Open souce quantitative finance models and algorithms with tutorials
Last updated Jun 16, 2026
64
Stars
10
Forks
0
Issues
0
Stars/day
Attention Score
36
Topics
Language breakdown
Jupyter Notebook 94.9%
Python 5.1%
▸ Files
click to expand
README
Quantitative finance models and algorithms
Collection of models with optimization algorithms for Time series analysis, algorithmic forecasting, quantitative research and risk-management.
Assets pricing and Optimization models
- European option pricing via Monte-Carlo simulation, Black-Scholes model
- discretization error estimate
- sensitivity analysis of option price to strike and volatility
- sensitivity of discretization error to number of simulations
- linear asset pricing: FX income, capital budgeting, floating-rate notes
- univariate concave nonlinear optimization of IRR-YTM using Brent method and binary grid search on subintervals
- available as mixed integer programming problem, ready-to-use on NISQ devices
Time series analysis models
GJR-GARCH- Glosten-Jagannathan-Runkle GARCH(p, o, q)
- unsupervised optimization of parameters
- captures asymmetric shocks (leverage effect)
- ARIMA(p, d, q)x(P, D, Q, s)
- unsupervised optimization of AR, MA and Seasonal parameters
- provides one-step-ahead predictions and out-of-sample forecast
- triple exponential smoothing
- cross-validation via Conjugate gradient, TNC
- in-sample prediction and extrapolation
- Moving average
- Exponential smoothing
- Double exponential smoothing
License and Copyright
Copyright (c) 2019 Oleksii LialkaLicensed under the MIT License.
🔗 More in this category