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Prepare for CFA Level 1: Quantitative Methods and Returns

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Prepare for CFA Level 1: Quantitative Methods and Returns

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply quantitative finance models to real-world financial data

  • Build statistical and probability frameworks for analysis

  • Perform regression, simulation, and hypothesis testing

  • Develop portfolio risk and return strategies

Details to know

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Recently updated!

April 2026

Assessments

17 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Prepare for CFA Level 1: Investment & Financial Basics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

Build job-ready skills in quantitative finance by mastering statistical methods, probability, and financial modeling used in a quantitative finance and CQF course pathways. This course helps you apply mathematical finance concepts to real-world problems in quant finance, trading, and investment analysis.

You will begin with rates and return concepts, including time value of money and return calculations used in financial decision-making. The course then progresses to statistical measures, where you will analyze distributions, dispersion, and correlation between asset returns. Next, you will explore probability, conditional expectations, and Bayes theorem to model uncertainty in financial markets. You will also work on portfolio mathematics, applying risk-return frameworks, covariance, and diversification techniques. In advanced modules, you will learn simulation methods such as Monte Carlo and bootstrapping, followed by estimation, hypothesis testing, and regression analysis used in quantitative analyst courses. The course concludes with big data techniques, including machine learning and data science applications in quantitative trading and investment analysis. By the end, you will: • Apply statistical and probability models in financial analysis • Build quantitative frameworks for portfolio risk and return • Use regression and hypothesis testing for financial decisions • Analyze financial data using quantitative methods This course is ideal for finance students, aspiring analysts, investment professionals, and anyone interested in alternative investments. Start building your expertise and make smarter investment decisions in evolving markets. Disclaimer: This course is an independent educational resource developed by Board Infinity and is not affiliated with, endorsed by, sponsored by, or officially associated with CFA Institute or any of its subsidiaries or affiliates. This course is not an official preparation material of CFA Institute. All trademarks, service marks, and company names mentioned are the property of their respective owners and are used for identification purposes only.

This module introduces the foundational concepts of interest rates, returns, and the time value of money in financial decision-making. Learners explore different return measures, compounding methods, and performance metrics used to evaluate investments. The module also examines implied returns, growth expectations, and cash flow additivity concepts applied to financial instruments.

What's included

9 videos3 assignments

9 videos•Total 71 minutes
  • Introduction•4 minutes
  • Interest Rates and Time Value of Money•5 minutes
  • Rates of Return•14 minutes
  • Money-Weighted and Time-Weighted Return•14 minutes
  • Annualized Return•10 minutes
  • Other Return Measures•8 minutes
  • Time Value of Money•6 minutes
  • Implied Return and Growth•7 minutes
  • Cash Flow Additivity•2 minutes
3 assignments•Total 120 minutes
  • Graded Quiz : — Time Value of Money in Finance•60 minutes
  • Practice Quiz : — Rates and Return•30 minutes
  • Practice Quiz : — Time Value of Money•30 minutes

This module focuses on statistical tools used to analyze financial return data. Learners examine measures of central tendency, dispersion, and distribution shape to understand return characteristics. The module also introduces correlation analysis, probability trees, portfolio mathematics, and simulation techniques used to model investment outcomes.

What's included

16 videos5 assignments

16 videos•Total 204 minutes
  • Introduction•6 minutes
  • Measures of Central Tendency and Location•15 minutes
  • Measures of Dispersion•13 minutes
  • Measures of Shape of a Distribution•15 minutes
  • Correlation between Two Variables•11 minutes
  • Properties of Correlation•10 minutes
  • Expected Value and Variance•9 minutes
  • Probability Trees and Conditional Expectations•15 minutes
  • Bayes Formula and Updating Probability Estimates•11 minutes
  • Bayes Theorem and Problems•11 minutes
  • Portfolio Expected Return and Variance of Return•9 minutes
  • Forecasting Correlation of Returns- Covariance Given a Joint Probability Function•12 minutes
  • Portfolio Risk Measures- Applications of the Normal Distribution•18 minutes
  • Lognormal Distribution and Continuous Compounding•13 minutes
  • Monte Carlo Simulation•17 minutes
  • Bootstrapping•15 minutes
5 assignments•Total 180 minutes
  • Graded Quiz : — Statistical Measures of Asset Returns•60 minutes
  • Practice Quiz : — Statistical Measures•30 minutes
  • Practice Quiz : — Probability Trees and Conditional Expectations•30 minutes
  • Practice Quiz : — Portfolio Mathematics•30 minutes
  • Practice Quiz : — Simulation Methods•30 minutes

This module explores statistical estimation and hypothesis testing techniques used in financial research and analysis. Learners examine sampling methods, the central limit theorem, and estimation procedures for population parameters. The module also covers parametric and nonparametric tests used to evaluate financial hypotheses and relationships

