Question

对于CAPM（资本资产定价模型）的非线性测试，我想在假设beta（bi）和期望收益（x）是条件变量（z）的线性函数的情况下测试参数稳定性

继Ghysels（1998）之后，我想使用GMM在以下时刻条件下计算参数： GMM moment conditions

这是我的代码：

gl <- function(theta, x) { 

  g_PF <- function(a) {

      aa1 <- (x[,a] * z[,1]) - ((z[,1:3] %*% matrix(theta[(a*3-2):(a*3)],3,1)) * z[,1])
      aa2 <- (x[,a] * z[,2]) - ((z[,1:3] %*% matrix(theta[(a*3-2):(a*3)],3,1)) * z[,2])
      aa3 <- (x[,a] * z[,3]) - ((z[,1:3] %*% matrix(theta[(a*3-2):(a*3)],3,1)) * z[,3])

      ab1 <- (((z[,1:3] %*% matrix(theta[(a*3-2):(a*3)],3,1)) * z[,1]) - ((z[,1:3] %*% matrix(bi[((a+2)/3), 1:3], 3, 1) * z[,1:3] %*% matrix(theta[19:21],3,1)) * z[,1]))
      ab2 <- (((z[,1:3] %*% matrix(theta[(a*3-2):(a*3)],3,1)) * z[,2]) - ((z[,1:3] %*% matrix(bi[((a+2)/3), 1:3], 3, 1) * z[,1:3] %*% matrix(theta[19:21],3,1)) * z[,2]))
      ab3 <- (((z[,1:3] %*% matrix(theta[(a*3-2):(a*3)],3,1)) * z[,3]) - ((z[,1:3] %*% matrix(bi[((a+2)/3), 1:3], 3, 1) * z[,1:3] %*% matrix(theta[19:21],3,1)) * z[,3]))

      mocon <- cbind(aa1, aa2, aa3, ab1, ab2, ab3)
      return(mocon)
    }

  g_M <- function(b) {

        bb1 <- (x[,b] * z[,1]) - ((z[,1:3] %*% matrix(theta[(b*3-2):(b*3)],3,1)) * z[,1])
        bb2 <- (x[,b] * z[,2]) - ((z[,1:3] %*% matrix(theta[(b*3-2):(b*3)],3,1)) * z[,2])
        bb3 <- (x[,b] * z[,3]) - ((z[,1:3] %*% matrix(theta[(b*3-2):(b*3)],3,1)) * z[,3])

        mocon1 <- cbind(bb1, bb2, bb3)
        return(mocon1)

        }

  #Moment conditions:

  MSL <- g_PF(a = 1)
  MSM <- g_PF(a = 2)
  MSB <- g_PF(a = 3)
  MHL <- g_PF(a = 4)
  MHM <- g_PF(a = 5)
  MHB <- g_PF(a = 6)
  MM <- g_M(b = 7)

  gmat <- cbind(MSL, MSM, MSB, MHL, MHM, MHB, MM)
  return(gmat)
}

ress <- gmm(g = gl,x = x,  rep(0,21))
summary(ress)

函数gl用于生成力矩条件，而期望的输出将是21个参数的向量（3个参数 - 两个调节变量+常数 - 用于六个测试投资组合+市场投资组合）。

当我运行我的代码时，我收到以下错误消息：

Error in AA %*% t(X) : requires numeric/complex matrix/vector arguments
In addition: Warning message:
In ar.ols(x, aic = aic, order.max = order.max, na.action = na.action,  :
  model order:  1 singularities in the computation of the projection matrix results are only valid up to model order 0

这是我的回报，beta和conditoning变量的数据：

https://1drv.ms/f/s!AuPlGq9-jRlpgzVR12selaXgL8s8

使用GMM在R中进行非线性测试

0 个答案: