Stochastic Valuation Processes

Version 1.0.5.1 (2.34 MB) by Lautaro Parada
Stochastic Valuation models for stocks and bond rates.
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Updated 25 May 2020
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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 (2024). Stochastic Valuation Processes (https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.5.1), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.5.1

See release notes for this release on GitHub: https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.5.1
1.0.5

See release notes for this release on GitHub: https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.5
1.0.4

See release notes for this release on GitHub: https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.4
To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.