Do machines beat humans? Evidence from mutual fund performance persistence

Miguel, António F.; Chen, Yi-Hao

doi:10.1016/j.irfa.2021.101913

International Review of Financial Analysis

2021

DOI: 10.1016/j.irfa.2021.101913

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Do machines beat humans? Evidence from mutual fund performance persistence

António F. Miguel

Yi-Hao Chen

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2024

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Cited by 4 publications

(1 citation statement)

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“…A great number of empirical studies are connected with performance and persistence of performance (see Vidal-García et al, 2016;Miguel & Chen, 2021). Chen et al (2010) and Ferreira et al (2012) discovered a positive mutual fund performance persistence.…”

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confidence: 99%

Mutual Funds’ Cost Persistence

Trzebiński

2022

Financial Internet Quarterly

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The research aimed to check whether investment fund managers maintain costs similarly from period to period. The research verified the hypothesis that managers maintain costs in the subsequent periods at a similar level. The study used a method based on contingency tables which are used to analyse the persistence of performance. In this study, we replaced performance with costs, assuming that managers also control these values. Costs were defined as: (1) total costs, (2) total costs minus management fees and (3) active management costs (expressed as the active expense ratio). Based on the results obtained, it should be stated that managers maintain costs at a similar level from period to period in the case of the split using the median. On the other hand, the results indicate that the costs were not maintained at a similar level in subsequent periods when broken down into quartiles. Considering the detailed results for funds divided into quartiles, it is clearly visible that most managers keep the costs close to the average value. Less frequently, costs from period to period are changed to be allocated to the extreme quartiles.

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confidence: 99%

Mutual Funds’ Cost Persistence

Trzebiński

2022

Financial Internet Quarterly

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Can quantitative investment improve market efficiency?—Evidence from China

Hu,

Xiang,

Zheng

et al. 2024

Euro Fin Management

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We investigate the impact of quantitative investment on market efficiency in China. We provide an illustrative model to show that quantitative investment enhances market efficiency. Empirically, we conduct both time‐series and cross‐sectional analysis. Regarding the time series dimension, we construct QuantDegree to measure the level of quantitative investment. We find that the performance of most anomalies decreases as QuantDegree increases. In the cross‐sectional dimension, we sort stocks into portfolios based on quant fund holdings and traditional anomalies. We find the anomaly return is lower within the groups with higher quant fund holdings, a result further confirmed by Fama–MacBeth regressions.

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Assessing the Performance of AI-Managed Portfolios

Praxmarer,

Simon

2024

SSRN Journal

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Do machines beat humans? Evidence from mutual fund performance persistence

Cited by 4 publications

References 45 publications

Mutual Funds’ Cost Persistence

Mutual Funds’ Cost Persistence

Can quantitative investment improve market efficiency?—Evidence from China

Assessing the Performance of AI-Managed Portfolios

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