribution habits thereby building investor confidence (Wilcox, 2004).

The Extreme CPPI case desires to protect the investor from the downside risk to reduce portfolio insurance. In other words, the case reflects a scenario where investors are only interested in business when profits are high. Despite timings, the investor may sometime stick at or near the floor never to escape to lose. The only way to build investor confidence is to use logarithmic returns in analyzing the business risks associated with the actions of the investor (Wilcox, 2004). This method allows the risk manager to predict when the return might be risky. However, it is worth stating that this model is more of a gamble than actual risk estimation or management.
The long-term capital management scenario relates to massive fund collapse. It also reflects a narrow academic view of risk management. Since everything, in this case, is not academically oriented, the best way to keep persons affected by this case in business is by applying Kelly’s coin-flipping rule that applies equally to investors and gamblers alike. Read More