Stochastic Valuation Processes
Stochastic Valuation models for stocks and bond rates.
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This is a collection of Stochastic Valuation methods for Monte-Carlo simulations of stock prices and bond interest rates. These simulations help to backtest on synthetic data trading strategies, asset allocation methods, option pricing, volatility estimators,etc.
Currently, the implemented methods are:
- Stock prices: Brownian Motion, Geometric Brownian motion, Merton model, Heston model.
- Bond Rates: Vasicek interest rate model, Cox Ingersoll Ross model
- Utilities: Quote inflow order (volume generation, according to the price series), Information driven bars (see Advances in Financial Machine Learning for details).
In the Getting started guide, you will find complete documentation of the toolbox.
Cite As
Lautaro Parada (2026). Stochastic Valuation Processes (https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.5.1), GitHub. Retrieved .
General Information
- Version 1.0.5.1 (2.34 MB)
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View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.5.1 | See release notes for this release on GitHub: https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.5.1 |
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| 1.0.5 | See release notes for this release on GitHub: https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.5 |
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| 1.0.4 | See release notes for this release on GitHub: https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.4 |
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