AriaS
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Hi everyone,
Thought I should share the process and concept of my trading. Reply with yours if you want.
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I trade 27 forex pairs - all majors and crosses except GBPNZD. Type: Quantitative swing. Two trades per day on average.
How I discovered it: I built about 10 indicators based on different ideas and looked for the best combination through optimization on large periods of lots of instruments - forex pairs, equities, commodities, crypto. Forex pairs showed the best result by far. I verified through WFA. It worked pretty well even without out-of-sample tests.
Exit: Fixed TP=20-50 pips, Dynamic Virtual SL based on the 4 indicators mentioned above, Hard SL=Very far, just for extra protection, never hit.
Average win = 28 pips, average loss = 51 pip. Win rate = 73%
Optimization: last 3 months. Around 1 million variants sorted by Recovery Factor and number of trades.
OOS: recent OOS**:** preceding 9 months, choice: RF>=2; Long OOS: 12 months before the recent OOS, choice: RF>=1.3, if lower no rejection but effects volume of trading.
Stress Tests: reject only if DD goes wild and doesn't recover.
Stability test: chosen setup with different TP and SL. Want to see positive RF on each variant. Must be no surprises like for example, tp20 = great, but tp50 = crazy losses
*This new algorithm was built by ChatGPT when it analyzed all the details. Up until recently I used a simpler version: Only one OOS: 3 months that precede the optimization, and no stress tests.
Through combining the backtests of all the instruments I saw which volume per balance I need to trade to keep safe distance from margin stop: it's 0.01 per $600. Factually, I've never got close even to the Margin Call (Margin Level = 100%).
Thought I should share the process and concept of my trading. Reply with yours if you want.
________________________
I trade 27 forex pairs - all majors and crosses except GBPNZD. Type: Quantitative swing. Two trades per day on average.
Position Lifecycle
Signal: mixture of 4 custom-made technical indicators. Each based on different idea, has lots of parameters and its own timeframe. I don't know why their mixture works. Even LLMs couldn't realize. Seems like a type of mean reversion, not pure.How I discovered it: I built about 10 indicators based on different ideas and looked for the best combination through optimization on large periods of lots of instruments - forex pairs, equities, commodities, crypto. Forex pairs showed the best result by far. I verified through WFA. It worked pretty well even without out-of-sample tests.
Exit: Fixed TP=20-50 pips, Dynamic Virtual SL based on the 4 indicators mentioned above, Hard SL=Very far, just for extra protection, never hit.
Average win = 28 pips, average loss = 51 pip. Win rate = 73%
Research
Rolling every 2 months for each instrument.Optimization: last 3 months. Around 1 million variants sorted by Recovery Factor and number of trades.
OOS: recent OOS**:** preceding 9 months, choice: RF>=2; Long OOS: 12 months before the recent OOS, choice: RF>=1.3, if lower no rejection but effects volume of trading.
Stress Tests: reject only if DD goes wild and doesn't recover.
Stability test: chosen setup with different TP and SL. Want to see positive RF on each variant. Must be no surprises like for example, tp20 = great, but tp50 = crazy losses
*This new algorithm was built by ChatGPT when it analyzed all the details. Up until recently I used a simpler version: Only one OOS: 3 months that precede the optimization, and no stress tests.
Risk Management
My leverage: 1:30, Margin Stop: Margin Level = 50%Through combining the backtests of all the instruments I saw which volume per balance I need to trade to keep safe distance from margin stop: it's 0.01 per $600. Factually, I've never got close even to the Margin Call (Margin Level = 100%).