A free ESG stock screener that publishes its losses and methodology
Hey HN, JSS(JumpstartSignal) is a free, ESG-filtered daily stock screener. I built it after some really badly-timed quantum computing stock buys, so I felt I needed to learn more about systematic, longer-horizon approaches and the underlying technicals instead of chasing themes. Three things about it that might be of interest: 1. Methodology is fully documented at https://jumpstartsignal.com/how-it-works/ 5-stage pipeline, 54 signals tested individually plus 1,836 combinations evaluated, walk-forward validation across 25 hold periods. Nothing hand-tuned to a single…
In plain words
JumpstartSignal is a free daily stock screener that filters companies based on ESG criteria and technical signals. It uses a five-stage pipeline testing 54 individual signals and 1,836 combinations through walk-forward validation across multiple time periods. The tool is designed for investors seeking systematic, longer-term approaches rather than theme-chasing. What distinguishes it is full transparency: the methodology is publicly documented, and the maker publishes both successful and unsuccessful stock picks as case studies showing the system's real-world performance.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN, JSS(JumpstartSignal) is a free, ESG-filtered daily stock screener. I built it after some really badly-timed quantum computing stock buys, so I felt I needed to learn more about systematic, longer-horizon approaches and the underlying technicals instead of chasing themes. Three things about it that might be of interest: 1. Methodology is fully documented at https://jumpstartsignal.com/how-it-works/ 5-stage pipeline, 54 signals tested individually plus 1,836 combinations evaluated, walk-forward validation across 25 hold periods. Nothing hand-tuned to a single backtest window. 2. Many wins, misses, and losses are published as case studies e.g. https://jumpstartsignal.com/case-studies/nvda/ walks through the 32 times the system flagged NVDA starting at $5.44 in 2018. https://jumpstartsignal.com/case-studies/sedg/ shows a -49% loss, and https://jumpstartsignal.com/case-studies/tsla/ explains why the system never flagged Tesla (it passed Stages 1 and 2 on 207 days but only peaked at 20/100 in scoring vs the 70 needed for OPPORTUNITY tier). https://jumpstartsignal.com/results/ also shows the 10 best entries alongside the 10 worst. 3. A genetic algorithm picked the signal weights, but constrained to maintain alpha across multiple market regimes (otherwise it overfits to a single bull market). The constraint dropped some "best in backtest" configurations that only worked 2018-2021. Topline: 2012-2025 backtest at SPOTLIGHT + OPPORTUNITY tier produced +163% alpha vs SPY (results page has the per-trade breakdown). Daily watchlist emailed free; reports + results + case studies are publicly browsable without signup. Happy to take questions about methodology, what the system gets wrong, or why specific tickers landed where they did.
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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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