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QUANT 6) - Coggle Diagram
QUANT 6)
6.3: Conditional Expectations and Bayesian Updating
Joint probability distribution
bivariate distribution, Joint PDF(1)
Contingency Table for Discrete Variables
Conditional mean
Conditional variance
Conditional covariance
Stock Price Model With Probabilities
Formulate investment problems through Bayesian updating
P(A|B) = [P(B|A)P(A)] / P(B)
6.1: Probability Distributions and Expected Values
Random variable
: discrete random variable, continuous random variable
Probability distribution
probability mass function (PMF)
probability density function (PDF)
cumulative distribution function (CDF)
Expected values
Unconditional variance
Def: the spread of a random variable around its mean :check:
Unconditional standard deviation
Unconditional mean
Covariance/correlation
Def: the direction of the linear relationship between two variables
ex with portfolio variance and weighted average :check:
Def Expected value: the probability-weighted average outcome for a random variable over an infinite number of trials
6.2: Discrete and Continuous Probability Distributions
Discrete Distributions
Discrete Uniform Distribution
Binomial Distribution
Bernoulli distribution
Probability Tree
Poisson Distribution
Continuous Distributions
Continuous Uniform Distribution
Normal Distribution
Standard Normal N(0,1)
Log-normal distribution
Logistic Distribution