Yamato
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I trade CME futures mostly (forex, equity indexes, bonds, gold, oil), so it is not related to anything in Italy. I think Wednesdays are trend days, regular days. It follows all possible cycles. On the other days things are less certain. There are many patterns in the markets and I built my systems on them: all the patterns work out on Wednesdays. Overall almost no patterns work out on Tuesdays. Or maybe it's because my futures mostly are LONG only strategies. And on Wednesdays markets rise and on Tuesdays they fall. When I say "rise", I refer to stock indexes and EUR, and OIL, and GOLD and related things, because they are all correlated.
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Actually, one more thing. I had thought of a different way to implement this filter. Implement a filter not based on the results of all systems put together, but on each single system. However I discarded this for two reasons:
1) Because I've already implemented such a filter on each single system: if I ever found out through back-testing that a given day doesn't make any money or even worse loses money, then I excluded that day from trading, and that obviously is reflected in my forward-testing. And I am figuring that if, after implementing this filter on each single system, some days are still so much better than others (for the basket of all systems), this must mean not that this is coming from some specific systems (because those systems are already disabled on those days) but that it must be a general tendency.
2) Because, by analyzing the trades of every single system, I'd also have to use a sample of fewer trades (on average, 1/37th as big as the collective sample), and, as you pointed out, that makes my hypotheses less reliable. After all, my collective hypotheses are now based on 500 trades, which is quite a lot. If I try to verify the same questions ("which of the 10 time zones don't work?") on each of those 37 systems, then I won't get anywhere. I won't even have trades on all weekdays.
So for these reasons, it makes sense to reason on all systems taken together.
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Actually, one more thing. I had thought of a different way to implement this filter. Implement a filter not based on the results of all systems put together, but on each single system. However I discarded this for two reasons:
1) Because I've already implemented such a filter on each single system: if I ever found out through back-testing that a given day doesn't make any money or even worse loses money, then I excluded that day from trading, and that obviously is reflected in my forward-testing. And I am figuring that if, after implementing this filter on each single system, some days are still so much better than others (for the basket of all systems), this must mean not that this is coming from some specific systems (because those systems are already disabled on those days) but that it must be a general tendency.
2) Because, by analyzing the trades of every single system, I'd also have to use a sample of fewer trades (on average, 1/37th as big as the collective sample), and, as you pointed out, that makes my hypotheses less reliable. After all, my collective hypotheses are now based on 500 trades, which is quite a lot. If I try to verify the same questions ("which of the 10 time zones don't work?") on each of those 37 systems, then I won't get anywhere. I won't even have trades on all weekdays.
So for these reasons, it makes sense to reason on all systems taken together.
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