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A project for STATS 601 at the University of Michigan. The project aims to model stock returns and volatility. We implemented a Support Vector Regression model with GARCH to predict volatility, and compared it against a multivariate linear ridge regression model.

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Name		Name	Last commit message	Last commit date
Latest commit History 86 Commits
data		data
model		model
models(ipynb)		models(ipynb)
src		src
.DS_Store		.DS_Store
README.md		README.md
final_project.pdf		final_project.pdf
main.py		main.py
main_ols.py		main_ols.py
main_ziwei.py		main_ziwei.py

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multivariate-time-series-prediction

A project for STATS 601 at the University of Michigan

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A project for STATS 601 at the University of Michigan. The project aims to model stock returns and volatility. We implemented a Support Vector Regression model with GARCH to predict volatility, and compared it against a multivariate linear ridge regression model.

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