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Santos-Alamillos, F. J., Thomaidis, N. S., Usaola-Garcia, J., Ruiz-Arias, J. A., & Pozo-Vazquez, D. (2017). Exploring the Mean-Variance Portfolio Optimization Approach for Planning Wind Repowering Actions in Spain. Renewable Energy, 106, 335-342.
https://doi.org/10.1016/j.renene.2017.01.041

has been cited by the following article:

• TITLE: Application and Effect Analysis of Financial Engineering Tools in Portfolio Optimization

  AUTHORS: Fangyuan Cai

  KEYWORDS: Financial Engineering Tools, Portfolio Optimization, Kalman Filtering

  JOURNAL NAME: Modern Economy, Vol.15 No.5, May 14, 2024

  ABSTRACT: The purpose of this study is to deeply discuss the application of financial engineering tools (FET) in portfolio optimization, and analyze its effect in detail. Through the comprehensive application of modern investment theory and advanced mathematical modeling technology, this study discusses the potential advantages of FET in improving portfolio efficiency, reducing risks and adapting to market fluctuations. This study focuses on the application of Kalman filtering (KF) algorithm in portfolio optimization. The algorithm provides a powerful and effective tool for investors by estimating and adjusting the market state in real time. The advantage of KF algorithm lies in dealing with noise, missing data and dynamic weight adjustment, thus improving the efficiency of portfolio, especially in the rapidly changing market environment. By adopting advanced risk measurement and model, investors can identify and measure the risk of portfolio more comprehensively and formulate more effective hedging and insurance strategies. This helps to reduce the overall risk level of portfolio and improve the robustness of asset allocation when market volatility increases. The application of FET in portfolio optimization provides investors with more comprehensive and accurate decision support.