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Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading, + Website by Kevin J. Davey

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CHAPTER 11 Let’s Talk about Data

With the entry, exit, market, and time frame/bar length decided, now comes one of the most important, most underappreciated, yet least understood aspects of testing: market data. People take data for granted, and that can be a big mistake. I’ve seen huge differences in strategy performance just due to different data sources. I’ll make the grand assumption that your data are clean, without bad data points, missing data, and so on. Of course, that is not the case at all, practically regardless of vendor. But most people understand that data may have errors; what most do not understand is the impact behind the answers to these data-related questions:

  • How much data should you use?
  • Should you use pit data or electronic data?
  • Should you use continuous contract data?
  • Did the advent of electronic trading impact market data?
  • How do you test with foreign exchange (forex) data?

Now, before you start testing, is the time to look at all these issues, and make some decisions. To go back and retest with different a data structure typically means you will be using tainted data, and that is not good.

images How Much?

If you are like me, you’ve probably done the “eyeball” test more than a few times. You look at a chart and, knowing your entry and exit criteria, perform a quick test of the past few days or weeks of data. After a few trades, if you see a lot of profit, ...

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