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Institutional-style regime detection for crypto traders

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    Hey HN, For the past few years, I've been obsessed with trying to get AI to produce accurate trading signals. The main challenges I found with AI trading models are lack of consistency, context window bottlenecks, hard to backtest, and high cost. Asking ChatGPT "Should I buy Bitcoin today?" doesn't work well because the LLM doesnt have a set trading strategy to opperate from. In addition, the small context window makes it challenging to fit enough historical data into. Not to mention it gets very expensive as well. My solution is a hybrid approach. Instead of having the LLM make direct…

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    Hi HN, I'm a solo dev and for the last few months I've been building Hikaro, a tool to find statistically significant trading signals for [e.g., US equities, crypto, forex]. I built this to solve my own problem: I was tired of backtests that looked great on paper but failed in practice. Simple metrics like "win rate" can be misleading, so I wanted a way to quickly tell if a signal's performance was genuine or just noise. Hikaro ingests daily market data and runs statistical analysis on various trading signals. The goal is to surface signals with strong properties, like: Low p-value: Evidence…

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