CFA Level 1 Reading 3: Probability Concepts - Complete CRASH COURSE 2023 - Wall Street Notes

Wall Street Notes - CFA® Level 1 Crash course: wallstreetnotes.com
Full course library: wallstreetnotes.com/p/level-1...
Topics covered in this video:
Quantitative Methods CFA® Level 1 2023
Reading 3: Probability Concepts
Learning Outcome Statements covered in this reading:
define a random variable, an outcome, and an event
identify the two defining properties of probability, including mutually exclusive and exhaustive events, and compare and contrast empirical, subjective, and a priori probabilities
describe the probability of an event in terms of odds for and against the event calculate and interpret conditional probabilities
demonstrate the application of the multiplication and addition rules for probability
compare and contrast dependent and independent events
calculate and interpret an unconditional probability using the total probability rule
calculate and interpret the expected value, variance, and standard deviation of random variables
explain the use of conditional expectation in investment applications
interpret a probability tree and demonstrate its application to investment problems
calculate and interpret the expected value, variance, standard deviation, covariances, and correlations of portfolio returns
calculate and interpret the covariances of portfolio returns using the joint probability function
calculate and interpret an updated probability using Bayes formula
identify the most appropriate method to solve a particular counting problem and analyze counting problems using factorial, combination, and permutation concepts.
CFA Level 1 Reading 3: Probability Concepts - Complete CRASH COURSE 2022 - Wall Street Notes
0:00 Introduction
1:03 2 PROPERTIES OF PROBABILITY
7:02 EXPECTED VALUES The probability-weighted average of possible outcomes
8:19 VARIANCE & STDEV USING PROBABILITIES
8:58 COVARIANCE & CORRELATION
10:25 COVARIANCE USING HISTORICAL VALUES
11:28 PORTFOLIO VARIANCE
12:39 COVARIANCE USING PROBABILITIES
13:38 BAYE'S THEOREM Used to update old probabilities when new information is given

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