Stochastic Valuation Processes

Stochastic Valuation models for stocks and bond rates.
247 descargas
Actualizado 25 May 2020

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.

Citar como

Lautaro Parada (2024). Stochastic Valuation Processes (https://github.com/LautaroParada/stochastic-processes/releases/tag/1.0.5.1), GitHub. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2020a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

@randomProcesses

Versión Publicado Notas de la versión
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

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.