
2026 CFA Program Curriculum Level I Box Set
Description
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Discover the official resource for success on the 2026 CFA Level I exam. Get your copy of the CFA Program Curriculum now.
The 2026 CFA Program Curriculum Level I Box Set contains the content you need to perform well on the Level I CFA exam in 2026. Designed for candidates to use for exam preparation and professional reference purposes, this set includes the full official curriculum for Level I and is part of the larger CFA Candidate Body of Knowledge (CBOK).
Covering all ten core topics found on the Level I exam, the 2026 CFA Program Curriculum Level I Box Set helps you:
- Develop critical knowledge and skills essential in the industry.
- Learn from financial thought leaders.
- Access market-relevant instruction.
The set also features practice questions to assist with your mastery of key terms, concepts, and formulas. Volumes include:
- Volume 1: Quantitative Methods
- Volume 2: Economics
- Volume 3: Corporate Issuers
- Volume 4: Financial Statement Analysis
- Volume 5: Equity Investments
- Volume 6: Fixed Income
- Volume 7: Derivatives
- Volume 8: Alternative Investments
- Volume 9: Portfolio Management
- Volume 10: Ethical and Professional Standards
Indispensable for anyone preparing for the 2026 Level I CFA exam, the 2026 CFA Program Curriculum Level I Box Set is a must-have resource for those seeking the foundational skills required to become a Chartered Financial Analyst.
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Content
Table of Contents
- Title Page
- Accessibility Page
- Table of Contents
- How to Use the CFA Program Curriculum
- Quantitative Methods
- Rates and Returns
- Time Value of Money in Finance
- Statistical Measures of Asset Returns
- Probability Trees and Conditional Expectations
- Portfolio Mathematics
- Simulation Methods
- Estimation and Inference
- Hypothesis Testing
- Parametric and Non-Parametric Tests of Independence
- Simple Linear Regression
- Learning Outcomes
- 1. Introduction
- 2. Estimation of the Simple Linear Regression Model
- 3. Assumptions of the Simple Linear Regression Model
- 4. Hypothesis Tests in the Simple Linear Regression Model
- 5. Prediction in the Simple Linear Regression Model
- 6. Functional Forms for Simple Linear Regression
- Practice Problems
- Solutions
- Introduction to Big Data Techniques
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