MATH 11158 : Optimization Methods in Finance Assignment 2 2022
Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: daixieit
MATH 11158 : Optimization Methods in Finance
Assignment 2
2022
Question 1 (Sortino ratio, (12 marks)). Consider a portfolio selection problem where R is the target return rate on the expected return of the portfolio. The set of feasible portfolios is denoted by x c Rn and it is to be assumed that this is a compact convex set.
1. Formulate an optimization problem for finding a feasible portfolio with the largest value of Sortino ratio. Also state, with justification, whether your objective function is convex or concave or neither. (5 marks)
2. Let sTR* denote the maximum Sortino ratio obtained by solving the problem in the first part. Show how you can compute a value < sTR* by solving a convex optimization problem. Clearly justify why the problem you are solving is convex. (7 marks)
Question 2 (Coherent Risk measures, (18 marks)). Let A > 0 be any positive scalar and consider the following function fλ : Rv (Ω) → R defined on the space Rv (Ω) of random variables supported over some scenario set Ω,
fλ := log ╱E ←e — λX ,、.
1. Check whether this function satisfies each of the four properties — monotonicity, translation equivariance, positive homogeneity, and subadditivity. (16 marks)
2. Conclude what you can say whether this function is a coherent risk measure or not. (2 marks)
Question 3 (Recourse function, (20 marks)). Let Ω be some set of scenarios and x c Rn be an arbitrary set. Consider the risk-neutral stochastic program
min cT u + E ┌o(u, 6)┐
where the recourse function o : x × Ω → R is given by
o(u, 6) = min fo (3, 6) s.t. fi (3, 6) + gi (u, 6) < hi (6), i = 1, . . . , m,
y∈Y
where y is a convex set and for every 6 e Ω and i = 1, . . . , m, gi (., 6) is a convex function of u.
1. Suppose that for every 6 e Ω and i = 0, . . . , m, fi (., 6) is a convex function of 3. Prove that o(., 6) is a convex function of u for every 6 e Ω. (6 marks)
2. Suppose that for every 6 e Ω and i = 0, . . . , m, fi (., 6) is a concave function of 3. Also assume that y is a polytope, which is a convex set with finitely many extreme points 1 . Let the extreme points of y be the vectors {3¯1 , . . . , 3¯K } for some finite integer K .
Prove that for every A > 0, the recourse function can be lower bounded by the function
φ : x × R × Ω → R which is defined as (14 marks)
m m m
φ(u, A, 6) := _ Ai hi (6) + Aigi (u, 6) + min fo (3¯k , 6) + Ai fi (3¯k , 6).
k91,...,K
i91 i91 i91
Also argue that this lower bound is a convex function of u for every A > 0 and 6 e Ω. l An extreme point is a point that cannot be written as a convex combination of two other points in the set.
Question 4 (Computational Exercise, (30 marks)). Consider the second question from tutorial 4.
1. Batch the data and create a table giving the geometric means ui,t and standard deviation 7i,t for the 8 indices (two 4 x 8 tables, one for mean, one for std.dev). (5 marks)
2. Solve the risk-neutral stochastic program as a Linear Program. (5 marks) Use the ten scenarios given below, and we assume for simplicity each of these scenarios repre- sents the scenarios for all assets i and quarters t,
Scenario |
Return rate ri,t (6j ) |
Probability p(6j ) |
61 |
ui,t _ 87i,t |
0.10 |
60 |
ui,t _ 37i,t |
0.04 |
61 |
ui,t _ 27i,t |
0.07 |
63 |
ui,t _ 1.57i,t |
0.12 |
64 |
ui,t _ 7i,t |
0.20 |
6月 |
ui,t |
0.15 |
6à |
ui,t + 7i,t |
0.05 |
6。 |
ui,t + 1.57i,t |
0.13 |
6s |
ui,t + 27i,t |
0.08 |
ui,t + 37i,t |
0.06 |
The investment cost ci for each index is
Index S&P100 S&P500 S&P600 Dow NASDAQ Russell 2000 Barron’s Wilshire
=i 0.45 1.15 0.65 0.8 1.25 1.1 0.9 0.7
and the penalty cost bt for the four quarters are, respectively, 1.3, 2.5, 1.75, 3.25. Target return rates for the different quarters are Rt (0.5) where for A e [0, 1] we define
╱ 、
3. Vary target returns as Rt (A) for A e {0, 0.05, 0.1, 0.15, . . . , 1.0} and using the optimal portfolios for the above stochastic program, plot the composition of portfolios. (5 marks)
4. Formulate a Linear Program for the risk-averse stochastic program using CVaR as the risk measure, where the term 6CV@Rβ [o(u, 6)] is added to the objective. (5 marks)
5. Solve the risk-averse problem and plot the portfolio composition by varying Rt (A) as before and 8 = 90% and 6 e {1, 10, 50}. (5 marks)
6. Comment on how your plots compare for the risk-neutral vs. risk-averse problems. (5 marks)
2022-03-22