What's included

12 videos4 assignments

12 videos•Total 97 minutes
  • Sampling Methods•12 minutes
  • Non-Probability Sampling, Sampling from Different Distributions•12 minutes
  • Central Limit Theorem and Inference•7 minutes
  • Bootstrapping and Empirical Sampling Distributions•4 minutes
  • Hypothesis Tests for Finance•9 minutes
  • Test Concerning Differences between Means with Dependent Samples•8 minutes
  • Test Concerning the Equality of Two Variances•6 minutes
  • Parametric versus Nonparametric Tests•8 minutes
  • Nonparametric Tests•8 minutes
  • Hypothesis Testing Practice Problems•9 minutes
  • Parametric Test of a Correlation•6 minutes
  • Non-Parametric Test of Correlation- The Spearman Rank Correlation Coefficient•8 minutes
4 assignments•Total 150 minutes
  • Graded Quiz : — Estimation and Inference•60 minutes
  • Practice Quiz : — Sampling and Estimation•30 minutes
  • Practice Quiz : — Hypothesis Testing•30 minutes
  • Practice Quiz : — Parametric and Non-Parametric Tests of Independence•30 minutes

This module introduces regression analysis as a tool for modeling relationships between financial variables. Learners examine the assumptions of linear regression, parameter estimation, hypothesis testing, and model evaluation techniques. The module also explores prediction methods and functional forms used in financial regression models.

What's included

9 videos3 assignments

9 videos•Total 72 minutes
  • Introduction to Linear Regression•13 minutes
  • Assumptions of the Simple Linear Regression Model•10 minutes
  • Hypothesis Tests in the Simple Linear Regression Model•9 minutes
  • Hypothesis Testing practice problems•6 minutes
  • Hypothesis Testing of Individual Regression Coefficients•5 minutes
  • ANOVA and Standard Error of Estimate in Simple Linear Regression•8 minutes
  • ANOVA practice problems•6 minutes
  • Prediction Using Simple Linear Regression and Prediction Intervals•7 minutes
  • Functional Forms for Simple Linear Regression•9 minutes
3 assignments•Total 120 minutes
  • Graded Quiz : — Regression testing•60 minutes
  • Practice Quiz : — Simple Linear Regression•30 minutes
  • Practice Quiz : — Analysis using Linear Regression•30 minutes

This module explores the role of big data and advanced analytical tools in modern financial analysis. Learners examine how fintech, artificial intelligence, and machine learning techniques support quantitative investment strategies. The module also introduces data science approaches such as data processing, visualization, and text analytics used in financial data analysis.

What's included

4 videos2 assignments

4 videos•Total 41 minutes
  • Introduction•7 minutes
  • How Is Fintech used in Quantitative Investment Analysis?•14 minutes
  • Advanced Analytical Tools- Artificial Intelligence and Machine Learning•11 minutes
  • Tackling Big Data with Data Science•8 minutes
2 assignments•Total 90 minutes
  • Graded Quiz: Big Data Techniques•60 minutes
  • Practice Quiz : — Introduction to Big Data Techniques •30 minutes

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Board Infinity
261 Courses•428,749 learners

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Frequently asked questions

A quantitative finance course focuses on applying mathematics, statistics, and data analysis to financial markets. It is ideal for learners aiming for roles in quant finance, trading, or risk analysis.

Yes, this course starts with foundational concepts like rates of return and gradually progresses to advanced topics such as regression and simulation.

This course covers core concepts similar to a CQF course, including probability, statistical modeling, and financial mathematics used in professional quant roles.

Basic knowledge of mathematics and finance is helpful, but key concepts are explained step-by-step for learners transitioning into quantitative finance.

Yes, it includes important topics aligned with CFA Level 1 quantitative methods such as probability, hypothesis testing, and regression.

You will learn the foundational quantitative methods used in trading, including statistical analysis and simulation techniques.

The course introduces tools like Excel, basic Python concepts, and statistical frameworks used in quantitative analysis.

Yes, it builds essential skills required in quantitative analyst courses, including data analysis, modeling, and financial decision-making.

Yes, it covers key topics from mathematical finance such as probability models, expected returns, and risk measurement.

Yes, it supports financial modeling by teaching regression, forecasting, and quantitative analysis techniques.

Monte Carlo simulation helps model uncertainty and predict financial outcomes, which is widely used in quant finance and risk management.

Yes, you will receive a certificate upon completion, which adds value to your profile in quantitative finance roles.

It focuses on practical applications such as portfolio analysis, risk modeling, and data-driven decision-making.

Basic exposure to coding is helpful but not mandatory, as concepts are explained with practical examples.

You can explore roles such as quantitative analyst, risk analyst, financial analyst, or quantitative developer in finance and fintech industries.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,