Adrian Reid explains designing trading systems using technical analysis and time-series data. He emphasizes creating clear buy/sell rules, testing those rules on historical data to assess risks (drawdowns, loss frequency and size), and using results to size positions and allocate capital.
The rules are typically for most systems, they're based on technical analysis. You can use fundamental data if you have the time series, because part of the first challenge is having rules so you know exactly when to buy and exactly when to sell. The second challenge is being able to test those rules over history to make sure that you know what good things, what bad things could happen, how big the dips could be, how many losses you could have, how big the losses are, all the risks you have to manage, we need to be able to test them. So we design our systems with rules that use data that we have time series data for. So we have open, high, low, close, and volume for every stock. For every day since the stock was listed, we have that data. You can get interest rate data every single day. You can get stock market index data every single day. You can get volatility. You can get some fundamental information. So anything you have in time series, you could incorporate into your system, if it gives you an edge, and test it and see if it helps. And all what we're trying to do is build confidence that the system will keep, you know, will keep working, build confidence that we understand what the risks are so that we can position size correctly and allocate capital correctly. And all of these things we can do, because we can test it analytically on historical data. It's.
