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L1 09 Common Probability Distributions > e define a discrete uniform random variable, a Bernoulli random variable, and a binomial random variable; > Flashcards

e define a discrete uniform random variable, a Bernoulli random variable, and a binomial random variable; Flashcards

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L1 09 Common Probability Distributions (20 decks)

Common Probability Distributions

9 A Probability Dist. Cont V. Discreet Random Variable + Prob Functions

a define a probability distribution and distinguish between discrete and continuous random variables and their probability functions;

b describe the set of possible outcomes of a specified discrete random variable;

c interpret a cumulative distribution function;

d calculate and interpret probabilities for a random variable, given its cumulative distribution function;

e define a discrete uniform random variable, a Bernoulli random variable, and a binomial random variable;

f calculate and interpret probabilities given the discrete uniform and the binomial distribution functions;

g construct a binomial tree to describe stock price movement;

h calculate and interpret tracking error;

i define the continuous uniform distribution and calculate and interpret probabilities, given a continuous uniform distribution;

j explain the key properties of the normal distribution;

k distinguish between a univariate and a multivariate distribution, and explain the role of correlation in the multivariate normal distribution;

l determine the probability that a normally distributed random variable lies inside a given interval;

m define the standard normal distribution, explain how to standardize a random variable, and calculate and interpret probabilities using the standard normal distribution;

n define shortfall risk, calculate the safety-first ratio, and select an optimal portfolio using Roy’s safety-first criterion;

o explain the relationship between normal and lognormal distributions and why the lognormal distribution is used to model asset prices;

p distinguish between discretely and continuously compounded rates of return, and calculate and interpret a continuously compounded rate of return, given a specific holding period return;

q explain Monte Carlo simulation and describe its major applications and limitations;

r compare Monte Carlo simulation and historical simulation.

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