The probability of an event given that another event has occurred. Bayes' theorem reverses the conditioning.
Where you will meet it
Conditional probability comes up in 9 learning outcome notes across the FRM syllabus.
A few of them:
Fundamentals of Probability FRM Part I · Quantitative analysis
“The conditional probability of A given B is the probability that A occurs when we know that B has occurred: P(A | B) = P(A and B) ÷ P(B).”
Estimating Default Probabilities FRM Part II · Credit risk measurement and management
“For investment-grade issuers the conditional probability of default in a later year, given survival to it, tends to rise with the horizon, because today's strength may fade.”
Financial Correlation Modeling: Bottom-Up Approaches FRM Part II · Market risk measurement and management
“The conditional probability of B given A is PAB ÷ PA.”
Risk Measurement and Assessment FRM Part II · Operational risk and resilience
“If events share a cause, the joint probability, written Pjoint, uses the conditional probability: Pjoint = P(A) × P(B given A).”
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