You run PCA on a matrix of daily returns for the S&P 500 stocks over the past year (252 trading days). You notice that the eigenvalues for the 253rd to 500th principal components are all exactly zero. Is there a bug in your code? What does this mean for practical arbitrage and hedging?

你用标普 500 成分股过去 1 年（252个交易日）的日收益率矩阵做 PCA，结果发现第 253 个到第 500 个主成分的特征值全是 0。这是代码出 bug 了吗？这在实际套利对冲中意味着什么？