Machine learning in trading: theory, models, practice and algo-trading - page 3228
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They show OOS on 20 sets taken next to different peaks of the target function. This means that if there are 19 false (fit) peaks and one positive (pattern) peak, we will see it immediately. And we won't care about all other results.
Answered this question here.
No offence, but I just don't understand the attempt of a purely theoretical person to influence the decisions of an expert practitioner. Even at the zero stage of selecting initial data (quotes) I disagree with you fundamentally.
MO researchers, as a rule, use a hypothesis that there is a pattern in the initial series, which can be traded in plus. This is a hypothesis, not confirmed by anything.
And then I give out a series that has a pattern 99.9% of the time. I expect that the most advanced generation methods should not break it at all.
If you can create such a generation with GARCH, honour and praise.
Don't generalise your ignorance of confirmation.
This is exactly why you are not responding substantively: the IO is looking for patterns that predict the future, not just patterns.
Theoretical question.
Condition.
As a result, there is a certain history, which definitely has a regularity. This history can be of any required length.
Question.
Theoretical question.
Condition.
As a result, there is a certain history, which definitely has a regularity. This history can be of any required length.
Question.
Random Forest also generates many trees (each tree is given several random fiches) and then averages the result of all trees. If there are patterns in most of the fiches, the result will be good and stable. If there is one common pattern in all fiches.
If there are only 1-3 good fiches, then they will be averaged with trees with only noisy fiches, and the result will be noisy. In trading, all chips can be considered noise.
If you have only 1000 trades out of 6 million ticks (activated by some condition of yours), that is 0.017% of all data. MO will never find such a thing, it will find something common and try to trade on 50% of ticks, you can tighten the conditions and trade 1% (only on the best leaves), but you have even less.
Basically, each leaf is a separate strategy like yours. But a tree can be divided into 100 leaves or 1000 or 10000.... And it trades all these 10000 strategies at the same time (or rather the ones you choose, you can for example only trade leaves with 90% or even 99% probability of winning on Traine, but on OOS such a clean (maybe retrained) leaf does not guarantee anything).
If you have only 1000 trades out of 6 million ticks (activated by some condition of yours), it is 0.017% of all data. MO will never find such a thing, it will find something common and try to trade on 50% of ticks, you can tighten the conditions and trade 1% (only on the best leaves), but you have even less.
1000 trades in six months is very active trading. If it's not enough, then what are you looking for on MO when you feed in many years? Duration distribution cited.
Forum on trading, automated trading systems and testing trading strategies
Machine learning in trading: theory, models, practice and algo trading
fxsaber, 2023.09.10 07:15 AM
Honestly, very rarely seen more trades. And not significant - times two only. But there on the edge of stability.
Question.
That's a very strange question...
And if you think about it logically?
If there are infinite computational possibilities, then all the money will flow into these computational wallets.
Who's going to let them if other computational powers want to take it away from the first.
Think about it at your leisure. It's good to use logic.))
Forum on trading, automated trading systems and testing trading strategies
Machine learning in trading: theory, models, practice and algorithmic trading
Renat Fatkhullin , 2023.09.10 10:44
We plan to launch another championship aimed at promoting neural networks:1000 trades in six months is a very active trade. If that is not enough, then what are you looking for on MO when you feed in many years? The distribution of duration was given.
To be honest, very rarely have I seen more trades. And not significant - times two only. But there on the edge of stability.
Well, manually I did 100 trades a day on 8 instruments, probably out of boredom and adrenaline)). On 1 instrument I probably did 10 a day on average - it will turn out to be about the same as yours. I averaged and of course I lost. That's why I switched to algo-trading, and then to MO. More precisely algo-testing, because no model interested me to put money on it.
I just make a forecast for each bar, now it's M5 (288 bars per day) and if the forecast is good - you can trade. If we take the probability of success 0.5, then on average 144 trades per day. If 0.9, then less, if 0.99, it can stand idle for a year and then actively trade for a week (White Swan Catcher).
By analogy with bars, you can forecast every tick, and there are 6 million of them - that's why I said "only 1000". On ticks you should probably not predict every line/tick, but filter them in some way. You did it with your manually detected algorithm and got 6-7 trades per day.
And if you think about it logically?
If there is limitless computing power, then all the money will flow into these computing wallets.
Who will let them, if other computational capabilities want to take it away from the first.
Think about it at your leisure. It's useful to apply logic.))