Tutorial lessons
01 Quantitative Methods
Learn CFA Level 2 Quantitative Methods with tutorials on multiple regression, model diagnostics, time series analysis, machine learning, and big data projects.
Lessons
Tutorial lessons
QM 1 – Basics of Multiple Regression and Underlying Assumptions
Learn the basics of multiple regression and its underlying assumptions, including OLS, partial slopes, ANOVA, adjusted R-squared, residuals, and diagnostic plots.
QM 2 – Evaluating Regression Model Fit and Interpreting Model Results
Learn the basics of multiple regression, including partial slopes, OLS assumptions, regression diagnostics, ANOVA, adjusted R-squared, and residual analysis.
QM 3 – Model Misspecification
Learn model misspecification in multiple regression, including omitted variables, heteroskedasticity, serial correlation, multicollinearity, diagnostic tests, and corrections.
QM 4 – Extensions of Multiple Regression
Learn extensions of multiple regression, including influential observations, leverage, studentized residuals, dummy variables, interaction terms, logistic regression, marginal effects, and likelihood
QM 5 – Time-Series Analysis
Learn CFA Level 2 time series analysis, including AR models, stationarity, unit roots, Dickey-Fuller tests, seasonality, ARCH, GARCH, and forecasting.
QM 6 – Machine Learning
Learn CFA Level 2 machine learning, including supervised and unsupervised learning, model training, overfitting, algorithms, and investment applications.
QM 7 – Big Data Projects
Explore CFA Level 2 Big Data Projects with worked examples on data wrangling, text processing, feature engineering, sentiment analysis, and model evaluation.