Hart proved the difficulty of deriving general comparative statics in portfolio weights. Instead, we derive new comparative statics for the distribution of payoffs: A is less risk averse than B iff A's payoff is always distributed as B's payoff plus a non-negative random variable plus...

This paper considers the portfolio problem for high dimensional data when the dimension and size are both large.We analyze the traditional Markowitz mean-variance (MV) portfolio by large dimension matrix theory, and find the spectral distribution of the sample covariance is the main factor to...

This paper proposes the spectral corrected methodology to estimate the Global Minimum Variance Portfolio (GMVP) for the high dimensional data. In this paper, we analysis the limiting properties of the spectral corrected GMVP estimator as the dimension and the number of the sample set increase to...