The Mathematics of Financial Models: Solving Real-World Problems with Quantitative Methods

CHAPTER 10 Parting Thoughts

In putting this book together, I made a conscious attempt to assume that the reader is comfortable with a lot of the standard quantitative tools, like calculus, statistics, probability, numerical analysis, and so on. For those who do not have this background or need a review of such topics, I strongly encourage the consultation of the website accompanying this book–something that I will be updating regularly.

As I mentioned several times throughout this book, the use of quantitative methods in daily business and financial affairs is becoming increasingly prevalent as companies try to gain an extra edge against their competitors. Thus, the more a practitioner gets comfortable with quantitative tools (some of which were touched on in this book), the better the ability to quantify the risks associated with the impact of decisions, consumer behavior, revenues, profits, and so on. While the existence of readily available mathematical/statistical packages like Matlab and @Risk give a practitioner the necessary ammunition to tackle problems discussed without having to create the underlying infrastructure, it is important to understand that these tools are nothing but tools. Hence, a practitioner still needs to understand the assumptions, constraints, and models deployed in the respective businesses so as to be able to couch the practical problem in the context of an analytical problem (often using simplifying assumptions), which can then be solved using ...