CPI、货币供给量、股指关系建模分析4(8)

%M2预测

clc,clear

x0=[625609.29... 636072.26... 649947.46... 656561.22... 663351.37... 673921.72... 674051.48... 687506.92... 696471.5... 699776.74... 710339.02... 725851.79]; n=length(x0);

lamda=x0(1:n-1)./x0(2:n) range=minmax(lamda) x1=cumsum(x0) for i=2:n

z(i)=0.5*(x1(i)+x1(i-1)); end

B=[-z(2:n)',ones(n-1,1)]; Y=x0(2:n)'; u=B\\Y

x=dsolve('Dx+a*x=b','x(0)=x0');

x=subs(x,{'a','b','x0'},{u(1),u(2),x1(1)}); yucel=subs(x,'t',[0:n-1]);

digits(6),y=vpa(x) %为了提高预测精度，先计算预测值，再显示微分方程的解yuce=[x0(1),diff(yucel)] epsilon=x0-yuce %计算残差

delta=abs(epsilon./x0) %计算相对误差

rho=1-(1-0.5*u(1))/(1+0.5*u(1))*lamda %计算级比偏差 yucel=subs(x,'t',[0:n+5])%预测未来数据 yuce=[x0(1),diff(yucel)]

%股票指数预测

clc,clear

x0=[2989.29... 3051.94... 3109.1... 2870.61...

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2592.15... 2398.37... 2637.5... 2638.8... 2655.66... 2978.83... 2820.18... 2808.08]; n=length(x0);

lamda=x0(1:n-1)./x0(2:n) range=minmax(lamda) x1=cumsum(x0) for i=2:n

z(i)=0.5*(x1(i)+x1(i-1)); end

B=[-z(2:n)',ones(n-1,1)]; Y=x0(2:n)'; u=B\\Y

x=dsolve('Dx+a*x=b','x(0)=x0');

x=subs(x,{'a','b','x0'},{u(1),u(2),x1(1)}); yucel=subs(x,'t',[0:n-1]);

digits(6),y=vpa(x) %为了提高预测精度，先计算预测值，再显示微分方程的解yuce=[x0(1),diff(yucel)] epsilon=x0-yuce %计算残差

delta=abs(epsilon./x0) %计算相对误差

rho=1-(1-0.5*u(1))/(1+0.5*u(1))*lamda %计算级比偏差 yucel=subs(x,'t',[0:n+5])%预测未来数据 yuce=[x0(1),diff(yucel)]

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