还有就是 i=1:nAssets; 我觉得 i 应该是收益样本的个数 i 的取值应该是从1到 J ，但是我该成i=1:J; 却运行错误

同时 请大家帮忙找找这个程序还存在哪些问题 谢谢

%-------------PORTFOLIO OPTIMIZATION FUNCTION UNDER CVAR MINIMIZATION----

%

function [fval,w]=CVaROptimization(ScenRets, R0, VaR0, beta, UB, LB)

%

%

% The function estimates the optimal portfolio weights that minimize CVaR

% under a given target return R0

%

%INPUTS: ScenRets: Portfolio returns matrix

% R0: The target return

% beta:The confidence level between 0.9 and 0.999

% LB, UB the upper and lower bound for the optimal weights. For example If

% you imput UB=.25 none of the stocks can consist more than the 25% of the

% portfolio.

% VaR0= the initial guess for the portfolio VaR

%

%OUTPUTS: fval = CVaR of the optimal portfolio

% w= the weights of the optimal portfolio, The last element in w

% equals the VaR of the optimal portfolio

%

%---------------- INPUT ARGUMENTS--------------------------------------

% The function accepts 6 imputs however only the two first are required

% If you dont supply the 6 argument then LB=0 (no short positions)

% If you dont supply the 5 argument then UB=1

% If you dont supply the 4 argument then beta=0.95

% If you dont supply the 3 argument VaR0 equals the HS VaR of the equally weighted

% portfolio

% Author: Manthos Vogiatzoglou, Un of Macedonia, 20/08/2008

% contact: vogia@yahoo.com

ScenRets=load('11.txt');

LB=0;

UB=0.5;

beta=0.99;

VaR0=0.05;

R0=0.25;

[J, nAssets]=size(ScenRets);

w0=[(1/nAssets)*ones(1,nAssets)];

if isempty(LB)

LB=0;

end

if isempty(UB)

UB=1;

end

if isempty(beta)

beta=.95;

end

if isempty(VaR0)

VaR0=quantile(ScenRets*w0',.95);

end

if beta>1|beta<0.9

error('The confidence level beta = 1 - alpha, should be in (0.9 0.99)')

end

if LB>=UB

error('The LB has to be smaller than UB')

end

if UB>1

error('The upper bound should be less than 1')

end

if LB<-1

error('The lower bound should be greater than -1')

end

i=1:nAssets;

% the objective function

Riskfun=@(w) w(nAssets+1)+(1/J)*(1/(1-beta))*sum(max(-w(i)*ScenRets(:,i)'-w(nAssets+1),0));

w0=[w0 VaR0];

% the (linear) equalities and unequalities matrixes

A=[-mean(ScenRets) 0];

A=[A; -eye(nAssets) zeros(nAssets,1)];

A=[A; eye(nAssets) zeros(nAssets,1)];

b=[-R0 -LB*ones(1,nAssets) UB*ones(1,nAssets)];

b=b';

Aeq=[ ones(1,nAssets) 0];

beq=[1];

options=optimset('LargeScale','off');

options=optimset(options,'MaxFunEvals',5000);

% The VaR of the optimal portfolio equals w(nassets+1)

[w,fval,exitflag,output

]=fmincon(Riskfun,w0,A,b,Aeq,beq,LB,UB,[],options)下载本文