Is it possible to create a system which will turn itself off, i.e. stop giving trade signals, when those signals are more likely to fail, without any intervention on your part or any attempt to use an external filter to detect market shifts?
How would you even know if the feature was working, other than by decreased frequency of signals? Would something like this be a case of trying to "prove a negative" by concluding that if your system is giving you fewer signals, it means that it stopped giving you signals which would have failed.
Anyone who's consciously tried to achieve this, please chime in with your results.
I've been going through a period with a major decrease in trade signals, but the signals I've been getting still have a nice profit factor, so it's not as if the system has started to fail. Is it possible that this system has this feature built-in without me explicitly designing for it?
Is it possible to create a system which will turn itself off, i.e. stop giving trade signals, when those signals are more likely to fail, without any intervention on your part or any attempt to use an external filter to detect market shifts?
How would you even know if the feature was working, other than by decreased frequency of signals? Would something like this be a case of trying to "prove a negative" by concluding that if your system is giving you fewer signals, it means that it stopped giving you signals which would have failed.
Anyone who's consciously tried to achieve this, please chime in with your results.
I've been going through a period with a major decrease in trade signals, but the signals I've been getting still have a nice profit factor, so it's not as if the system has started to fail. Is it possible that this system has this feature built-in without me explicitly designing for it?
Unless you have code that does this, what you're asking is dependent on what your criteria for unfavorable conditions is, and if you know already, it can be coded.
Seems obtuse and abstract. Everything you code is part of your system, and if you know what your conditions are you can backtest them to know if they improve your results.
We have larger positions in NQ sometimes when two of our systems agree. 1 system trades 2 NQ, another 1 NQ, but when they agree we'd have 2 NQ and 1 NQ as normal and do 2 extra NQ. After backtesting that there was the better payoff of 0.01% more drawdown for 80+% higher returns. Not really a turn off.
Backtesting any changes will let you know for sure. Without backtesting, though, this is not possible to answer. You might do that occassionally around news events such as FOMC announcements or GDP or unemployment reports, identify the dates of those and see if abstaining from action would have been prudent. Other than news events though, you should be able to code and analyze what makes you better off in terms of expectancy. The manual ommission of those dates can also help you improve your results by being more selective about market conditions.
I think one I follow is never trade the friday before a 3 day weekend, especially if it's an early close. It just isn't worth it.
There is a rather simple trick which works for most (not all) strategies:
You need a platform that is able to simulate trades not only in a backtest, but also in real time. Run your system and build a Moving Average of your equity curve. When the equity falls below the Moving Average, switch from trading to simulation, until the simulated equity curve crosses its Moving Average again from below. Then resume trading. This will, with some lag, eliminate unprofitable periods from your strategy. When you use a lowpass filter instead of an MA, you can minimize the lag.
This method works because the equity curve normally reflects quite well the adaption of your system to the market.
There is a rather simple trick which works for most (not all) strategies:
You need a platform that is able to simulate trades not only in a backtest, but also in real time. Run your system and build a Moving Average of your equity curve. When the equity falls below the Moving Average, switch from trading to simulation, until the simulated equity curve crosses its Moving Average again from below. Then resume trading. This will, with some lag, eliminate unprofitable periods from your strategy. When you use a lowpass filter instead of an MA, you can minimize the lag.
This method works because the equity curve normally reflects quite well the adaption of your system to the market.
My personal experience with such "switches" is that they can "whipsaw" you badly ... they get you out after a loss, then you miss the winners, and then you get back in again in time for more losses! ... my own conclusion has been that it's best simply to keep trading the strategy, and not try to advance pick the trades that will be winners versus losers. If you're comfortable the strategy is still working, that is ...
My personal experience with such "switches" is that they can "whipsaw" you badly ... they get you out after a loss, then you miss the winners, and then you get back in again in time for more losses! ... my own conclusion has been that it's best simply to keep trading the strategy, and not try to advance pick the trades that will be winners versus losers. If you're comfortable the strategy is still working, that is ...
It depends on the strategy, or rather, on the "trendiness" of its equity curve. When the market situation does not change in a chaotic way, such a switch can often reduce losses. A typical example where some switch algorithm would work well is this strategy:
There is a rather simple trick which works for most (not all) strategies:
You need a platform that is able to simulate trades not only in a backtest, but also in real time. Run your system and build a Moving Average of your equity curve. When the equity falls below the Moving Average, switch from trading to simulation, until the simulated equity curve crosses its Moving Average again from below. Then resume trading. This will, with some lag, eliminate unprofitable periods from your strategy. When you use a lowpass filter instead of an MA, you can minimize the lag.
This method works because the equity curve normally reflects quite well the adaption of your system to the market.
