Repeat the last part of Problem 58 for the matrix M = 3 − 1 − 1 3 . Note in Section 6 [see (6.15)) that, for the given matrix A, we found A 2 = − I, so it was easy to find all the powers of A. It is not usually this easy to find high powers of a matrix directly. Try it for the square matrix M in equation 11.1 . Then use the method outlined in Problem 57 to find M 4 , M 10 , e M .
Repeat the last part of Problem 58 for the matrix M = 3 − 1 − 1 3 . Note in Section 6 [see (6.15)) that, for the given matrix A, we found A 2 = − I, so it was easy to find all the powers of A. It is not usually this easy to find high powers of a matrix directly. Try it for the square matrix M in equation 11.1 . Then use the method outlined in Problem 57 to find M 4 , M 10 , e M .
Repeat the last part of Problem 58 for the matrix
M
=
3
−
1
−
1
3
.
Note in Section 6 [see (6.15)) that, for the given matrix A, we found
A
2
=
−
I,
so it was easy to find all the powers of A. It is not usually this easy to find high powers of a matrix directly. Try it for the square matrix M in equation
11.1
.
Then use the method outlined in Problem 57 to find
M
4
,
M
10
,
e
M
.
Starting with the finished version of Example 6.2, attached, change the decision criterion to "maximize expected utility," using an exponential utility function with risk tolerance $5,000,000. Display certainty equivalents on the tree.
a. Keep doubling the risk tolerance until the company's best strategy is the same as with the EMV criterion—continue with development and then market if successful.
The risk tolerance must reach $ ____________ before the risk averse company acts the same as the EMV-maximizing company.
b. With a risk tolerance of $320,000,000, the company views the optimal strategy as equivalent to receiving a sure $____________ , even though the EMV from the original strategy (with no risk tolerance) is $ ___________ .
Calculus for Business, Economics, Life Sciences, and Social Sciences (14th Edition)
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