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Use factor model to predict stock return and evaluate our predictions on stock returns.
In this Build Project you will use factor models to predict stock returns. The project is an example of quantitative finance field, where people utilize the skill of data analysis, statistics and programming to predict stock return and make investment decisions. You’ll learn to handle data using Python and get a solid introduction to forecasting in finance. The project covers important basics like data analysis and applying factor models. Completing it will gear you up for entry-level finance and data science jobs, which are key roles in many U.S. industries. This is a great start for students aiming for a future in the financial sector.
Get to know the Build Fellow and other students, ask questions about the project requirements, prepare your workspace.
Read stock price downloaded from Kaggle in Python using pandas package.
Process stock price to stock return and analyze the data in Python using pandas. Visualize the analysis in Python.
Understand the math of linear regression; write code to run linear regression in Python.
Load data of Fama-French factors from website to Python.
Run linear regression in Python, use Fama-French factors to predict stock return.
Learn about the key matrices to evaluate the accuracy of prediction, and evaluate the predicted stock return.
Polish your project deliverables and present them to the Build Fellow and other students in the final group session.
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