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CFA Level 1 Quantitative Methods

The mathematical foundation of CFA Level I — returns, probability, statistics, and regression made exam-ready.

👤 Krawl Edutech🌐 English📚 11 sections
CFA Level 1 Quantitative Methods
$32.99

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14h 19m of lessons ≈ about 3 weeks at 45 min/day, or a focused weekend

Course content

11 sections · 38 lectures · 14h 19m total length

The course begins where the curriculum does: what an interest rate really is. This module interprets rates as required returns, discount rates, and opportunity costs, and decomposes them into the real risk-free rate plus inflation, default, liquidity, and maturity premiums. You'll then master the full family of return measures — holding period, arithmetic and geometric means, money-weighted and time-weighted returns, and annualized and continuously compounded returns — and learn exactly when each is the right tool.

Foundations: Interest Rates & Time Value of Money (incl. determinants)25:27
Rates of Return I: HPR, Arithmetic, Geometric & Harmonic Means26:17
Money-Weighted vs Time-Weighted Return30:34
Annualized Return: Non-annual & Continuous Compounding19:57
Other Return Measures: Gross/Net, Tax, Real, Leveraged15:26

About this course

This course covers the complete Quantitative Methods topic area of the CFA Level I curriculum across eleven learning modules, delivered through focused video lectures. Quantitative Methods is the load-bearing topic of Level I. The return measures, time value of money mechanics, probability tools, and statistical inference you build here are reused constantly in Fixed Income, Equity, Portfolio Management, and Derivatives - which is why this course treats every concept as a skill to be applied, not a formula to be memorized.


The course opens with the money mathematics: interest rates as required returns and risk premiums, the full family of return measures — holding period, money-weighted, time-weighted, annualized, and continuously compounded — and the time value of money applied to fixed-income and equity instruments, including implied returns, implied growth, and the cash flow additivity principle behind forward rates and no-arbitrage pricing.


It then builds the statistical core: central tendency, dispersion, skewness, and kurtosis for asset returns; probability trees, conditional expectations, and Bayes' formula; and portfolio mathematics — expected return, variance, covariance, correlation, and Roy's safety-first criterion. Simulation methods follow, covering lognormal distributions, Monte Carlo simulation, and bootstrap resampling.

The final third turns to inference and modeling. You will work through sampling methods and the central limit theorem, the complete hypothesis testing framework — Type I and Type II errors, power, parametric versus nonparametric tests, and tests of independence — before building simple linear regression from the least squares criterion through ANOVA, measures of fit, and prediction intervals. The course closes with fintech, Big Data, and machine learning applications in investment management.


How Every Lecture Is Built

Each lecture follows a consistent structure: why the concept matters, mapping to the CFA Learning Outcome Statements, core exposition built on diagrams and comparison tables, worked examples with full calculator keystrokes wherever the curriculum is quantitative, common exam traps, and a recap. Every module ends with a dedicated review session working through practice problems with full solution reasoning.


Who It's For

The material is fully aligned to the CFA Level I curriculum and suits candidates preparing for the exam as well as finance professionals seeking a rigorous, structured grounding in quantitative finance.

14h 19m of lessons ≈ about 3 weeks at 45 min/day, or a focused weekend

Course content

11 sections · 38 lectures · 14h 19m total length
About this course

This course covers the complete Quantitative Methods topic area of the CFA Level I curriculum across eleven learning modules, delivered through focused video lectures. Quantitative Methods is the load-bearing topic of Level I. The return measures, time value of money mechanics, probability tools, and statistical inference you build here are reused constantly in Fixed Income, Equity, Portfolio Management, and Derivatives - which is why this course treats every concept as a skill to be applied, not a formula to be memorized.


The course opens with the money mathematics: interest rates as required returns and risk premiums, the full family of return measures — holding period, money-weighted, time-weighted, annualized, and continuously compounded — and the time value of money applied to fixed-income and equity instruments, including implied returns, implied growth, and the cash flow additivity principle behind forward rates and no-arbitrage pricing.


It then builds the statistical core: central tendency, dispersion, skewness, and kurtosis for asset returns; probability trees, conditional expectations, and Bayes' formula; and portfolio mathematics — expected return, variance, covariance, correlation, and Roy's safety-first criterion. Simulation methods follow, covering lognormal distributions, Monte Carlo simulation, and bootstrap resampling.

The final third turns to inference and modeling. You will work through sampling methods and the central limit theorem, the complete hypothesis testing framework — Type I and Type II errors, power, parametric versus nonparametric tests, and tests of independence — before building simple linear regression from the least squares criterion through ANOVA, measures of fit, and prediction intervals. The course closes with fintech, Big Data, and machine learning applications in investment management.


How Every Lecture Is Built

Each lecture follows a consistent structure: why the concept matters, mapping to the CFA Learning Outcome Statements, core exposition built on diagrams and comparison tables, worked examples with full calculator keystrokes wherever the curriculum is quantitative, common exam traps, and a recap. Every module ends with a dedicated review session working through practice problems with full solution reasoning.


Who It's For

The material is fully aligned to the CFA Level I curriculum and suits candidates preparing for the exam as well as finance professionals seeking a rigorous, structured grounding in quantitative finance.

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