Intelligent algorithm of optimal investment model under stochastic interest rate and stochastic volatility

• Published in: Journal of intelligent & fuzzy systems Vol. 37; no. 1; pp. 283 - 292
• Main Authors: Luo, T., Metawa, Noura
• Format: Journal Article
• Language: English
• Published: London Sage Publications Ltd 01.01.2019
• Subjects: Algorithms; Cluster analysis; Clustering; Financing; Genetic algorithms; Interdisciplinary subjects; Investment; Machine learning; Mathematical analysis; Mathematics; Quantitative analysis; Random sampling; Support vector machines; Volatility
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-179085

Financial mathematics, an interdisciplinary subject between mathematics and finance, is the application of mathematics in the financial field, which carries mainly out the quantitative analysis and research of financial issues by mathematical theories and methods. The idea of financial mathematics is adopted to study investment. First of all, an investment risk prediction model is designed based on cluster analysis-hybrid genetic algorithm and integrated improved support vector machine, and AdaBoost-support vector machine and clustering-AdaBoost support vector machine, the model is fully analyzed and verified. Combining the ways of more than half random sampling, the imbalance state is adjusted and reduced. Then the idea of integrated learning is used to cope further the data imbalance state and improve the classifier’s attention to a few classes. Finally, the algorithm is tested. The results show that this algorithm effectively reduces the cost of accidentalinjury.