S&P 500 trading pit at the Chicago Board of Options Exchange

Long before I worked on distributed systems, I spent my summers in college working at an options trading desk in Chicago. I ran different models, proposed different strategies, and sent down different reports to the traders on the floor of the S&P 500 trading pit. These traders used pricing models like Black-Scholes or Binomial Options Pricing Model to find arbitrage opportunities. It was a game of risk. But the lessons I learned on the trading floor had wider usefulness — a group of economists has applied options pricing models to real-world decision-making.

First, a crash course in options. In finance, an option is the right, but not the obligation to buy or sell a stock at a certain price until a certain date. It is a derivative of the underlying stock. There are theoretical models that value options. You can look up the partial differential equation that describes the Black-Scholes model, one of the most well-known models, but most traders just talk about "the Greeks".

The Greeks are the different variables that go into options pricing, named after the Greek symbols used in the equation.

But what does this have to do with the real world?

A real option is the right, but not the obligation to undertake a certain decision.

In business, real options are mostly applied to capital budgeting decisions — should the business invest in a new project, wait a year, or abandon an existing project? It incorporates flexibility into a classic net present value (NPV) decision-making process.

We're doing this in our heads all the time. When I was deciding to go to graduate school, I had real options that could be valued: stay at my job, start a company, or go back to school (I went).

While you can't necessarily use the pricing models to exactly determine the value of real-world options, you can still use it as a conceptual model. Here are some questions you can ask when confronted with a decision: