u/DavieTheAl

Context: I trade crypto, specifically leveraged futures. And I kept running into the same frustrating loop.

I'd have a read on the market, enter a trade feeling confident, get stopped out. Then two weeks later the thing I expected to happen would play out exactly as I thought. Just without me in it.

The question I couldn't answer: was my actual analysis right, but my timing was off? Or was I just getting lucky with pattern recognition and fooling myself?

The tools that exist for this are built for stock traders (they don't handle crypto-specific data like open interest, funding rates, or liquidation levels), or they require you to write code, which I don't want to do every time I have a trading idea. I just wanted something simple: "has this setup worked historically, and tell me when it's happening again."

So I built it. Called it Stingray (stingray DOT fi). You describe your entry conditions, run them against historical data, see what would have happened. Then set an alert so your phone pings when those conditions are live again. No code required.

Classic "scratch your own itch" project. I've been using it for a few months and it's genuinely changed how I approach entries. But I've been too deep in building it to know what's confusing to a fresh set of eyes, what's missing, or what's just broken in ways I've stopped noticing.

Looking for people willing to actually use it and tell me the honest version of good or bad!

Ran this backtest out of curiosity after noticing SOL seemed to bounce fast after big drawdowns. Wanted to know if that was real or just survivor bias.

365 days of data. Signal: SOL price drops more than 8% in any 24-hour window.

Results:

• Total signals fired: 181
• 1-hour forward win rate: 56.4% (avg return: +0.11%)
• 4-hour forward win rate: 59.1% (avg return: +0.08%)
• 24-hour forward win rate: 49.2% (avg return: +1.06%)

The short-term bounce is the real story here. At 1h and 4h, the win rate is meaningfully above 50%. By 24h, the win rate falls back toward 50% but the average return stays elevated (+1.06%) because the winners are bigger than the losers.

Distribution of 24h returns:

• 46 fires (25%) returned >+5% in the next 24h
• 23 fires (13%) continued down >5%
• Best single outcome: +14.85%
• Worst single outcome: -15.84%

This is not a "buy every dip" signal. The 24h win rate is basically a coin flip. What it is: a short-term mean reversion signal with positive expected value and positively skewed payout. The 4h timeframe is where the edge is clearest.

Stingray.fi shows when SOL drops 8%+ in a day, the next 1-4 hours have historically been favorable for a bounce trade. You're not betting on sustained recovery, you're betting on an immediate relief move.

The signal breaks down when you extend to 24h, by then the macro picture dominates and the dip effect has faded.

Worth noting: 32 distinct events drove the 181 fires (some events cluster as the same underlying move). That's enough sample to say something, not enough to bet the house on it.

(Ran this with Stingray's backtest API. Full backtest card here if you want the chart:)

Ran this backtest out of curiosity after noticing SOL seemed to bounce fast after big drawdowns. Wanted to know if that was real or just survivor bias.

365 days of data. Signal: SOL price drops more than 8% in any 24-hour window.

Results:

• Total signals fired: 181
• 1-hour forward win rate: 56.4% (avg return: +0.11%)
• 4-hour forward win rate: 59.1% (avg return: +0.08%)
• 24-hour forward win rate: 49.2% (avg return: +1.06%)

The short-term bounce is the real story here. At 1h and 4h, the win rate is meaningfully above 50%. By 24h, the win rate falls back toward 50% but the average return stays elevated (+1.06%) because the winners are bigger than the losers.

Distribution of 24h returns:

• 46 fires (25%) returned >+5% in the next 24h
• 23 fires (13%) continued down >5%
• Best single outcome: +14.85%
• Worst single outcome: -15.84%

This is not a "buy every dip" signal. The 24h win rate is basically a coin flip. What it is: a short-term mean reversion signal with positive expected value and positively skewed payout. The 4h timeframe is where the edge is clearest.

Stingray.fi shows when SOL drops 8%+ in a day, the next 1-4 hours have historically been favorable for a bounce trade. You're not betting on sustained recovery, you're betting on an immediate relief move.

The signal breaks down when you extend to 24h, by then the macro picture dominates and the dip effect has faded.

Worth noting: 32 distinct events drove the 181 fires (some events cluster as the same underlying move). That's enough sample to say something, not enough to bet the house on it.

(Ran this with Stingray's backtest API. Full backtest card here if you want the chart:)

Curious whether others have found the 4h window or use different entry logic?