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
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volatility-modelling
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This project aims to construct the Equity Implied Volatility surface under the Stochastic Volatility Inspired (SVI) model.
python jupyter-notebook derivatives option-pricing black-scholes implied-volatility equity-options svi volatility-modeling option-pricing-calculator volatility-smile quant-finance volatility-modelling volatility-surface arbitrage-free-pricing black-scholes-model option-pricing-theory arbitrage-free svi-implied-volatility
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Mar 18, 2026 - Jupyter Notebook
A python-based risk engine that computes Value at Risk (VaR) and Expected Shortfall. The engine includes a tournament-style selector to identify the optimal dynamic GARCH model using AIC/BIC. It also provides a backtesting function with validation hypothesis tools such as Proportion of Failure (POF) and Christoffersen Independence test (CIT).
python statistics hypothesis-testing garch value-at-risk risk-management backtesting expected-shortfall quant-finance financial-modelling volatility-modelling
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Updated
Aug 7, 2026 - Jupyter Notebook
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