penn state class project - SENTIMENT DRIVEN MARKET VOLATILITY INDEX
why we made this : traditional volatility models like vix miss sentiment-driven moves. news and social media can move markets before the numbers catch up. we built a pyspark pipeline to process large-scale text, extract sentiment, and combine it with volatility metrics to capture those early signals. The goal is a sentiment-weighted volatility index that improves short-term predictions. Markets are driven by both numbers and human behavior; ignoring sentiment leaves a blind spot. by processing millions of documents at scale and blending sentiment with quantitative models, we aim to build a more complete view of market dynamics.
