This is not an introductory module in finance. Tools and techniques that are basic for a quant career in finance, from mathematics, such as algebra and calculus will be taught on the module. Some prior computing skill in managing large amounts of data is necessary as well as a willingness to learn further computing skills in Maple, which will be demonstrated on the module.
A common feature of finance is the need to make good use of, and where possible the best use of limited resources; constrained optimization techniques, which are taught on the module, can often guide us in this need. Since concepts in probability are widely employed in finance to describe the inevitable uncertainty regarding the future, we examine its basic elements. It is a near universal truth that most of us dislike risk and prefer to avoid risk. We also find that we will avoid risks only if the price for avoiding that risk is acceptable. We study how expected utility theory helps us measure how averse we are to taking such risks.
We then proceed to apply these building blocks to examine several concepts: choice under uncertainty, maximizing returns and minimizing risk subject to constraints, mean-variance analysis and the capital asset pricing model. Finally, we show how real options can often help improve corporate investment decisions as compared to traditional approaches that employ the net present value rule.