OIPD computes the market's expectations about the probable future prices of an asset, based on information contained in options data.

Streamlit IV surface visualizer (Yahoo Finance + Black–Scholes). Explore IV vs expiry and strike/log-moneyness.

Vollab (Volatility Laboratory) is a python package for testing out different approaches to volatility modelling within the field of mathematical finance.

Daily Volatility trading strategies on Index Equity Options

Closed-form solutions and fast calibration & simulation for SABR-based models with mean-reverting stochastic volatility

Quantitative Finance Library & Option Trading Tool

A quantitative research project exploring hybrid volatility forecasting. Integrates parametric surface models (SVI/SSVI) and Risk-Neutral Density (RND) extraction with Deep Learning (LSTM + Self-Attention) to predict future Implied Volatility surfaces.

https://arbitragefreessvi.streamlit.app/

Jupyter notebooks implementing Finance projects

A package that utilises QT and OpenGL graphics to visualise realtime 3D volatility surfaces and analytics.

Modular multi-asset-class Monte Carlo engine for pricing exotic derivatives and structured products with calibrated implied volatility surfaces (Heston, local vol, SVI) and a user-friendly Django web interface.

Quantitative finance library for volatility surface modelling in C++20

An interactive toolkit visualising options pricing and Greeks across Black-Scholes and Monte Carlo models with comparative analytics.

Live updating dynamic volatility surface constructed from options prices in C++

Implied volatility surfaces from SPX option chains data (both calls and puts), interpolation for continuous querying, and GUI to visualize surfaces and calculate Black-Scholes prices and IVs

A volatility surface cleaner built by a high school student — arbitrage-free interpolation of implied volatility from real options data.

Fast Monte Carlo option strategy simulator with implied vol surfaces in Rust

Toolkit for option market research: SABR/SVI baseline calibration, neural network volatility surface models, fast Greeks inference, and reinforcement learning agents for dynamic hedging.

📈 Build and analyze arbitrage-free volatility surfaces with robust calibration and visualization tools for options pricing.