Vol. 1 Probability Concepts Flashcards

1
Q

(probability concepts)
An investor’s concerns center on returns.
The return on a risk asset is an example of _____?

A

[a] random variable

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2
Q

(probability concepts)
Random variable [definition]

A

A quantity whose future outcomes are uncertain

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3
Q

(probability concepts)
outcome [definition]

A

a possible value of a random variable

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4
Q

(probability concepts)
event [definition]

A

a specified set out outcomes

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5
Q

(probability concepts)
probability [definition]

A

a number between 0 and 1 that measures the change that a stated event will occur

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6
Q

(probability concepts)
two defining properties of probability

A

1: the probability of any event E is a number between 0 and 1: 0 <= P(E) <= 1;

2: The sum of the probabilities of any set of mutually exclusive and exhaustive events equals 1.

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7
Q

(probability concepts)
mutually exclusive [definition]

A

means that only one event can occur at a time

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8
Q

(probability concepts)
exhaustive [definition]

A

means that the events cover all possible outcomes

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9
Q

(probability concepts)
empirical probability [definition]

A

the probability of an event as a relative frequency of occurrence based on historical data

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10
Q

(probability concepts)
subjective probability [definition]

A

a personal assessment of probability without reference to any particular data.

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11
Q

(probability concepts)
a prior probability [definition]

A

a deduction of the probability based upon logical analysis rather than on observation or personal judgment

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12
Q

(probability concepts)
estimate the probability of flipping a coin and getting exactly two heads out of five flips [empirical probability]

A

perform the experiment 100 times (five flips each time) and find you get 33. so, 33/100

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13
Q

(probability concepts)
estimate the probability of flipping a coin and getting exactly two heads out of five flips [a priori probability]

A

assume that binomial probability function applies, and calculate

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14
Q

(probability concepts)
If you have a 40% probability of passing a course, then what are the odds of passing?

A

p/(1-p = 0.4/0.6 = 0.667

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15
Q

(probability concepts)
What is the probability that the stock earns a return above the risk-free rate (event A)?

A

an unconditional probability that can be viewed as the ratio of two quantities, wit the numerator as the sum of the probabilities of stock returns above the risk-free rate. The denominator is 1, as it is the sum of the probabilities of all possible returns.

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16
Q

(probability concepts)
binomial probability distribution [formula]

A
17
Q

(probability concepts)
Multiplication rule for probability

A

The joint probability of A and B can be expressed as
P(AB) = P(A | B) P(B)

18
Q

(probability concepts)
Addition rule for probabilities

A

P( A or B) = P(A) + P(B) - P(AB)

19
Q

(probability concepts)
Multiplication rule for independent events

A

P(AB) = P(A) P(B)

20
Q

(probability concepts)
Total probability rule

A

Explains the unconditional probability of the event in terms of probabilities conditional on the scenarios

21
Q

(probability concepts)
Total probability rule for two scenarios

A
22
Q

(probability concepts)
Total probability rule for n scenarios

A
23
Q

(probability concepts)
Bayes’ Formula [description]

A

Bayes’ formula make use of the total probability rule. Bayes reverses the “given that” information. It is a rational method for adjusting our viewpoints as we confront new information.

24
Q

(probability concepts)
Bayes’ formula [calculation]

A

P( Event | Information) = [P ( Info | Event) / P(Info)] * P(Event)

25
Q

(probability concepts)
conditional probabilities of an observation are sometimes referred to as ___________

A

likelihoods

26
Q

(probability concepts)
___________ are required for updating the probability

A

likelihoods

27
Q

(probability concepts)
On the basis of your interpretation of the announcement, you update that probability. This updated probability is called the _____________ because it reflects or comes after the new information.

A

posterior probability