Financial Time Series Explorer
Interactive exploration of market prices, returns, volatility, drawdowns, and correlations
This project is an interactive Streamlit application for exploring financial time series data. Using Python, yfinance, and rich visualizations, the app lets users select market tickers and dynamically analyze normalized prices, log returns, cumulative returns, rolling volatility, drawdowns, and cross-asset correlations. By combining configurable filters, modular analytics functions, and Plotly-based charts, it provides a practical tool for understanding market behaviour and risk over time.
View Project on GitHub
Explore the full application, including data pipeline, metrics, and visualization code, in the GitHub repository.