Strategy Examples

This page collects public Stingray examples where a plain-English market idea became a typed rule and a backtest artifact. The goal is proof over pitch: show the prompt, the data sources, the replay window, the trigger count, and the forward-return shape before anything goes live.

These are published product walkthroughs, not anonymized customer case studies. When customer examples are published, they should be permissioned, anonymized, and specific enough to audit.

What each example should show

• The prompt or thesis the user started with
• The typed condition Stingray produced
• The data sources used during the replay
• The backtest window and trigger count
• Forward returns or hit-rate summaries at relevant horizons
• The activation path: notify, preview-confirm, or opt-in execution

Funding-rate squeeze example

The prompt:

Create a draft alert that fires when BTC funding rate on Hyperliquid is below 0 bps/hr and Binance BTCUSDT moves up at least 0.5% over 60 minutes. Keep it as a draft, do not activate it.

What Stingray tested:

• Data sources: Hyperliquid funding and Binance BTCUSDT price
• Window: 2026-04-20 to 2026-05-18
• Raw matches: 150 five-minute windows
• Fired alerts after 1h cooldown: 37
• 24h profile: average +0.41%, 62% positive, median +0.55%
• Compound comparison from non-overlapping 24h holds: +8.3% versus BTC buy-and-hold at +4.9%

Read the full funding-rate walkthrough.

BTC breakout alert example

The prompt:

Alert when RSI is above 65, price touches or breaks the upper Bollinger Band, and volume is 2x the 24h average, all true at the same time on the 1h chart.

What Stingray tested:

• Data sources: BTCUSDT price, RSI, Bollinger Band, and volume
• Window: April 2025 to April 2026
• Fired alerts after 1h cooldown: 109
• Frequency: about one fire every 3.3 days
• Forward-return profile: +0.03% at 1h, -0.26% at 4h, +0.17% at 24h
• Use case: reject loose breakout logic before a live alert starts waking anyone up

Read the full BTC breakout walkthrough.

More strategy inputs to test

These examples are crypto-market-native because that is where the most complete public data lives today. The pattern is broader: state a thesis, resolve the data, replay it, and only then decide whether to monitor or activate.

• Funding rates plus macro events
• Polymarket odds as a trading signal
• FOMC transcripts as strategy inputs
• Whale flow and open-interest divergence

What these examples are not

They are not trading advice, live performance promises, or proof that a rule will work in the future. They are proof that the rule was made explicit, tested against a stated historical window, and turned into an artifact someone can inspect before capital is involved.

For the full workflow, start with How Stingray Works, learn how to read a backtest card, or browse the Strategy Guides.