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  1. Eustice_Langham

    Bayes Theory

    Hi David, I have a question concerning an old video on YT concerning the Bayes Theory. The YT link is here, , my question concerns how you have arrived at the values in the formula, specifically the values in the denominator of P(U). In the formula, you have: P(G/U) = P(U/G) * P(G) / P(U)...
  2. Nicole Seaman

    CFA Level 1 CFA: Correlation, covariance and probability topics

    Session 2, Reading 9 (Part 2): This video reviews portfolio variance and covariance, where covariance is the expected cross-product. We look at correlation, which is given by the covariance divided by the product of standard deviations, and therefore standardizes the covariance into a unitless...
  3. Nicole Seaman

    YouTube T2-9c Bayes Theorem, Three-state variable

    This explores the answer to Miller's sample question in Chapter 6 of Mathematics and Statistics for Financial Risk Management. There are three types of managers: Out-performers (MO), in-line performers (MI) and under-performers (MU). The prior probability that a manager is an outperformer is...
  4. Nicole Seaman

    YouTube T2-9b Bayes Theorem, adding a bit of complexity

    Here is the question: "You are an analyst at Astra Fund of Funds. Based on an examination of historical data, you determine that all fund managers fall into one of two groups. Stars are the best managers. The probability that a star will beat the market in any given year is 75%. Ordinary...
  5. Nicole Seaman

    YouTube T2-9 Bayes Theorem: Simple test for disease

    Bayes Theorem updates a conditional probability with new evidence. In this case, the conditional probability (disease | positive test result) equals the joint probability (disease, positive test result) divided by the unconditional probability (positive test result). The question illustrated is...
  6. David Harper CFA FRM

    Bayes Theorem: two approaches

    Here is a recent question I wrote to test Bayes Theorem (which has been reintroduced into the FRM) 1. Tree Approach I have typically used a (binomial) tree to visualize this sort of problem. You start the tree with the unconditional (aka, marginal) probabilities which are the probabilities...