10-10-2018, 04:28 AM
@danibeni81,
Awesome explanation of your findings and extremely detailed work in your attempt to truly understand how this strategy work!
It's always good to hear people astounded by how well this strategy performs in backtests and then tried to truly understand this strategy by going into extensive testing to confirm the ideas.
Having said that, backtesting doesn't predict future performance, but lack of an actual working crystal ball to see the future, daytraders/swing traders/speculators in general look to the past (comparing the current bear market to 2014 post Mt. Gox time frame) for guidance. Backtesting is similar in that if the trend plays out in similar fashion, you should make better than market gains.
I haven't done much backtesting with this strat for some time, but the question of win rate % vs. gains (using the backtest tool by xFFFFF, doesn't work with Gekko 0.6x) was always a question that I never quite figured out. I couldn't find parameters that had high win rate (above 75%) and also made massive gains. I don't have a definitive answer but having worked with this strategy for quite some time, my general sense is this strategy when bias for gains is gambling every time it goes long by taking risky position that loses more often but wins big once in a while. When bias for high win rate %, the strat misses out on the losses but also misses out on the big gains.
Win rate isn't important if the strat performs exactly like it does in backtest, but we already know that's not possible as backtests can't predict the future absolutely. It also is extremely frustrating to see consecutive losing trades or 3 losing trades totaling 10% with a 1% gain stuck in between during live trading.
But back to your analysis, You have the right idea to backtest pure bull trends and pure bear trends. I believe that is closer to how expert day traders utilizes historical information to make their trades. You can also add in sideways trend to see if you can find profitable parameters for that as well.
One other thing you can do is instead of running backtest on the entire bull trend or bear trend period, just run it for 75% of the period first to find the optimal parameters. Then use those parameters on the remaining 25% to see if they actually work. Then try to find the optimal parameters for the remaining 25% and see if they differ from the 75% significantly. My guess (just based on my experience with market overall) is, for bull trends, the optimal parameters from the 75% won't perform as well compare to the 25%, because the latter part is usually when the market gets extremely volatile and RSI move in extremes so the RSI highs won't capture the best gains. I want to say it's the inverse for bear trends but I honestly don't know.
Awesome explanation of your findings and extremely detailed work in your attempt to truly understand how this strategy work!
It's always good to hear people astounded by how well this strategy performs in backtests and then tried to truly understand this strategy by going into extensive testing to confirm the ideas.
Having said that, backtesting doesn't predict future performance, but lack of an actual working crystal ball to see the future, daytraders/swing traders/speculators in general look to the past (comparing the current bear market to 2014 post Mt. Gox time frame) for guidance. Backtesting is similar in that if the trend plays out in similar fashion, you should make better than market gains.
I haven't done much backtesting with this strat for some time, but the question of win rate % vs. gains (using the backtest tool by xFFFFF, doesn't work with Gekko 0.6x) was always a question that I never quite figured out. I couldn't find parameters that had high win rate (above 75%) and also made massive gains. I don't have a definitive answer but having worked with this strategy for quite some time, my general sense is this strategy when bias for gains is gambling every time it goes long by taking risky position that loses more often but wins big once in a while. When bias for high win rate %, the strat misses out on the losses but also misses out on the big gains.
Win rate isn't important if the strat performs exactly like it does in backtest, but we already know that's not possible as backtests can't predict the future absolutely. It also is extremely frustrating to see consecutive losing trades or 3 losing trades totaling 10% with a 1% gain stuck in between during live trading.
But back to your analysis, You have the right idea to backtest pure bull trends and pure bear trends. I believe that is closer to how expert day traders utilizes historical information to make their trades. You can also add in sideways trend to see if you can find profitable parameters for that as well.
One other thing you can do is instead of running backtest on the entire bull trend or bear trend period, just run it for 75% of the period first to find the optimal parameters. Then use those parameters on the remaining 25% to see if they actually work. Then try to find the optimal parameters for the remaining 25% and see if they differ from the 75% significantly. My guess (just based on my experience with market overall) is, for bull trends, the optimal parameters from the 75% won't perform as well compare to the 25%, because the latter part is usually when the market gets extremely volatile and RSI move in extremes so the RSI highs won't capture the best gains. I want to say it's the inverse for bear trends but I honestly don't know.
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