基于SVM算法的金融市场投资组合与风险预测研究

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Xinyu Han, Dianqi Yao
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引用次数: 0

摘要

为了应对当前金融市场复杂的风险环境,实现投资组合优化和准确的风险预测,本文利用SVM算法进行了有效的研究。本文以股票数据为样本,实证分析了基于SVM算法的投资组合策略的风险收益和风险预测效果。与传统指数基金投资策略相比,投资组合策略的抗风险能力显著提高,风险收益也稳定在较高水平。此外,在支持向量机算法的支持下,金融市场的风险预测误差水平保持在较低的范围内。从实际应用的角度来看,基于SVM算法的金融市场投资组合选择和风险预测具有较强的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploration on Portfolio Selection and Risk Prediction in Financial Markets Based on SVM Algorithm
In order to cope with the complex risk environment of the current financial market, achieve portfolio optimization and accurate risk prediction, this paper conducts effective research using SVM algorithm. This article uses stock data as a sample to empirically analyze the risk return and risk prediction performance of investment portfolio strategies based on SVM algorithm. Compared with traditional index fund investment strategies, the risk resistance of investment portfolio strategies is significantly improved, and the risk return is also stable at a high level. In addition, with the support of SVM algorithm, the risk prediction error level in the financial market remains within a relatively low range. From the perspective of practical applications, the financial market investment portfolio selection and risk prediction based on SVM algorithm has strong feasibility.
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来源期刊
CiteScore
2.60
自引率
0.00%
发文量
24
期刊介绍: Organizations are continuously overwhelmed by a variety of new information technologies, many are Web based. These new technologies are capitalizing on the widespread use of network and communication technologies for seamless integration of various issues in information and knowledge sharing within and among organizations. This emphasis on integrated approaches is unique to this journal and dictates cross platform and multidisciplinary strategy to research and practice.
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