Equilibrium Data Mining and Data Abundance

IF 7.6 1区 经济学 Q1 BUSINESS, FINANCE Journal of Finance Pub Date : 2024-10-28 DOI:10.1111/jofi.13397
JÉRÔME DUGAST, THIERRY FOUCAULT
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Abstract

We study theoretically how the proliferation of new data (“data abundance”) affects the allocation of capital between quantitative and nonquantitative asset managers (“data miners” and “experts”), their performance, and price informativeness. Data miners search for predictors of asset payoffs and select those with a sufficiently high precision. Data abundance raises the precision of the best predictors, but it can induce data miners to search less intensively for high‐precision signals. In this case, their performance becomes more dispersed and they receive less capital. Nevertheless, data abundance always raises price informativeness and can therefore reduce asset managers' average performance.
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均衡数据挖掘与数据丰富性
我们从理论上研究了新数据的激增("数据丰度")如何影响定量和非定量资产管理者("数据挖掘者 "和 "专家")之间的资本分配、他们的业绩和价格信息量。数据挖掘者寻找资产收益的预测因素,并选择那些精度足够高的预测因素。数据丰富会提高最佳预测指标的精确度,但也会促使数据挖掘者减少对高精度信号的搜索。在这种情况下,他们的业绩会变得更加分散,获得的资本也会减少。尽管如此,数据的丰富性总是会提高价格的信息量,因此会降低资产管理者的平均业绩。
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来源期刊
Journal of Finance
Journal of Finance Multiple-
CiteScore
12.90
自引率
2.50%
发文量
88
期刊介绍: The Journal of Finance is a renowned publication that disseminates cutting-edge research across all major fields of financial inquiry. Widely regarded as the most cited academic journal in finance, each issue reaches over 8,000 academics, finance professionals, libraries, government entities, and financial institutions worldwide. Published bi-monthly, the journal serves as the official publication of The American Finance Association, the premier academic organization dedicated to advancing knowledge and understanding in financial economics. Join us in exploring the forefront of financial research and scholarship.
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