Yug Anil Solanki / Perfil

Hey everyone, I recently finished architecting a new quantitative volatility engine for Gold (M3 timeframe) and just successfully pushed it through the automated validator's netting and margin stress tests. I wanted to share the core logic and execution mechanics with the community, as optimizing for extreme institutional-level breakouts presented some unique coding challenges. The Logic:
Instead of relying on lagging retail oscillators, the algorithm (Aurum Floww) operates entirely on a Multi-Anchored VWAP model cross-referenced with variance standard deviations. It sits dormant until price action extends to an extreme statistical anomaly—specifically a +4.0 Standard Deviation band during the London/NY overlapping sessions. To protect equity during standard mean reversion, the system uses a dynamic Volatility-Band Trailing Stop, trailing risk mathematically behind lower standard deviation bands rather than static points. The Engineering Hurdles:
The biggest challenge was the fractional compounding math. Because the system targets massive +38 StdDev moves, the account equity scaled aggressively during the 2024-2026 data runs. I had to build a custom Order Splitter function to seamlessly slice block orders and bypass the strict 100-lot broker ceilings and netting volume limits, ensuring zero slippage bottlenecks as the volume scaled. The Data (100% Real Ticks): Asset: XAUUSD (M3) Period: Jan 2024 – Feb 2026 Starting Equity: $100,000 Net Profit: $3,679,586.09

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