Vollab (Volatility Laboratory) is a python package for testing out different approaches to volatility modelling within the field of mathematical finance.
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Updated
Apr 30, 2021 - Jupyter Notebook
Vollab (Volatility Laboratory) is a python package for testing out different approaches to volatility modelling within the field of mathematical finance.
Quantitative Finance Library & Option Trading Tool
Daily Volatility trading strategies on Index Equity Options
Closed-form solutions and fast calibration & simulation for SABR-based models with mean-reverting stochastic volatility
Jupyter notebooks implementing Finance projects
A package that utilises QT and OpenGL graphics to visualise realtime 3D volatility surfaces and analytics.
Live updating dynamic volatility surface constructed from options prices in C++
An interactive toolkit visualising options pricing and Greeks across Black-Scholes and Monte Carlo models with comparative analytics.
No-arbitrage SVI calibration is currently available.
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
Toolkit for option market research: SABR/SVI baseline calibration, neural network volatility surface models, fast Greeks inference, and reinforcement learning agents for dynamic hedging.
active investing
BEVL Toolkit is a Python library for constructing Break-Even Volatility (BEVL) surfaces — the volatility level that makes the expected P&L of a delta-hedged option equal to zero.
Implied Volatility Calibration via raw-SVI
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