Abstract
The uncertainty of return rate will affect the investment decision. In this paper, the ARMA-GARCH model is used to describe the data characteristics of stock returns, and the Monte Carlo method is used to construct a scenario tree containing the stock return rate and node probability. The decision rules are used to determine the nodes on the scene tree, and two mean-variance models are established based on the scene tree. Finally, four stock data are selected to optimize the portfolio of the constructed model, the results show that the scenario tree has good advantages in describing the uncertainty problem, and the constructed model is effective and feasible; the difference between the two models is analyzed and compared, which provides a reference for different investors.
Highlights
When to invest and how to make the return and risk reach a balance point satisfying investors are the main problems to be solved by portfolio
Fuzzy numbers are mainly based on past data, which can not provide a good guide for later investment decisions
In order to satisfy the portfolio with uncertain return rate and transform uncertainty into certainty, this paper combines scenario tree with the mean-variance model proposed by Markowitz[1], that is, studies the portfolio model based on scenario tree
Summary
When to invest and how to make the return and risk reach a balance point satisfying investors are the main problems to be solved by portfolio. Based on the uncertainty of returns and risks, some scholars use fuzzy numbers to describe them, and give the corresponding portfolio model, which proves the practicability of fuzzy numbers in describing uncertainty[2]. In order to satisfy the portfolio with uncertain return rate and transform uncertainty into certainty, this paper combines scenario tree with the mean-variance model proposed by Markowitz[1], that is, studies the portfolio model based on scenario tree. The ARMA-GARCH model is used to predict the rate of return, Monte Carlo simulation is used to generate new scenarios, and the scenario tree is constructed by combining the sampling method.
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