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People will tell you that you were just a lucky monkey. But you could have run your algorithm on past data, for hundreds or thousands of fake portfolios, to tell, statistically, what the odds of your algorithm being simply lucky are.

In early 2000s I wrote a machine learning algorithm that beat the S&P 100 with over 1 trillion to 1 odds against it being luck. It predicted a full trading day in advance. But that was all on paper at trading firms' puny costs; unlike you I couldn't beat retail costs. It's amazing that you could do that. For that reason alone I think it's highly likely that you were a skilled monkey.

Also like you, nobody in the industry was interested in my code, even after an industry magazine watched it for 3 months and found it gave "stellar" performance. The few people I was able to discuss it with told me point blank that it was impossible to do it skillfully (efficient market theory), so they assumed it was a hoax or the algorithm was just lucky.

What did you end up doing with your code? Would you be able to run it today with the low-cost broker APIs?

The code sits in one of my archive folders. I ran it for a few years, perhaps to 2004, and saw the market steadily becoming more efficient, lowering my results (like the OP did). It may well be that it no longer predicts skillfully or profitably. As I recall, to beat the market the costs had to be very low, like pennies per trade, with no bid/ask spread, which I understood to be possible for large trading firms.

OK, cool. There are some places that offer equity trading for ~$0.005/share, but that says nothing about overcoming bid/ask. Looks like the OP did that by throwing a bit of market making into the mix.

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