Financial Modeling: Building Analytical Tools

During my tenure on at JP Morgan, I created a number of tools using the Excel interface. They were coded in VBA and also used the Excel "cell" functionality. Unfortunately, due to rigid corporate intellectual property rights and regulatory controls at JP Morgan, I was not able to take my work with me when I left the firm. Thus, I do not have any of the actual Excel tools that I built. Below are examples of previous work from graduate school that represent the kind of modeling that I produced for JP Morgan using the Excel interface.

The project that I was most proud of was a very comprehensive analytical tool. It was a dashboard that provided all the financial data that a sales person working in foreign exchange could ever need. The tool updated daily with a click of a button pulling in live data from Bloomberg and an internal JPM data warehouse. This tool was useful for two reasons:

1. Working in Sales in the financial markets, a person can become inundated with information: news, research reports, Central Bank announcements, etc. 
2. With overnight centers in Tokyo, Sydney and London, financial markets are constantly moving

The tool provided up-to-date information of all overnight movements and consolidated data from every single financial market to give a sales person a macro-view of the world. It meticulously charted, for example, all interest rate curves and the most popular equity indices (like S&P).

Below is an example of modeling Brownian motion, a statistical function used to predict anything with a probabilistic outcome, like the price of an Option. 

Below is an example of modeling a normal distribution which can report expected outcomes that are likely to occur in a "normal, everyday state of the world." It is, for example, a way to model stock prices or volatility. 

Below is an example of modeling the price of a Reverse Knock-Out Option. For example, the price of the option will change over time and as the price of the underlying asset changes.