How I improved results on a scalping algo (mean reversion logic)

I run a scalping algo on NQ, (you can check my initial post there: ([Initial post](https://www.reddit.com/r/algotrading/comments/1r5al3o/finally_having_good_results_with_my_scalping_alog/)) First thing before comments on slippage and fees, it's all incorporated in backtests and has been running live for 2 months now with similar results. Just wanted to share 2 simple steps that considerably improved results. \- It's always complicated to have a run a profitable scalping algo for a long time (we'll see if/when it fails) So I created a second strategy with different settings to run in parallel, that adapt more quickly to volatility. Some days one works well, some other days the other one, and sometimes both give great results. I find it interesting to split capital in these 2 different settings to reduce overall drawdown and have more uncorrelated results. Attached pictures of both algos running with same logic but different settings \- Second improvement: Offer more room to each trade with the possibility to pyramid 2 entries per strategy. I work on 5 sec timeframe and market is never perfect, sometimes first entry is too early, and allowing a second entry slightly later if market drops a little more statistically improved results and reduced drawdown. So beside splitting capital on 2 different settings, I also split each position to allow a second entry on each settings. These 2 small steps considerably reduced drawdowns and improved overall results. Do you have other ideas / tips to improve a strategy?