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The Performance Forecast Index of Innovation Investment Fund Based on Animal Algorithm

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DOI: 10.23977/ferm.2022.050301 | Downloads: 16 | Views: 739

Author(s)

Jianyu Zhou 1, Shujing Feng 2, Benxing Tian 1

Affiliation(s)

1 School of Finance and Economics, Tibet University, Lhasa, Tibet, China
2 School of Cultural Industry Management, Shanghai Institute of Visual Arts, Shanghai, China

Corresponding Author

Jianyu Zhou

ABSTRACT

At the point when individuals decide to put resources into protections or other gamble resources, there are two issues that they are generally worried about: the normal profit from resources and the dangers. In the beginning phase of the improvement of monetary hypothesis, how to decide the gamble and return of speculation is an issue that financial backers need to earnestly settle. Economists have been studying how to use quantitative methods to continuously improve the investment theory and the practical operation of the theory. These studies have made great progress in the theory and application of portfolio theory. At present, many meaningful attempts have been made in the research and practical application of portfolio theory in China, but none have achieved good results. In order to better solve the problem of performance prediction indicators after investment funds, this paper deliberately introduces the current most popular animal algorithm-ant colony algorithm. The ant colony algorithm can well predict the investment results, with an accuracy rate of more than 95% and a failure rate of less than 3%. It solves the problems that investors are most concerned about. I hope to play a certain role in promoting the development of China's investment industry.

KEYWORDS

Animal Algorithm, Innovation Investment, Investment Forecast, Performance Forecast

CITE THIS PAPER

Jianyu Zhou, Shujing Feng and Benxing Tian, The Performance Forecast Index of Innovation Investment Fund Based on Animal Algorithm. Financial Engineering and Risk Management (2022) Vol. 5: 1-11. DOI: http://dx.doi.org/10.23977/ferm.2022.050301.

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