Section II: Asset Returns & Volatility Analytics
Before applying derivative-based analysis to a security, it is essential to understand the broader process of transforming raw market-price and trading-volume data into structured, analysis-ready information. In practice, this process involves cleaning, organizing, and preparing the data before converting a time series of prices into a corresponding series of asset returns. Both traditional statistical methods and more advanced machine-learning applications generally rely on returns data rather than raw price levels.
Understand the Linkage
Data science is usually more focused on insight, interpretation, and communication, while machine learning is more focused on model building, optimization, and automation. They overlap heavily, but data science asks, “What is happening and why?” while machine learning asks, “Can we learn a rule that predicts what happens next?”.