TRADING & QUANT RESEARCH

OVERVIEW

PulseBit provides quantitative traders and researchers with machine-readable sentiment data for trading algorithms. The API delivers structured sentiment scores, historical datasets for backtesting, and systematic strategy inputs.

Trusted by quant teams, proprietary trading firms, and individual algo traders for generating news-driven alpha signals and managing risk exposure.

KEY FEATURES FOR TRADING

CODE EXAMPLES

import requests

def get_crypto_sentiment():
    """Fetch Bitcoin sentiment for trading signal"""
    response = requests.get(
        "https://api.pulsebit.io/news_search",
        params={"q": "Bitcoin", "limit": 50},
        headers={"X-RapidAPI-Key": "YOUR_API_KEY"}
    )
    data = response.json()
    
    # Calculate aggregate sentiment
    sentiments = [article['sentiment'] for article in data['articles']]
    avg_sentiment = sum(sentiments) / len(sentiments)
    
    # Generate signal
    if avg_sentiment > 0.2:
        return "BUY"
    elif avg_sentiment < -0.2:
        return "SELL"
    return "HOLD"

signal = get_crypto_sentiment()
print(f"Trading Signal: {signal}")

const axios = require('axios');

async function monitorMarketSentiment(topics) {
  const results = await Promise.all(
    topics.map(async (topic) => {
      const response = await axios.get(
        'https://api.pulsebit.io/news_recent',
        {
          params: { topic, hours: 1 },
          headers: { 'X-RapidAPI-Key': process.env.API_KEY }
        }
      );
      
      const articles = response.data.articles;
      const avgSentiment = articles.reduce(
        (sum, a) => sum + a.sentiment, 0
      ) / articles.length;
      
      return { topic, sentiment: avgSentiment, count: articles.length };
    })
  );
  
  return results;
}

// Monitor finance and crypto topics
monitorMarketSentiment(['finance', 'crypto']).then(console.log);

# Download 90-day sentiment history for backtesting
curl -X GET "https://api.pulsebit.io/news_stats?days=90&topic=finance&format=json" \
  -H "X-RapidAPI-Key: YOUR_API_KEY" \
  -o backtest_data.json

# Parse with jq for time series analysis
cat backtest_data.json | jq '.daily_stats[] | {date, sentiment_avg, article_count}'

COMMON USE CASES