We want to model the daily movement of a particular stock (say Amazon, ticker = AMZN) using a homogeneous markov-chain. Suppose at the close of the market each day, the stock can end up higher or lower than the previous day’s close. Assume that if the stock closes higher on a day, the probability that it closes higher the next day is .65. If the stock closes lower on a day, the probability that it closes higher the next day is .45. (a) What is the 1-step transition matrix? (Let 1 = higher, 2 = lower)

(b) On Monday, the stock closed higher. What is the probability that it will close higher on Thursday (three days later)

See the explanation and attached images for the answers.

Step-by-step explanation:

a) 1-step transition matrix:

See the attached image for transition matrix.

Let the matrix be M

if the stock closes higher on a day, the probability that it closes higher the next day is 0.65.

If the stock closes lower on a day, the probability that it closes higher the next day is 0.45

if the stock closes higher on a day, the probability that it closes lower the next day is 1 - 0.65 = 0.35

if the stock closes lower on a day, the probability that it closes lower the next day is 1 - 0.45 =0.55

b)

To compute probability for 3 days later multiply matrix M (from part a) thrice i.e. M*M *M

The probability that it will close higher on Thursday is 0.566. See the transmission matrix of M³ for higher-higher. This can be interpreted as:

if the stock closed higher on Monday, the probability that it closes higher the on Thursday (three days later) is 0.566

13.33%

say 50 oranges, then 100 apples

80 are red, 20 are yellow

total fruit = 150

20chances out of 150 for yellow

20/150 = 13.33%

answer: 2/4

step-by-step explanation: