CVaR.zip_CVAR_cvar计算_generallyqua_条件风险_条件风险价值

w=xlsread(); alpha=0.01; % 0.05 0.1 r=price2ret(w(:,1:end)); n=size(r,2); % 资产数 IW=ones(n,1)/n; % 初始权重值 method='hs'; e=mean(r); % 各资产期望收益率 stdev=std(r); % 各资产标准差 for i=1:n [var(i),cvar(i)]=var_cvar(r(:,i),alpha,method); % 用历史数据法求单个资产VaR和CVaR end Aeq=[ones(1,n);e]; options=optimset('largescale','off'); ER=linspace(min(e),max(e),20); % 设置预期组合收益率序列 V=cov(r); % 各资产方差协方差矩阵 % M-VaR、M-CVaR for i=1:length(ER) Beq=[1;ER(i)]; W(:,i)=fmincon(@var_cvar_min_fun,IW,[],[],Aeq,Beq,zeros(n,1),ones(n,1),[],options,alpha,method,1); nW(:,i)=fmincon(@var_cvar_min_fun,IW,[],[],Aeq,Beq,zeros(n,1),ones(n,1),[],options,alpha,method,2); sigma(i)=sqrt(W(:,i)'*V*W(:,i)); nsigma(i)=sqrt(nW(:,i)'*V*nW(:,i)); %最小VaR下的VaR和CVaR值 [VaR(i),CVaR(i)]=var_cvar(weight_profolio(W(:,i),r),alpha,method); %最小CVaR下的VaR和CVaR值 [nVaR(i),nCVaR(i)]=var_cvar(weight_profolio(nW(:,i),r),alpha,method); end % MV for i=1:length(ER) Beq=[1;ER(i)]; [mW(:,i),fv(i)]=quadprog(V,[],[],Aeq,Beq,zeros(n,1),ones(n,1),IW,options); fv(i)=sqrt(fv(i)*2); [mVaR(i),mCVaR(i)]=var_cvar(weight_profolio(W1(:,i),r),alpha,methhod); end %作图 h=figure(1); set(h,'color','w'); plot(nCVaR,ER,'-o'); hold on xlabel('CVaR'); ylabel('ER'); legend('ER-CVaR 99%','ER-CVaR 95%','ER-CVaR 90%',2);