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Building a vector autoregressive model with R. My coursework for the course Time Series Analysis II (offered by University of Helsinki's Master's Programme in Mathematics and Statistics), spring 2020.
Machine Learning case study including an exploratory data analysis and fitting a Decision Tree, Random Forest, and XGBoost Model. Interactive notebook with outputs and visualizations: https://yaldan.github.io/ml_case_study/
Testing the hyphotesis of cointegration of two term structures through Dickey-Fuller tests and Engle-Granger causality. Finally I exploit the VECM to infer the model and through the Cholesky decomposition I analyze SIRF and FEVD