The field of actuarial science is by no means a new discipline. However, the educational content for aspiring actuaries must continue to develop alongside the advancements in the profession. The increasing prevalence of data analysis in the field of actuarial science begs for a change in the curriculum and the Society of Actuaries is responding. The question that naturally arises concerns how data analytics can be integrated into the already rigorous educational standards of the actuarial profession. To examine this idea it is necessary to research what data analytics is to an actuary and how colleges and universities have created actuarial science programs. These topics can facilitate a solution to how actuarial programs can adapt to changes in the curriculum. A literary review and analysis will provide insight to better actuarial education here at Murray State University and in the profession as a whole.

Financial options are contracts often used as tools for hedging a position on fluctuating stock prices. There is no closed form solution for the pricing of these options; however, there exist certain numerical techniques to price them. For this paper, I implemented binomial and trinomial probability models to price a total of twenty-four different types of options, using MATLAB to code the pricing algorithms. The probability-based pricing system starts with the creation of a lattice for the tree of possible stock prices, then works recursively from the far end of the tree (the end of a user-specified time period) to reach a single price value at the time of the option’s purchase. There was also an investigation into simplicity (measured in time taken for the computer to reach the option price) versus accuracy (measured in difference in price from some benchmark, more accurate value) as the number of steps of the stock tree increased.