Use cases

Use Cases

⚠️ DISCLAIMER: The examples and use cases provided in this documentation are for informational and educational purposes only. They are NOT trading advice, financial advice, or investment recommendations. Sentiment402 provides market context data only; it does not provide investment guidance.

Do Your Own Research (DYOR): Always conduct your own thorough research before making any trading or investment decisions. Market sentiment data is one of many factors to consider, and past performance does not guarantee future results.

Use at Your Own Risk: Trading cryptocurrencies and other financial instruments involves substantial risk of loss. You should only trade with funds you can afford to lose. The examples shown here are illustrative only and may not be suitable for your specific situation.

Sentiment402, its operators, and contributors are not responsible for any losses or damages resulting from the use of this data or the examples provided.

Trading Bot Gating

Problem: Bots get wrecked by narrative shifts they can't see in price data.

Solution: Check sentiment before every trade and downshift risk when sentiment is unstable.

// Compact format saves bandwidth
const sentiment = await getSentiment({ format: "compact_trading" });

// 1. Extreme fear: avoid longs
if (direction === "long" && sentiment.mood < 30) return false;

// 2. Decoupling + "reduce_risk": hard stop
if (sentiment.corr_status === "decoupled" && sentiment.rec === "reduce_risk") return false;

Tip: gate on both mood and correlation status rather than mood alone.

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Grid Trading Optimization

Problem: Fixed grids don't adapt to volatility.

Solution: Dynamic grid spacing based on mood (and optionally correlation).

• Fear (<30): Widen grids (1.5x) for safety.

• Greed (>80): Narrow grids (0.8x) to capture volatility.

• Neutral: Standard spacing.

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AI Agent Context (MCP)

Problem: Agents need "why" without expensive scraping loops.

Solution: One tool call gives full narrative context.

Agent Prompt: "Should I long BTC?"

Agent Action: Calls get_crypto_pulse.

Result: The agent can summarize the pulse + outlook into an action recommendation.

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Portfolio Rebalancing

Problem: Knowing when to rotate between crypto and stables.

Solution: algorithmic rebalancing based on moodIndex and correlationLayer.

if (sentiment.cryptoPulse.moodIndex > 75) {
  // High greed: Rotate to stables
  target_allocation = { crypto: 0.4, stables: 0.6 };
} else if (sentiment.cryptoPulse.moodIndex < 30) {
  // High fear: Accumulate
  target_allocation = { crypto: 0.75, stables: 0.25 };
}

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DeFi Risk Gating

Problem: Impermanent loss and liquidation cascades.

Solution: Exit pools on Crash signals or correlation breakdown.

if (sentiment.marketMovement?.crypto?.label === "down") {
  await exitPool(); // Emergency exit
}
if (sentiment.correlationLayer.status === "decoupled") {
  await reduceLeverage(); // Contagion risk
}