Regression Models
Predicting the future based on the past.
Regression Analysis is a statistical method used to estimate the relationship between a dependent variable (like a stock's return) and one or more independent variables (like interest rates, GDP growth, or oil prices). The most common form is Linear Regression, which fits a straight line through data points to predict outcomes.
Simple vs. Multiple Regression
In CAPM (Capital Asset Pricing Model), this formula describes a stock's return (Y) based on the market's return (X). Alpha (α) is the excess return, and Beta (β) is the sensitivity.
Key Takeaways
Basis for factor investing and risk management.
R-Squared measures how well the model explains the data.
Overfitting is a common risk in complex models.
Regression Models
Predicting the future based on the past.
Regression Analysis is a statistical method used to estimate the relationship between a dependent variable (like a stock's return) and one or more independent variables (like interest rates, GDP growth, or oil prices). The most common form is Linear Regression, which fits a straight line through data points to predict outcomes.
Simple vs. Multiple Regression
In CAPM (Capital Asset Pricing Model), this formula describes a stock's return (Y) based on the market's return (X). Alpha (α) is the excess return, and Beta (β) is the sensitivity.
Key Takeaways
Basis for factor investing and risk management.
R-Squared measures how well the model explains the data.
Overfitting is a common risk in complex models.
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