A wise man once said that trading isn’t rocket science. Well… sometimes it is, literally.
To those outside of finance, what quantitative traders and hedge funds do may seem like rocket science. However, although what really goes on behind the scenes may not be too complex, sometimes, it really is rocket science.
So, today, we’ll be taking a dive into how Wall Street quants apply actual rocket science concepts to real-world trading.
Signals Are Everything
While Aerospace Engineering (rocket science) and Finance may not have much in common, the biggest similarity is that they both use tons of data. In both fields, most of this data is in the form of a time-series, where the data points are observations across time:
In both fields, the data is used to generate insights, but most importantly, it’s used to influence decision making. Making data-driven decisions are especially important when it comes to rockets, as errors in performance can lead to deadly and costly mistakes.
Because of this, engineers have worked tirelessly to create a framework for getting the absolute most of their data:
Digital Filtering
A digital filter is essentially just a way transforming data to make it more interpretable. This transformation is done to identify trends and better spot anomalies. To see why this is necessary, let’s look at how one dataset can look very different after filtering:
Original Data:
A common type of filtering is low-pass filtering. This essentially just smooths the data so that fast, rapid changes don’t alter the message of the data: