Problem 2 (4 points) Write a Python code to simulate the Markov chain for different starting values: Hint. You can use the numpy built-in function random.choice() In [ : def simulateRating(startRating, numberosteps, P): ### Insert your code here return samplePath In [ ]: ### Test your code here: simulateRating(startRating-e, numberOfSteps-10, P-P) Table 1 0.9207 0.0709 0.0063 0.0015 0.0006 0 0 0 0.0062 0.9084 0.0776 0.0059 0.0006 0.001 0.0002 0.0001 0.0005 0.0209 0.9138 0.0579 0.0044 0.0016 0.0004 0.0005 0.0003 0.00210.040.89370.0482 0.0086 0.0024 0.0037 0.0003 0.0008 0.004 0.0554 0.8324 0.0815 0.0111 0.0145 0 0.0008 0.0027 0.0034 0.0539 0.8241 0.0492 0.0659 0 0.0029 0.0058 0.0155 0.10540.528 0.3414 0.001 0 0 0 0 Problem 2 (4 points) Write a Python code to simulate the Markov chain for different starting values: Hint. You can use the numpy built-in function random.choice() In [ : def simulateRating(startRating, numberosteps, P): ### Insert your code here return samplePath In [ ]: ### Test your code here: simulateRating(startRating-e, numberOfSteps-10, P-P) Table 1 0.9207 0.0709 0.0063 0.0015 0.0006 0 0 0 0.0062 0.9084 0.0776 0.0059 0.0006 0.001 0.0002 0.0001 0.0005 0.0209 0.9138 0.0579 0.0044 0.0016 0.0004 0.0005 0.0003 0.00210.040.89370.0482 0.0086 0.0024 0.0037 0.0003 0.0008 0.004 0.0554 0.8324 0.0815 0.0111 0.0145 0 0.0008 0.0027 0.0034 0.0539 0.8241 0.0492 0.0659 0 0.0029 0.0058 0.0155 0.10540.528 0.3414 0.001 0 0 0 0