Financial Economic
Essay by วรันดา อนุตรอำไพ • October 22, 2015 • Coursework • 884 Words (4 Pages) • 1,149 Views
Homework 2 MF640
1. What is the meaning of Lagrange Multiplier?
Ans The Lagrange multipliers method is one of methods for solving constrained extrema problems. Assume that we have a function f of n variables {y = f (x1,..., x n)} and we would like to find the value of x1,..., xn that will maximize or minimize this function subject to constraint g (x1,..., xn). The Lagrange multipliers method is based on setting up the new function (the Lagrange function)
L(x1,..., x n,λ) = f(x1,..., x n) +λg (x1,..., x n)
where λ is an additional variable called the Lagrange multiplier. From the Lagrange equation, the conditions for a critical point are
L´ x1 = f´x1 +λg´ x1
L´ x2 = f´x2 +λg´ x2
…
L´ xn = f´xn +λg´ xn
L´ λ = g (x1,..., xn)
Rearrange the first n equations and set it equal to zero as
λ or = λ[pic 3][pic 4]
The Lagrange multipliers can interpret that the value of optimal f will change λ unit if the exogenous variable (g(x)) change 1 unit. This show the marginal effect of changing in exogenous variable affect to the value of optimal objective variable (f). If the Lagrange multipliers are too high, the value of f will change more than the constraint which the Lagrange multiplier is low.
3. What is the optimum point of investment? If the utility function is quadratic utility function and
Return | Standard Deviation | [pic 5] | |
Investment 1 | 0.15 | 0.2 | -0.2 |
Investment 2 | 0.08 | 0.1 |
Begin with the efficient Frontier (Calculate from excel), we separate weight of investment into 11 groups.
Portfolio | Weight 1 | Weight 2 | Expected Return(%) | S.D.(port%) |
1 | 0 | 1 | 8 | 1 |
2 | 0.1 | 0.9 | 8.7 | 0.778 |
3 | 0.2 | 0.8 | 9.4 | 0.672 |
4 | 0.3 | 0.7 | 10.1 | 0.682 |
5 | 0.4 | 0.6 | 10.8 | 0.808 |
6 | 0.5 | 0.5 | 11.5 | 1.05 |
7 | 0.6 | 0.4 | 12.2 | 1.408 |
8 | 0.7 | 0.3 | 12.9 | 1.882 |
9 | 0.8 | 0.2 | 13.6 | 2.472 |
10 | 0.9 | 0.1 | 14.3 | 3.178 |
11 | 1 | 0 | 15 | 4 |
[pic 6]
After that we create the quadratic utility function as
and assume that a = 0 (it doesn’t play any role). .
However, we have to create the conditions of b and c to support the theory.[pic 7][pic 8]
Condition | Reason |
| Utility has positive relationship with return but negative relationship with S.D. (risk). |
| Positive marginal Utility ( first diff > 0) |
| Relative Risk aversion (second diff < 0 ) |
We find that the optimum point of investment depend on preference of investor (b and c). If you change value of b and c, the optimum point will change as table below
- b = 0.3 and c = -0.7
Portfolio | Expected Return | S.D. | Expected Utility | b+2c*Rp | Condition | Condition | |||
1 | 0.08 | 0.01 | 0.01945 | 0.188 | Pass | a | 0 | Assume | |
2 | 0.087 | 0.00778 | 0.02075933 | 0.1782 | Pass | b > 0 | 0.3 | Pass | |
3 | 0.094 | 0.00672 | 0.021983189 | 0.1684 | Pass | c < 0 | -0.7 | Pass | |
4 | 0.101 | 0.00682 | 0.023126741 | 0.1586 | Pass | b+2c*Rp > 0 | Table |
| |
5 | 0.108 | 0.00808 | 0.0241895 | 0.1488 | Pass | 2c < 0 | -1.4 | Pass | |
6 | 0.115 | 0.0105 | 0.025165325 | 0.139 | Pass | ||||
7 | 0.122 | 0.01408 | 0.026042428 | 0.1292 | Pass | ||||
8 | 0.129 | 0.01882 | 0.026803365 | 0.1194 | Pass | ||||
9 | 0.136 | 0.02472 | 0.027425045 | 0.1096 | Pass | ||||
10 | 0.143 | 0.03178 | 0.027878722 | 0.0998 | Pass | ||||
11 | 0.15 | 0.04 | 0.02813 | 0.09 | Pass |
- b = 0.3 and c = -0.6
Portfolio | Expected Return | S.D. | Expected Utility | b+2c*Rp | Condition |
1 | 0.08 | 0.01 | 0.0201 | 0.204 | Pass |
2 | 0.087 | 0.00778 | 0.021522283 | 0.1956 | Pass |
3 | 0.094 | 0.00672 | 0.022871305 | 0.1872 | Pass |
4 | 0.101 | 0.00682 | 0.024151493 | 0.1788 | Pass |
5 | 0.108 | 0.00808 | 0.025362428 | 0.1704 | Pass |
6 | 0.115 | 0.0105 | 0.02649885 | 0.162 | Pass |
7 | 0.122 | 0.01408 | 0.027550652 | 0.1536 | Pass |
8 | 0.129 | 0.01882 | 0.028502885 | 0.1452 | Pass |
9 | 0.136 | 0.02472 | 0.029335753 | 0.1368 | Pass |
10 | 0.143 | 0.03178 | 0.030024619 | 0.1284 | Pass |
11 | 0.15 | 0.04 | 0.03054 | 0.12 | Pass |
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