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【RFS】算法交易是否会减少信息获取?

[发布日期]:2018-07-12  [浏览次数]:

The Review of Financial Studies, Volume 31, Issue6

算法交易是否会减少信息获取?

作者:Brian Weller (Duke University)

摘要:我证明了在获取信息并将其纳入资产价格之间的一个重要关系。如一个突出的案例,我分析了算法交易(AT),这通常与提高价格效率相关。使用一种新的价格的信息内容度量方法和由来自美国证券交易委员会(SEC)市场数据的54,879只股票季度面板数据库,我确定了:AT活动变化每1个标准差和预定披露前一个月,价格信息量将下降9%至13%。因此,AT可以降低价格信息量,尽管它对于将可用信息转化为价格具有重要意义。

Does Algorithmic Trading Reduce Information Acquisition?

Brian Weller (Duke University)

ABSTRACT

I demonstrate an important tension between acquiring information and incorporating it into asset prices. As a salient case, I analyze algorithmic trading (AT), which is typically associated with improved price efficiency. Using a new measure of the information content of prices and a comprehensive panel of 54,879 stock-quarters of Securities and Exchange Commission (SEC) market data, I establish instead that the amount of information in prices decreases by 9% to 13% per standard deviation of AT activity and up to a month before scheduled disclosures. AT thus may reduce price informativeness despite its importance for translating available information into prices.

原文链接:https://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/15674/Efficient;jsessionid=22981A86EC725BC4424A1E9E29E9326B?sequence=5

翻译:黄涛



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