在此背景下，本文通过对历史股票数据的分析和建模，设计了一种用于股票收益率风险预测的模型。本文基于风险价值理论，采用GARCH模型和最大熵模型两种方法，从不同角度研究了股票收益率的风险预测模型。研究结果表明，该模型的预测结果具有较高的精度和可靠性。
题目：股票收益率的风险预测模型研究及应用
摘要：
股票市场的风险管理一直是金融领域中最重要的议题之一，在股票投资中，一方面需要获取收益，另一方面也必须关注风险。在此背景下，本文通过对历史股票数据的分析和建模，设计了一种用于股票收益率风险预测的模型。本文基于风险价值理论，采用GARCH模型和最大熵模型两种方法，从不同角度研究了股票收益率的风险预测模型。研究结果表明，该模型的预测结果具有较高的精度和可靠性。在应用中，本文将该模型应用到股票交易中，通过交易模拟实验，验证了该模型在股票风险管理中的实用性和可行性。
关键词：股票收益率、风险预测模型、风险价值理论、GARCH模型、最大熵模型
Abstract:
Risk management in the stock market has always been one of the most important issues in the financial field. In stock investment, on the one hand, it is necessary to obtain returns, on the other hand, it is also necessary to pay attention to risks. In this context, this paper analyzes and models historical stock data, and designs a model for predicting stock return risks. Based on the theory of value at risk, this paper uses two methods, GARCH model and maximum entropy model, to study the risk prediction model of stock return from different perspectives. The research results show that the model has high accuracy and reliability in prediction. In application, this paper applies the model to stock trading. Through trading simulation experiments, the practicality and feasibility of the model in stock risk management are verified.
Keywords: stock return, risk prediction model, value at risk theory, GARCH model, maximum entropy model
