Abstract
In order to solve the problem of investment style drift of open industry theme fund, this paper divides 110 industry theme stocks into ten types based on ITC classification by establishing hierarchical model, constructing judgment matrix, calculating portfolio weight vector and portfolio consistency test. On this basis, combined with the risk weight coefficient of stocks, this paper divides ten types of stocks into three risk levels, and completes the classification of open-end funds based on industry themes and risk levels. Second, this paper defines the fund risk volatility index and the fund steady return index under the new combination, establishes the style drift index using the daily cumulative return rate, and carries on the symbolic processing. The fund style drift control rate is introduced as the judgment basis, and the secondary drift index with only positive and negative properties is taken as the final judgment index. Finally, based on the theory that the total risk value of funds before and after the drift remains stable, combined with the style weight value under nine investment styles, this paper establishes a fund style drift correction model by solving the weight interval of each style after the drift and comparing it with the specific weight before the drift, to realize the correction of the drifting result of funds.
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Funding
This work was supported by The Key Project of China National Social Science Foundation (No.22AZD107) and The Science and Technology Innovation Plan Base Project of Shanxi Provincial Colleges and Universities (No.19 202204031401055).
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All authors contributed to the study conception and design. Data collection and analysis were performed by YG and ZZ. The first draft of the manuscript was written by YG and ZZ. Article review by JL and HD. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Guo, Y., Zhang, Z., Li, J. et al. Research on Identification and Correction of Fund Investment Style Drift Based on FSD Model. Comput Econ (2024). https://doi.org/10.1007/s10614-023-10534-9
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DOI: https://doi.org/10.1007/s10614-023-10534-9