Expecting signal correction based on past performance and current sample
I don't understand your question.
Irrespective of past, present or future results, the risk you take should be the same based on the money management method you have defined for the strategy.
If for example you have defined it to be a 1% fractional risk for position sizing, then you continue to do so irrespectively.
...
Is it wise to "shift" the risk down or avoid trading in expectation of those losses that have not appeared ? (again for the example we are messing with our R:R)
Thank you
Is it wise? In my experience, no. What i found is that all (z-score/news filters/recovery factor deviations etc) methods to reduce draw down also reduce profit either by reducing volume or halt/pause trading. Your mileage may very because my strategy is not yours.
I don't understand your question.
Irrespective of past, present or future results, the risk you take should be the same based on the money management method you have defined for the strategy.
If for example you have defined it to be a 1% fractional risk for position sizing, then you continue to do so irrespectively.
You mean the loss $ and win $ should be the same ?
The question is inspired by football betting . There is an idea there that a team that always wins will eventually lose and vice versa . Now in football i think its stupid to expect it for a winning team but makes sense to expect it for a losing side because its something they want to change .
Anyway ,back to forex , the question is (the idea becomes) : with a known hit rate of strategy F , every passing trade that is taken live and is a win increases the chances of the next trade being a loss ?
...
Anyway ,back to forex , the question is (the idea becomes) : with a known hit rate of strategy F , every passing trade that is taken live and is a win increases the chances of the next trade being a loss ?
Z-Score allows us to estimate how often profitable trades are alternated with losing ones.
Z for a trading system is calculated by the following formula:
Z=(N*(R-0.5)-P)/((P*(P-N))/(N-1))^(1/2) where: |
Let's assume strategy F
Besides the risk reward ratio , it has a historical hit rate of 95% (this is an assumed strategy because the number closer to 100% is easier to convey my question)
We assume everything is symmetrical with past and present trade execution for the example (meaning you read the real spread and real delays slippages etc in the backtest)
We start trading it and we hit a winning streak of 100 trades (for the example) , so in the subset of these trades taken live we are at 100% win rate but we know there will be losers since we have analyzed a bigger sample in the backtest .
Is it wise to "shift" the risk down or avoid trading in expectation of those losses that have not appeared ? (again for the example we are messing with our R:R)
Thank you
No! I'm saying that the risk you take should be the same irrespective of your expectation of a win or a loss for the trade.
That is the whole purpose of a proper money management method, be it fixed risk, fixed fractional risk, or whatever money management method you decided to use for your strategy.
Could there be a z_static and z_evolve though ? And when z_evolve deviates from z_static you block x amount of trades , which also depends on the size of the series i guess .
And then the problem is where do you start z_evolve in the beggining and where after a block .
So at first z_static + z_evolve are equal , then on the conclusion of a trade z_evolve is recalculated from the second historic trade to maintain the same "window" size and so on.
But i gotta do a test and see the numbers otherwise i'm probably not aware of what i'm talking about .
Thanks for the formula
The probability of an electrical appliance breaking down has nothing to do with how long it has been on.
Exactly , that is why new and used have the same value in the market .
Could there be a z_static and z_evolve though ? And when z_evolve deviates from z_static you block x amount of trades , which also depends on the size of the series i guess .
And then the problem is where do you start z_evolve in the beggining and where after a block .
So at first z_static + z_evolve are equal , then on the conclusion of a trade z_evolve is recalculated from the second historic trade to maintain the same "window" size and so on.
But i gotta do a test and see the numbers otherwise i'm probably not aware of what i'm talking about .
Thanks for the formula
Good questions and quite a few extra veriables you are introducing to the system. IMO all should be kept to the essential minimum. And like i wrote, in my case it reduces drawdown but also profit, so not worth the while.
Essentially i am saying the same as Fernando
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Expecting signal correction based on past performance and current sample
Fernando Carreiro, 2023.02.26 14:19
No! I'm saying that the risk you take should be the same irrespective of your expectation of a win or a loss for the trade.
That is the whole purpose of a proper money management method, be it fixed risk, fixed fractional risk, or whatever money management method you decided to use for your strategy.
Good questions and quite a few extra veriables you are introducing to the system. IMO all should be kept to the essential minimum. And like i wrote, in my case it reduces drawdown but also profit, so not worth the while.
Essentially i am saying the same as Fernando
Yeah . i'll try to build a test code , just for fun i'll likely end up at the same conclusion as you guys
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Let's assume strategy F
Besides the risk reward ratio , it has a historical hit rate of 95% (this is an assumed strategy because the number closer to 100% is easier to convey my question)
We assume everything is symmetrical with past and present trade execution for the example (meaning you read the real spread and real delays slippages etc in the backtest)
We start trading it and we hit a winning streak of 100 trades (for the example) , so in the subset of these trades taken live we are at 100% win rate but we know there will be losers since we have analyzed a bigger sample in the backtest .
Is it wise to "shift" the risk down or avoid trading in expectation of those losses that have not appeared ? (again for the example we are messing with our R:R)
Thank you