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October 14, 2025
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.
The Time Value of Money
Organizing, Visualizing, and Describing Data
Probability Concepts
Common Probability Distributions
Sampling and Estimations
Hypothesis Testing
Introduction to Linear Regression
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
When you get to Hypothesis Testing focus on what the Learning Outcome Statement (LOSs) LOSs require
Ensure you are reading the SchweserNotes and watching the Module Videos to understand the previous two readings before you attempt Hypothesis Testing
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 6%-9% of the Level I exam, which is approximately 10-16 questions. This topic is tested in the morning session, within the Tools Functional Area, alongside Economics and Financial Statement Analysis.
Candidates can find Quantitative Methods challenging, especially the later readings which build upon each other. 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 analyze the results of hypothesis testing for example, as it is to produce the results.
The content in the first reading of Quantitative Methods will crop up throughout the Level I syllabus so ensure you feel comfortable with this before moving on.
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 (in particular the first reading ‘The Time Value of Money’) will appear across various other topics at Level I - Financial Statement Analysis, Equity Investments, 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.
Quantitative Methods Volume 1 readings moved to “pre-requisite” status, which means it will not be tested but available for you as needed.
CFA prerequisite readings are meant to help you meet the prerequisite knowledge requirements for the CFA Program.
Below are overviews of each Level I Quantitative Methods readings and what you are expected to learn.
The Time Value of Money reading covers the calculations for future and present values of cashflows, which are essential techniques we see come up over and over again throughout the Level I curriculum (e.g. within valuations in Equity Investments). The impact of different compounding periods is also covered here.
In the Organizing, Visualizing, and Describing Data reading we look at different types of data and ways - mostly graphical - to present data, as well as how to analyze the data given. There are a few key terms that are defined in this reading such as skewness, kurtosis, and correlation which you will also see appear in later curriculum readings and other topics.
Probability is a subject which many people have studied before - even if not since high school, so we find candidates are often comfortable with the concept of what this reading covers. It can get more challenging as we delve into different problems and the equations needed to find the appropriate answer, for example, Baye’s formula, which is used to update prior probabilities for a given event, in response to the arrival of new information.
A probability distribution describes the probabilities of all the possible outcomes for a random variable. Here you will learn about various distributions, with binomial and normal distributions being key. The reading introduces confidence intervals (the probability that a normally distributed random variable lies inside a given interval) and equips you with the tools necessary to calculate this for various scenarios. There is a brief mention of Monte Carlo simulation to close the reading.
What is a ‘random’ sample? This reading begins by looking at different ways to select samples (including biases affecting these choices) and contains some key calculations, developing on the confidence intervals of the previous reading and introducing standard error of the sample mean.
The Hypothesis Testing reading builds upon the previous reading’s content to lay out the standard hypothesis testing procedures. Once this has been memorized, you can pair this with your knowledge of confidence intervals, standard errors etc. to either calculate or analyze given hypothesis testing results.
Quantitative Methods ends with a standalone reading introducing simple linear regression, which involves two variables: an independent and dependent variable. By the end of the reading you will be able to construct or interpret a simple regression model as well as analyze assumptions given.
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 +).
Learn about the TI BAII Plus, including how to set it up, store and retrieve results, do combination and permutation and calculations, calculate the time value of money, and more.
Answer these five 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.
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