Lecture 18: Multiple linear regression model to Predict SPY Price Changes with Python| Practice|

Complete Course Material : https://drive.google.com/file/d/1uy6J...
In this video, we delve into the application of Multiple Linear Regression to generate signals for the growth of SPY, the exchange-traded fund tracking the S&P 500. By utilizing multiple global market indices as predictors, we aim to forecast the daily price change of SPY, making informed trading decisions. Discover the rationale behind selecting SPY for trading, considering its suitability and volatility. We leverage data from various global markets, including the US, Europe, and Asia, to construct a comprehensive predictive model. Learn how to handle missing data, split data for model building and testing, and assess the model's performance using key statistics such as RMSE and adjusted R-squared. Despite the challenges posed by multicollinearity and noisy stock data, our analysis provides valuable insights into the predictive power of the model. Join us as we explore the intricacies of multiple linear regression and its application in the dynamic world of stock trading.


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