Financial Analytics Course
An introduction to methods and tools useful in decision-making in the financial industry, including: macroeconomic event studies, analysis of term structures, Morningstar equity data, style analysis, credit card receivables, trading analytics, execution algorithms, etc.
Welcome to Financial Analytics. Thank you very much for joining us on this 10-week journey. We have a lot of things planned to do together. We’re going to be collaborating on projects and new ideas, all in the domain of finance. We will be covering a lot of areas, and I’ll be your guide through that. My name is Bill Foote. Just a little bit of background on who and what I am in this area of financial analytics. I’ve been doing this for some time. I started out as a credit analyst at a bank, originally because I needed a job, but it grew on me. And one of the things they found out I was very good at was figuring out why lending failed. I was actually a pretty bad lender on my own, but I could figure it out, and we used a lot of analytical tools and techniques that got us to the answers that were needed by decision-makers to say yea or nay to a credit, a new customer, a new client, a new counterparty. And it’s that workflow, that ethic, that has stayed with me for a number of years. I ended up going back to school getting a degree in economics, and around that time a bunch of people came up to me and said can you do this? And this was build a model—usually of something brand new—and so I learned how to do that, and I want to help you do that as well.
You will be coming up against some brand new areas, and we’re going to help you with tools, with thinking, with workflow, and with capability to make those things happen. What are those things? They are everything from figuring out revenue, to costs, to present value, what’s a bond with a particular statistical technique, but more importantly, throughout the course, we’re going to make this practical. We’re going to bring it right back down to earth with real data like oil prices or exchange rates or stock prices—real-life data that we can actually pull from open data sources using techniques in an environment that is well beyond Excel but consistent with Excel-based products called R. R is one of the analytical platforms of choice that have been growing by leaps and bounds and exponentially including a very, very large learner community, and that’s the real thing in a course like this. We’re going to develop our own community of learners. I’m one of the learners, and you’re all of the learners, and we’re going to learn from one another what we can contribute to this enterprise that we’re going to call financial analytics.
So, the course is going to cover several units, you see that throughout the syllabus, but broadly it’s three big steps. We’re going to play with R, and then eventually work with R, walk with it, run with it throughout the course. We’re also going to build some capability and statistics, probability as well as more finance, as we go through the course. Better than that, we’re going to be able to learn how to visualize everything, even in the end build an application to interact with all of the models that we have. This is, in the end, what a decision-maker, the ultimate consumer of our analysis, can use to think through a decision and even after making the decision monitor it and modify that decision, whether it’s an acquisition, a divestiture, a new hire, or just running the business as it is right now in the status quo.
So, at the end let’s accomplish together three things. One, let’s create a community of learning where we are teaching one another. Let’s build basic analytical capability with a software platform. Let’s build more financial statistics and probability capability that we might be able to use as we are attacking new problems. There’s a lot of stuff that we will not yet see that we will use these tools to help figure out how to work them. And then finally, we will learn how to communicate our results, and a very consistent reproducible and extensible approach to the people who need our results, to consumers of our analysis. So, welcome to the ride. I look forward to the journey. It’s going to be some harrowing chasms that we will span together and some lovely meadows that we will just breeze through. There will be all of that and everything in between. So welcome, and look forward to seeing you during our first set of sessions. Thank you.