Optimization of blockchain investment portfolio under artificial bee colony algorithm

To improve the security of asset securitization and reduce investment risk, the risk reduction methods of asset securitization are investigated. First, the risk and return of investment are measured using multiple methods, and several portfolio methods are introduced. Second, there are problems of fraud risk, underlying assets, and asymmetry risk when assets are being transformed into securitization. The blockchain technology is used to reduce the probability of these risks and improve investment security. Finally, the artificial bee colony (ABC) algorithm is applied to the optimization of the blockchain investment portfolio. Since the traditional ABC algorithm can only solve the problem of single-objective optimization, an external population is constructed to improve it. The results show that the improved ABC algorithm can simultaneously optimize multiple features in the investment portfolio, reduce the error of investors when making decisions, and improve the balance between investment returns and risks. At the same time, after the algorithm is evaluated, it is found that the accuracy and practicality have been improved to a certain extent. Also, it is proved that the ABC algorithm can solve the problem of portfolio optimization, improve the security of asset securitization, and ensure the balance of investment return and risk to a certain extent. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This study investigates risk reduction methods of asset securitization using various approaches, including portfolio methods and blockchain technology, to enhance investment security. It proposes an improved ABC algorithm for portfolio optimization and demonstrates its capability to simultaneously optimize multiple features in the investment portfolio, thereby reducing investor errors and improving the balance between investment returns and risks.