On the bull run, alpha here is measured against SPY, which ran the same period. The claim is relative outperformance, not that we picked a rising tide. The window also includes 2020 and 2022, not great for momentum strategies. Signals that showed near-zero predictive value in statistical validation are zeroed out of the scoring.

Paper trading is already running against live signals. The daily reports are public and free, no subscription needed to check. Methodology is at https://jumpstartsignal.com/how-it-works/ if you want the detail on what's actually being validated.

On stock picking: the system is rules-based and mechanical, not discretionary. The "folly" argument applies most strongly to human judgment calls, which this attempts to remove. I literally wanted to reduce bias and get a better vantage point.

On beating the index: 14 years of backtested data with walk-forward validation suggest it's possible for this specific strategy. Whether it holds going forward, nobody knows. We publish the ten best and worst precisely because we're not claiming certainty.

The round numbering is partly for exactly the reason you named: it forces a name onto every change. When a result comes out wrong, the temptation to quietly shift a threshold is real, and having to call it R28 and re-run the full validation raises the cost of doing that on a whim.

Perhaps a changelog would close the loop though? Right now, R27 is visible in config and referenced in the metrics, but there's no page that says "R27 changed X because Y, here's what the backtest/walk-forward showed before and after." That's the missing accountability layer, and probably more useful to a skeptical reader than any amount of methodology prose.

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.

Comments URL: https://news.ycombinator.com/item?id=47908912

Points: 30

# Comments: 25

Perhaps read 'The Relation of Science and Religion', Richard P. Feynman.

I have chewed this cud before: http://tr.im/f95s