FRM Part 1 - Book 2 - Quantitative Analysis

This comprehensive course, led by Prof. James Forjan, PhD (with 25+ years of business teaching experience), provides an in-depth review of key chapters from the "Quantitative Analysis" book – perfectly designed to prepare you for the FRM Part 1 exam. Master the essential quantitative concepts vital for a career in financial risk management.

The course builds a strong foundation, starting with Fundamentals of Probability, crucial for understanding advanced statistical ideas. You'll then explore Random Variables and their significance in quantitative analysis. A detailed examination of Common Univariate Random Variables and Multivariate Random Variables equips you to analyze the dynamics of financial risk factors.

Key topics covered include:

• Sample Moments: Learn how to infer population characteristics from sample data.
• Hypothesis Testing: Develop skills to rigorously test assumptions and theories.
• Linear Regression: A fundamental tool for financial modeling.
• Regression with Multiple Explanatory Variables: Understand relationships between various financial variables.
• Regression Diagnostics: Assess the validity and reliability of your regression models.
• Stationary Time Series and Nonstationary Time Series: Pivotal for financial data analysis, modeling, and financial time series forecasting.
• Measuring Return, Volatility, and Correlation: Essential for risk management and portfolio management.
• Simulation and Bootstrapping: Explore modern techniques used in risk modeling and decision-making under uncertainty.

Prof. Forjan's course blends theory with practical applications, offering a step-by-step approach to complex quantitative analysis. Whether you're new to the subject or seeking to strengthen your skills, this course will provide you with the quantitative skills needed for success in finance and risk management. Gain a deep understanding of time series analysis, regression analysis, and advanced risk modeling techniques.

Course chapters include:

1. Fundamentals of Probability
2. Random Variables
3. Common Univariate Random Variables
4. Multivariate Random Variables
5. Sample Moments
6. Hypothesis Testing
7. Linear Regression
8. Regression with Multiple Explanatory Variables
9. Regression Diagnostics
10. Stationary Time Series
11. Nonstationary Time Series
12. Measuring Return, Volatility, and Correlation
13. Simulation and Bootstrapping