Where Has All the Big Data Gone?
Where Has All the Big Data Gone?
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所有的大数据都去哪儿了？
DOI：
10.2139/ssrn.3164360
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Laura L. Veldkamp
中科院分区：
文献类型：
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作者：
Maryam Farboodi;Adrien Matray;Laura L. Veldkamp
随着越来越多的技术被用来处理和传输金融数据，这可以通过允许更有效地分配资本来造福社会。最近的工作支持了这一观点。 Bai、Philippon 和 Savov（2016）记录了标准普尔 500 指数股票价格预测公司未来收益的能力有所提高。我们表明，随着标准普尔 500 指数公司规模不断扩大，“价格信息量”的上升大部分可归因于规模构成效应。相比之下，普通上市公司的价格信息正在恶化。这些事实是否意味着大数据未能更有效地对资产进行定价？为了回答这个问题，我们制定了一个数据处理选择模型。我们发现，大数据的增长与企业相对规模的变化相结合，可能会引发小企业信息量的下降。该模型还揭示了大数据增长如何伪装成规模构成。这意味着不断增长的大量金融数据可能有助于更准确地定价资产。但这可能无法为绝大多数公司带来财务效率效益。
As ever more technology is deployed to process and transmit financial data, this could benefit society, by allowing capital to be allocated more efficiently. Recent work supports this notion. Bai, Philippon and Savov (2016) document an improvement in the ability of S&P 500 equity prices to predict firms' future earnings. We show that most of this "price informativeness" rise can be attributed to a size composition effect as S&P 500 firms are getting larger. In contrast, the average public firm's price information is deteriorating. Do these facts imply that big data failed to price assets more efficiently? To answer this question, we formulate a model of data-processing choices. We find that big data growth, in conjunction with a change in the relative size of firms, can trigger a decline in informativeness for smaller firms. The model also reveals how big data growth can masquerade itself as size composition. The implication is that ever-growing reams of financial data may be helping price assets more accurately. But this might not deliver financial efficiency benefits for the vast majority of firms.