信谊R K L ext_mon
T = 100;
%的公司
Gamma = 0.03;
A_0 = 100;
债务= 0;
symfun(ext_mon*1.03^T,ext_mon);
%的保险公司
Ai_0 = 200;
Li_0 = 100;
mu_L = 0.02;
mu_A = 0.03;
sigma_L = 0.002;
sigma_A = 0.001;
prem = symfun(R+K,[R K]);
A_T = symfun((1+gamma)*(A_0+prem),[R K]);
expAI = symfun (prem (R, K) (AI_0 +) * exp ((mu_A + (sigma_A ^ 2/2)) * T), [R K]);
expi_tilde = LI_0*exp((mu_L + (sigma_L^2/2))*T);
X = symfun(分段(L < R, L, R < = L < = K, R, L > K, R + L-K) [R K]);
Y = symfun(分段(L < R, 0, R < = L L > < = K,唐森,K, K-R), (R K));
D = symfun(分段((Y (R、K) - expAI (R、K) - expLI_tilde) > 0, Y (R、K) - expAI (R、K) - expLI_tilde, 0), [R K]);
S_T = symfun(A_T - debt - L - X - D,[R K]);
投资= symfun(S_T(R,K) + ext_mon,[R K]);
GrossReturn = symfun(投资(R,K)*1.03^T,[R K]);
利润= symfun(GrossReturn(R,K) -投资(R,K) - ext_cost(ext_mon),[R K ext_mon]);
利润
negProfit = -利润
Tn = tempname +“m”;
negProfitfun = matlabFunction“var”, {[R, K, ext_mon, L]},“文件”tn,“优化”假)
Ph = fileparts(tn);
目录(ph)
Opts = optimset(@fminsearch);
选择。MaxFunEvals = 1e5;
选择。MaxIter = 1e5;
[bestvars, negprofit] = fminsearch(negProfitfun, [0 1 0 0], opts);
利润= -negprofit;
流(利润% g (R = % g、K = % g, ext_mon = % g L = % g \ n ',利润,bestvars);