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May 5, 2026
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Quantitative Methods are an important part of the CFA® Level I exam. To perform well on this section of the exam, you need a concrete understanding of the foundational concepts and techniques.
Studying for the CFA Level I Quantitative Methods topic requires a comprehensive approach that includes both theoretical knowledge and practical application of the subject matter.
Quantitative Methods covers a wide range of content, so take each reading slowly
Focus on what the Learning Outcome Statement (LOSs) LOSs require
Practice as many questions as you can using the Qbank and mock exams and for each incorrect answer you give, identify one thing you will do differently “next time”
Throughout your prep stay organized to keep track of your progress
Learning Outcome Statements while studying for a CFA exam refer to specific skills and concepts you should possess within an exam topic whereas exam topics describe the broader body of knowledge you should have. For example, the Quantitative Methods exam topic at Level I has numerous LOSs that you’ll need to learn.
An example of a CFA LOS is “describe the use of bootstrap resampling in conducting a simulation based on observed data in investment applications.”
The statistical and analytical tools and techniques you will learn in Quantitative Methods will help you not only in the rest of Level I but as you move forward to Level II, Level III, and beyond. Whether the “number crunching” is what you see in your day-to-day tasks or not, being able to understand how various analytical methods have been performed, and being able to interpret the results is crucial to investment decision-making.
The Quantitative Methods topic represents 11% to 14% of the Level I exam, which is approximately 20 to 25 questions. This topic is tested in the morning session, within the Tools Functional Area, alongside Economics, Corporate Finance, and Financial Statement Analysis.
Candidates can find Quantitative Methods challenging. Take it slow, and focus on each LOS in turn. Remember that although there is a large amount of numerical content in this topic, on exam day it will be just as important (if not more) to be able to interpret a calculation as it is to produce the results.
Quantitative Methods is the first topic presented in the CFA curriculum, and it is recommended that you study this towards the beginning, if not first. Many of the skills learned in this topic will appear across various other topics at Level I - Financial Statement Analysis, Equities, and Fixed Income to name a few. It’s important to master these calculations in particular early to enable you to study other topics most efficiently.
Below are overviews of each Level I Quantitative Methods readings and what you are expected to learn.
The two sources of returns on an investment are capital appreciation (price changes) and capital distribution (cash flows such as interest and dividends). Here you will learn how to calculate returns for a single period, across multiple periods, on an annualized basis, and for different compounding periods including continuous compounding. Also know the various definitions of return and the components of an interest rate, as these concepts are built on throughout the CFA curriculum.
Different financial instruments have different risks and components of return, and this affects an investment manager’s decisions when constructing a portfolio. Financial indicators such as interest rates and foreign exchange rates, while not financial instruments themselves, can affect investment returns. Understand the risks listed in the reading and how investors demand returns to compensate them for these risks.
Time-weighted returns are appropriate for measuring performance when a manager does not control when cash will flow into or out of an account. Money-weighted returns are appropriate when a manager controls the cash flows. Know how to calculate returns on either basis. This reading also describes security market indexes, various index weighting methods, and how these methods affect the return on an index portfolio.
Here you will start using your financial calculator to compute present values and future values of cash flows. This is the basis for all the valuation techniques you will learn later in the Level I curriculum. Don’t worry if you are not yet familiar with the securities we use as examples in this reading. We will explain them in more detail in Economics, Equities, Fixed Income, and Derivatives.
This reading introduces statistical measures you will see throughout the CFA program. Most important are measures of central tendency and how outliers in the data affect them; and measures of dispersion, especially variance and standard deviation, which will be our most common measures of risk; and measures of symmetry, such as skewness and kurtosis, which tell us when returns do not fit a normal distribution. We also introduce measures of how two variables interact, such as covariance and correlation, which are key for diversifying portfolios.
In this reading we look at different ways data can be distributed and show how these ways affect mean and variance calculations. Focus in particular on the properties of a normal distribution, because it occurs often in the real world and we use it frequently in hypothesis testing.
Here we describe a variety of different hypothesis tests, some of which can look quite daunting at first. Focus on understanding hypothesis testing for a population mean and be prepared to do the calculations. For the more exotic kinds of hypothesis tests, it’s more important to understand what they are used for than to be able to actually carry them out. Although their calculations differ, the hypothesis testing process is the same for all of these, including the non-parametric tests.
This rather long reading introduces portfolio theory, which is the basis for the Portfolio Construction topic area. We will repeat much of this material there. While the calculations are necessary, and testable on the exam, the concepts they are there to support are quite straightforward. We state the basics of those concepts here and develop them further in Portfolio Construction.
Here we introduce three techniques for modeling investment returns: historical simulation using observed past conditions; bootstrap resampling, which involves repeated sampling from past observations; and Monte Carlo simulation, which samples from assumed distributions of data to run many simulations and aggregate the results.
The purpose of simple linear regression is to explain the variation in a dependent variable in terms of the variation in a single independent variable, then use this relationship to make predictions about the dependent variable. We describe the technique and how to calculate and interpret a variety of the statistics that are commonly associated with it.
The Quantitative Methods topic finishes with a reading that describes data science and how it is being applied in the financial industry. No calculations here, but plenty of concepts and definitions with which a financial analyst should become familiar.
For Quantitative Methods, it’s the Time Value of Money buttons (N, I/Y etc) on your BAII Plus which will come in most handy, alongside the CF function (which also calculates the present value of cashflows, but allows different cashflows each period unlike the TVoM payment (PMT) button). There are also some nifty functions for permutations and combinations (using 2nd - and 2nd +).
Answer these five CFA practice questions to test your readiness for the Level I Exam.
You can pass CFA Level I without meeting the passing score for Quantitative Methods. It is an important topic in the syllabus though so you will have to compensate by scoring more highly in other areas. You can not automatically fail the exam by failing one particular topic - although do note our warning about the Ethical and Professional Standards topic.
The Quantitative Methods topic is similar at Level I and Level II. In the Level I exam, candidates are asked to learn fundamental information whereas, in Level II, new areas get introduced such as Machine Learning and Big Data Projects and the focus shifts as you progress to the application rather than standalone technical content.
Looking for more guidance on how to prepare for Quantitative Methods? Enroll in one of our CFA Level I Premium study packages to receive expert instruction, CFA Program study materials, and more. Give yourself the best chance to prepare, practice, and perform on the CFA exam.
Written by Kaplan Schweser experts, reviewed by Craig Prochaska, CFA.
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