The BS model is a model used to determine price variation over time such as stock options. The utilization of confidence intervals to determine if the BS model was accurate was concluded constructing a 95 percent confidence interval for the call option, we found in general that significantly less than 95 percent of the observations fall within the relevant range. The theory of incorporating a confidence interval into the BS model developed a way for investors to identify what options we better to purchase.
(Levy & Byun, 1987) In a case study to estimate the confidence in advertising the authors of Estimating Confidence Bounds for Advertising Effect Duration Intervals studied the dynamic effects of current and past advertising on current and future sales utilizing confidence intervals. The study identified how long an advertisement should be displayed depending on the duration interval and the confidence interval that helped managers arrive at proper decisions.
Using confidence intervals in this situation enabled leaders to make an informed decision. (Franses & Vroomen, 2006) Through the use of surveys in case study Mortality rate and confidence interval estimation in humanitarian emergencies they were able to incorporate confidence intervals. They used confidence intervals to determine the mortality confidence level from surveys in devastated areas. The authors approach enables health officials to identify confidence levels from survey areas to be better prepared for future emergencies.
(Sullivan, Hossain, & Woodruff, 2010) There is an infinite amount of ways to use confidence intervals in any professional culture. The three examples are only a small sample of what can actually be done to better understand present or past issues. The use of confidence levels can help any leader or manager make decisions that foster an environment of growth. References Franses, P. H. , & Vroomen, B. (2006). Estimating Confidence Bounds for
Advertising Effect Duration Intervals. Journal of Advertising , 33-37. Levy, H. , & Byun, Y. H. (1987). An Empirical Test of the Black-Scholes Option Pricing Model and the Implies Variance: A Confidence Interval Approach. Journal of Accounting, Auditing & Finance , 355-368. Sullivan, K. , Hossain, S. M. , & Woodruff, B. A. (2010). Mortalizty rate and confidence interval estimation in humanitarian emergencies. Disasters , 164-175.