Using Deep Learning to Find "Market DNA" — Pattern Matching Across BTC, NASDAQ, and Gold

The Fractal Hypothesis Markets are fractal — patterns repeat across different scales and assets. This isn't mysticism; it's a well-documented phenomenon in quantitative finance. Mandelbrot wrote about it, and modern quant funds use it daily. But what if you could automate the search for these repeating patterns? NextCandle: Cross-Asset Pattern Intelligence I've been working on a tool called NextCandle that applies deep learning to find historically similar candlestick patterns. What started as a BTC/USDT analyzer has grown into a multi-asset platform. Supported Assets Asset Timeframes Data Depth BTC/USDT 1H, 4H, 1D, 1W 10+ years ETH/USDT 1H, 4H, 1D, 1W 8+ years NASDAQ 4H, 1D, 1W 15+ years S&P 500 4H, 1D, 1W 20+ years Gold 4H, 1D, 1W 15+ years The Lookback Revolution One of the most requested features was extended lookback — analyzing up to 100 candles at once instead of just 3. This enables: Macro pattern recognition : Identifying multi-week formations Higher confidence matches : More