Portfolio optimization is highly valued and used by many people in the financial field. This paper analyzes asset portfolio allocation of different industries, namely, transportation industry, software semiconductor insurance industry. selected four representative assets from these then mean-variance combination model to analyze forecast return on investment. In order find optimal proportion in...

A recent line of work has studied the statistical properties of neural networks to great success from a mean field theory perspective, making and verifying very precise predictions of neural network behavior and test time performance. In this paper, we build upon these works to explore two methods for taming the behaviors of random residual networks (with only fully connected layers and no batc...

Classical derivations of mean variance preferences have all relied upon the expected utility hypothesis. Some widespread experimental studies have uncovered that the expected utility model tends to be systematically violated in practice. Such findings would lead people to doubt the empirical relevance of the literature and the practical effectiveness of the portfolio selection which employ the ...

5 We present efficient partial differential equation (PDE) methods for continuous time mean6 variance portfolio allocation problems when the underlying risky asset follows a jump-diffusion. 7 The standard formulation of mean-variance optimal portfolio allocation problems, where the 8 total wealth is the underlying stochastic process, gives rise to a one-dimensional (1-D) non-linear 9 Hamilton-J...

We analyze comparative static effects under uncertainty when a decision maker has mean-variance preferences and faces a generic, quasi-linear decision problem with both an endogenous risk and a background risk. In terms of mean-variance preferences, we fully characterize the effects of changes in the location, scale, and concordance parameters of the stochastic environment on optimal risk-takin...