Keywords: financial assets, return prediction, linear models, data preprocessing, time series
Description:
Using the data of three real assets given by a Chicago Financial Service and Technology company, we make basic analysis for their statistics to understand
their relationships and develop potential strategies to make investment. After carefully analyzing the data, we also preprocess the financial data by
removing outliers, building time series, and making other necessary processing. Though we finally utilized general linear regression to predict the return,
we also try gradient boosting and ARIMA, which do not fit for this one.
Report: Please mail to me (hw2894@columbia.edu) or through the mail symbol at the right bottom.