← All Projects

Quantitative Finance · Python

Real-World
Options Analyser

An interactive Streamlit dashboard that fetches live options chains for any stock symbol and computes Black–Scholes prices, Greeks, and implied volatility with intuitive visualisations.

Python Streamlit NumPy SciPy Plotly Black–Scholes
Full Analysis ↗

BSM

Pricing Model

5

Greeks Computed

Live

Market Data

IV

Surface Mapping

01 / Problem

Options analysis is locked behind expensive terminals

Proper options analysis — BSM fair value, full Greeks, implied volatility surface — typically requires Bloomberg or equivalent platforms costing thousands per month. Individual traders and small desks have no lightweight, code-driven alternative they can adapt to their own strategies.

02 / Approach

Live data + analytical layer in a Streamlit app

Options chain data is pulled live for any ticker via a market data API. The analytical layer implements closed-form Black–Scholes pricing in NumPy/SciPy, computing Delta, Gamma, Vega, Theta, and Rho for every contract in the chain.

Implied volatility is solved numerically using Brent's method — iterating until the BSM price matches the observed market price. Results are rendered in Plotly: volatility smiles, Greek heatmaps, and put/call comparison charts. The entire dashboard is a single Streamlit script — reproducible, modifiable, and deployable in minutes.

03 / Result

Terminal-grade options analytics, open source

Any ticker can be loaded, the full options chain analysed, and BSM mispricing surfaces identified — without a Bloomberg subscription. The full interactive analysis with code and methodology is documented in the companion report.

Key Features
  • Live options chain retrieval for any ticker
  • Black–Scholes fair value computation
  • Full Greeks: Delta, Gamma, Vega, Theta, Rho
  • Implied volatility via Brent's method
  • Volatility smile and Greek heatmap visualisations