Shaun -nice summary. depending on the reader, that is a very encouraging list or a door slammer. i particularly resonate with trap 6 on a wet wednesday afternoonShaunWhite wrote: โMon Aug 31, 2020 3:56 pmWithout staring an entire book on the subject the #1 sin with any data is backfitting. If you give me data I guarantee I can find you a strategy that would have won. What I can't guarantee is that it'll win ever again. Keep some data to one side for out of sample tests.
#2 would be an understanding of sample size with regard to statistical significance.
#3 Do as much testing and modeling as possible offline. Trialing or refining using money is a really ineffective way to do it and the final stage not the first one.
#4. Be realistic. If manual trading isn't easy then building something that will make you rich while you sit in the garden is even harder.
#5 Fail fast. Only 1 idea in (10?) will have legs so don't get wedded to ideas.
#6 Strategies that have a higher frequency will give you a faster yes/no than infrequent ones. If you trade 200 dogs a day you'll get am answer faster than say trading premiership footy with 11 games a week.
#7 for longevity and scale consider the fundamentals of any market and the things least likely to change. Things like supply and demand, or the tendency for markets to overshoot on price corrections amongst othees. That way it stands a chance of working everywhere dogs/horses/win/place/football or anything. 10p on 1000 trades a day is clearly better than 10p on 100 trades. That's also going to insulate you from the problem of killing all the fish. A strategy might start to fail on one market type but could still work elsewhere. Picking trap 6 on Wednesdays certainly won't do that.
#8 same again. If you're going to spend a year working on the perfect strategy, you want it to last otherwise the return never exceeds the investment.
#9 Expect a cost. For any idea you need to think of it as a raffle ticket. How much you spend depends on how much chance you think you have and the size of the prize on offer. (see #5)
That'll do for now.
Truth is though that there's as many types of automated trader as there are manual traders. Some automate what they've learned manually and focus on niche situations a bot can sit and look for (and you might not even need data for that) and some are hft quants placing 100s of 000s of offers a day for whom tick data and an accurate simulator are a necessity.
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