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我正在使用quadprog两个约束（资产权重之和等于 1）进行优化，资产权重在 0 到 10% 之间。一切正常，但我不明白的结果与我的结果相反。当TAU（我的风险承受能力）最低（= 0）时，我的结果矩阵中的值应该最低。这就是说，在我最低的风险承受能力下，我将获得最低的回报。这遵循现代投资组合理论。同样，当TAU我的返回向量最高时，我的返回向量也应该最高。我知道发生了一些逆或符号错误。有人可以解释吗？

mu #return vector of our 30 assets
Dmatrix <- Q #covariance matrix
na <- 30 #number of assets
wmin <- 0 #minimum weight of an  asset
wmax <- 0.1 #maximum weight of an asset, 10% = 0.1

A <- rbind(1,-diag(na), diag(na)) #A matrix with proper diagonals for linear algebra 
b <- c(1, -rep(wmax, na), rep(wmin, na)) #b vector to store weights
print(b)
# [1]  1.0 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1 -0.1
#[26] -0.1 -0.1 -0.1 -0.1 -0.1 -0.1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
#[51]  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0

#cbind(A, b)

TAU <- seq(0, 0.5, by = 0.001) ## choose an appropriate stepsize
results <- numeric(length(TAU))
weights <- array(NA, dim = c(na, length(TAU)))
for (i in seq_along(TAU)) {
  solQP <- solve.QP(Dmat = Dmatrix,
                    dvec = TAU[i]*mu,
                    Amat = t(A),
                    bvec = b, meq = 1)
  
  ## an equivalent computation    
  ## NMOF::mvPortfolio(mu, V, wmax = 0.1, lambda = c(TAU[i], 0.5))
  
  results[i] <- solQP$value
  weights[, i] <- solQP$solution
}

results[1] #TAU = 0
#[1] 0.2214824
results[501] #TAU = 0.5
#[1] 0.2046475
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