Machine learning in trading: theory, models, practice and algo-trading - page 3111
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it's just a feature that says nothing about sustainability.
stability was tested on new data (10 years), but even this does not promise lambos and yachts. It is interesting to observe the model not in the tester, but how it works in real life.
In the top picture all the drawdowns are big, and around 06.01 the drawdown was about 7 quid out of eight profits. 13 quid on 10 000 for a month - this is nothing, you need to increase the lot and such an opportunity seems to be available, really in 100 times, which will lead to quite acceptable loading of the deposit. Then the drawdown will be several tens of per cent of the balance, which will lead to fixing the loss for the reason of "saving something at least".
On the top picture all drawdowns are big, and around 06.01 the drawdown was about 7 quid out of eight profits. 13 quid on 10 000 for a month is nothing, it is necessary to increase the lot and such an opportunity seems to be available, really in 100 times, which will lead to quite acceptable loading of the deposit. Then the drawdown will be several tens of per cent of the balance, which will lead to fixing the loss for the reason of "saving something at least".
Everyone has their own subjective understanding of risk. I am more interested in robust models and ways to obtain them.
I know people who trade with landings of 80% or drain at zero, but sometimes make thousands of %. I have made thousands without risks only on arbitrage, everything else always involves risks.I read the work of a very clever man Gabriel Okasa 2201 .12692.pdf
What struck me from the first page was that he started bolting a bicycle to a motorbike.
It was fun to watch some theory unfold in three-dimensional space.
The greatest creation was finished at page 30 and without a single example, real world application.
It was more fun with algo-trading and S.B.
I read the work of the smartest man Gabriel Okasa 2201 .12692.pdf
What struck me was that from the first page, he started bolting his bicycle to his motorbike.
It was fun to watch some theory unfold in three dimensions.
The greatest creation was finished on page 30 and without a single example, a real application.
Algorithm trading and S.B. was more fun.
.
Yesterday when I went to the loo, it struck me and I wrote this!
In lipstick on the glass. E=S*M*S .
E=C*M*C
Is the ternary formula in tensor form?
Teach! I won't teach you. You have to understand that I'm working against you all in the market.
Algo-trading is based on fake market data. It's simple. Close slightly coincides with the market, and High and Low. go on the minute chart much higher than the market. So, simply, we sell at 5 pips above Close[1]. We buy the same way. If below 4-5 pips below Close[1].
I am not going to discuss S.B. for moral reasons. I will write in matte and I will be banned early.
Teach! I won't teach you. You must realise that I'm working against all of you in the market.
Algo-trading is based on fake market data. It's simple. Close slightly coincides with the market, and High and Low. go on the minute chart much higher than the market. So, simply, we sell at 5 pips above Close[1]. We buy the same way. If it is below 4-5 pips below Close[1].
I am not going to discuss S.B. for moral reasons. I will write in matte and I will be banned early.
I tested the bot that I threw here on the 15th of May, a month has passed. With different sl and tp different results, but on average all on the growth.
What features were used? A full list would be desirable)