correlation coefficient and risk
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Correlation Coefficient and Risk. http://www.zenwealth.com/BusinessFinanceOnline/RR/Portfolios.html. If You Liked This, You’re Sure to Love That By CLIVE THOMPSON Published: November 21, 2008 - PowerPoint PPT PresentationTRANSCRIPT
Correlation Coefficient and Risk
http://www.zenwealth.com/BusinessFinanceOnline/RR/Portfolios.html
If You Liked This, You’re Sure to Love That By CLIVE THOMPSONPublished: November 21, 2008
THE “NAPOLEON DYNAMITE” problem is driving Len Bertoni crazy. Bertoni is a 51-year-old “semiretired” computer scientist who lives an hour outside Pittsburgh. In the spring of 2007, his sister-in-law e-mailed him an intriguing bit of news: Netflix, the Web-based DVD-rental company, was holding a contest to try to improve Cinematch, its “recommendation engine.” The prize: $1 million.
Chapter 4
Introduction to Probability
Experiment
A process that generates well-defined outcomes. On any single repetition of the experiment, one and only one of the possible experimental outcomes (or sample points) can occur.
Probability
A numerical measure of the likelihood that an event will occur.
Assigning Probabilities
1. The probability assigned to each experimental outcome must be between 0 and 1, inclusively.
0 < P(Ei) < 1 for all i2. The sum of the probabilities for all experimental
outcomes must equal 1. Given n possible outcomes:
P(E1) + P(E2) + . . . + P(En) = 1
Assigning Probabilities
Classical method – Assumes all the experimental outcomes are equally likely.
Relative frequency method – Assigns probabilities based on the frequency with which some event occurs in the data.
Subjective method – Assignment of a probability based on the degree of belief an event will occur.
Example
Which approach is being used to assign the probability in the following cases?• Political commentators believe there is a 60% chance Congress will pass health care legislation.• A baseball player has gotten 90 hits in 300 at-bats, so the probability he will get a hit at his next at-bat is 30%.• There is a 25% chance of flipping a coin twice and getting two heads.
Event
A collection of outcomes (or sample points).
Probability of an Event
The sum of the probabilities of the outcomes (sample points) in the event.
Example
Given a die with six sides, what is the probability of rolling the die and getting an even number?
xi P(xi)
1 1/62 1/63 1/64 1/65 1/66 1/6
P(E) = P(2) + P(4) + P(6) = 1/6 + 1/6 + 1/6 = 3/6 = 1/2
Complement of an Event
The complement of event A is the event consisting of all sample points that are not in A.
Probability of the Complement of an Event
P(AC) = 1 - P(A)
Venn Diagram
Event AComplement of A
Combinations of Events• Union of two events• Intersection of two events
Combinations of Events• Union of two events• Intersection of two events
Union of Two Events
The union of A and B is the event containing all outcomes (or sample points) belonging to A or B or both. The union is denoted by A U B.
Intersection of Two EventsGiven two events A and B, the intersection of A and B is the event containing the outcomes (sample points) belonging to both A and B. The intersection is denoted by A ∩ B.
Addition Law
The addition law is used to calculate the probability of the union of two events.
P(A U B) = P(A) + P(B) – P(A ∩ B)
Mutually Exclusive Events
Two events are said to be mutually exclusive if the events have no outcomes (sample points) in common.
Addition Law for Mutually Exclusive Events:P(A U B) = P(A) + P(B)
A B
Joint Probability
The probability of the intersection of two events.
Marginal Probability
The probability of an event occurring.
