Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model

With the continuous development of the stock market, designing a reasonable risk identification tool will help to solve the irrational problem of investors. This paper first selects the stocks with the most valuable investment value in the future through the random forest algorithm in the nine-factor model and then analyzes them by using the higher-order moment model to find that different investors’ preferences will make the weight of the portfolio change accordingly, which will eventually make the optimal return and risk set of the composition of the portfolio change. The risk identification system designed in this paper can provide an effective risk identification tool for investors and help them make rational judgments.

Taxing Our Wealth

This paper evaluates proposals for an annual wealth tax. While a dozen OECD countries levied wealth taxes in the recent past, now only three retain them, with only Switzerland raising a comparable fraction of revenue as recent proposals for a US wealth tax. Studies of these taxes sometimes, but not always, find a substantial behavioral response, including of saving, portfolio change, avoidance, and evasion, and the impact depends crucially on design features, especially the broadness of the base and enforcement provisions. Because the US proposals are very different from any previous wealth tax, experience in other countries offers only broad lessons, but we can gain insights from closely related taxes, such as the property and the estate tax, and from optimal tax analysis of the role of wealth taxation.