Alternative Data in Finance: Satellite, Social, and Sentiment

Module: Fintech AI | Difficulty: Advanced

Data Sources

Sentiment Analysis

Alpha from Alt Data

Processing Pipeline

import numpy as np
from textblob import TextBlob

class SentimentAnalyzer:
    def __init__(self):
        pass
    def analyze(self, text):
        blob = TextBlob(text)
        return {
            'polarity': blob.sentiment.polarity,
            'subjectivity': blob.sentiment.subjectivity
        }
    def aggregate_sentiment(self, texts, method='mean'):
        sentiments = [self.analyze(t)['polarity'] for t in texts]
        if method == 'mean':
            return np.mean(sentiments)
        elif method == 'median':
            return np.median(sentiments)
        return sentiments

Research Insight: Alternative data provides unique insights but has low signal-to-noise ratio. The key is combining multiple sources — satellite data alone is weak, but combined with social sentiment and transaction data, it can predict earnings surprises.