Cross TabulationNapoleon Dynamite
Like Dislike TotalLike 70 60 130Dislike 30 40 70Total 100 100 200
Transformers
Joint Probability TableNapoleon Dynamite
Like Dislike TotalLike .35 .30 .65Dislike .15 .20 .35Total .50 .50 1.00
Transformers
Practice
Assume event A is “likes Napoleon Dynamite” and event B is “likes Transformers”. Find the following probabilities of the events listed below:1. P(A)2. P(AC)3. P(A U B)4. P(AC U B)5. P(A U AC)6. P(A ∩ B)7. P(A ∩ AC)8. P(A ∩ BC)
Napoleon Dynamite
TransformersLike Dislike Total
Like .35 .30 .65Dislike .15 .20 .35Total .50 .50 1.00
PracticeA = “likes Napoleon Dynamite” B = “likes Transformers” 1. P(A) = .52. P(AC) = .53. P(A U B) = .5 + .65 - .35 = .84. P(AC U B) = .5 + .65 - .3 = .855. P(A U AC) = .5 + .5 = 16. P(A ∩ B) = .357. P(A ∩ AC) = 08. P(A ∩ BC) = .15
Napoleon Dynamite
TransformersLike Dislike Total
Like .35 .30 .65Dislike .15 .20 .35Total .50 .50 1.00
Conditional Probability
The probability of some event taking place given that some other event has already occurred.
P(A|B)
Probability they like Napoleon Dynamite (event A) given they like Transformers (event B) is:
P(A|B) = 70/(70+60) = 70/130 = 0.52
Conditional Probability, cont.
More generally:
)()()|(
BPBAPBAP
Practice #2
Assume event A is “likes Napoleon Dynamite” and event B is “likes Transformers”. Find the following probabilities listed below:1. P(B|A)2. P(AC|B)3. P(A|BC)4. P(AC|A)
Napoleon Dynamite
Transformers
Like Dislike TotalLike .35 .30 .65Dislike .15 .20 .35Total .50 .50 1.00
Practice #2
A = “likes Napoleon Dynamite” B = “likes Transformers” 1. P(B|A) = .35/.52. P(AC|B) = .3/.653. P(A|BC) = .15/.354. P(AC|A) = 0
Napoleon Dynamite
Transformers
Like Dislike TotalLike .35 .30 .65Dislike .15 .20 .35Total .50 .50 1.00
Independent Events
Two events are independent if the probability of A is the same regardless of whether or not B has occurred.
)()|(
)()|(
BPABPor
APBAP
Independent Events, cont.
Is liking Napoleon Dynamite independent of liking Transformers?P(A|B) = .52P(A) = .5P(A|B) ≠ P(A), so the events are not independent
Independent Events, cont.
Assume event A is “likes Napoleon Dynamite” and event B is “Birthday on odd-numbered day”. Are the events independent?
Napoleon Dynamite
Odd-numbered birthday
Like Dislike TotalYes .25 .25 .50No .25 .25 .50Total .50 .50 1.00
Independent Events, cont.
P(A|B) = .25/.50 = .50P(A) = .50Since P(A|B) = P(A) the events are independent
Multiplication Law
P(A ∩ B) = P(B)P(A|B)orP(A ∩ B) = P(A)P(B|A)
Tree Diagram
A graphic representation of a multistep experiment.
Each fork represents an experiment, each branch represents an outcome from the experiment.
Tree Diagram
Red, 2/4Red, 1/3
Black, 2/3
Black, 2/4Red, 2/3
Black, 1/3
Assume we take the four aces out of a deck of cards and we draw twice without replacement:
PracticeIf A is the probability of getting a red ace on the first draw, and B is the probability of getting a red ace on the second draw, using the multiplication rule find:1. P(A ∩ B)2. P(A ∩ BC) 3. P(AC ∩ B) 4. P(AC ∩ BC)
Practice, cont.1. P(A ∩ B) = (2/4)/(1/3) = 2/122. P(A ∩ BC) = (2/4)(2/3) = 4/123. P(AC ∩ B) = (2/4)(2/3) = 4/124. P(AC ∩ BC) = (2/4)/(1/3) = 2/12
Multiplication Rule, cont.
If events A and B are independent then P(A|B) = P(A)P(B). In this special case the multiplication rule reduces from:
P(A ∩ B) = P(B)P(A|B)to:
P(A ∩ B) = P(B)P(A)
Tree Diagram
Red, 2/4Red, 2/4
Black, 2/4
Black, 2/4Red, 2/4
Black, 2/4
Assume we take the four aces out of a deck of cards and we draw twice with replacement:
Are A and B statistically independent in this case?
Sampling and Statistical Independence
If we sample without replacement the outcomes will not be statistically independent.
However, if we are drawing from a large population the change in probability will be so small we can treat the draws as being statistically independent.
Graded Homework
P. 163, #29P. 170, #35, 37