Ir al contenido principal


Mostrando las entradas de mayo, 2021

Stochastic Valuation Processes

This toolbox packages a set of stochastic processes for prices and rates simulation, aiming to create a synthetic dataset for quantitative back-testing of trading strategies and asset allocations methods. TLDR; Matlab SDK for stochastic simulation of stock prices and bond rates. Additionally, some utilities to sample data are included, such as Order flow and information-driven bars. Please visit the site documentation for details Rationale Simulating synthetic stock prices and bond rates provides an alternative back-testing method that uses history to generate datasets with statistical characteristics estimated from the observed data. This method allows back-testing on a large sample of unseen scenarios, reducing the likelihood of overfitting to a particular historical data set. Because each trading strategy needs an implementation tactic (a.k.a., trading rules) to enter, maintain, and exit the respective positions on each instrument, a simulation over thousands of different scenari