This project performs large scale Monte Carlo simulations of the eigenvalues that appear in Johansen's null distribution. Results are written to `*.dat` files which can be reloaded later for analysis.

Build a forecasting model to predict the sale of a store.

Project exploring the possibility of building a statistical arbitrage strategy based on pricing inefficiencies between three S&P 500 ETFs. The approach combines Johansen cointegration analysis to define mean-reverting spreads, and ARMA forecasting to generate trading signals.

Statistical arbitrage engine that screens S&P 500 pairs using Engle-Granger and Johansen cointegration tests, fits Ornstein-Uhlenbeck dynamics via MLE, and trades spreads with a Kalman filter hedge ratio. Includes a walk-forward backtest with monthly pair re-screening, continuous position carry-over, and a full performance dashboard.

Code from the paper Over the Stable Space of a Multivariate Time Series

An advanced mean-reversion trading strategy for ETF baskets using Bayesian Optimization to maximize Sharpe Ratio. Features walk-forward analysis, cointegration testing, and comprehensive backtesting reports.