Inside the Black Box: The Simple Truth About Quantitative Trading

8.1. THE IMPORTANCE OF DATA

It is difficult to overstate the importance of data, and it can be seen from many perspectives. First, data, as we know, are the inputs to quant trading systems. It turns out that the nature of the inputs to a system dictates what you can do with the system itself. For example, if you were handed a lot of lettuce, tomatoes, and cucumbers, it would be very difficult to build, say, a jet engine. Instead, you might decide that these inputs are most suited for making a salad. To make a jet engine, you more or less need jet engine parts, or at least materials that can handle high velocities and acceleration, high altitude and a wide range of temperatures. The same is true with quant systems. To the extent that you are given data that focus on macroeconomic activity, it is extremely difficult to build a useful model that doesn't somehow reflect macroeconomic concepts.

Frequently, many details of the model itself are driven by characteristics of the inputs that are used. Refining our example, imagine that you are given slow-moving macroeconomic data, such as quarterly U.S. GDP figures; furthermore, you receive them only a week after they are released to the public. In this situation, it is unlikely that you can build a very fast trading model that looks to hold positions for only a few minutes. Furthermore, note that the U.S. data you get might be useful for predicting bonds or currency relationships, but they might not be sufficient to build a helpful model ...