dc.contributor.author | Farboodi, Maryam | |
dc.date.accessioned | 2021-02-16T18:01:52Z | |
dc.date.available | 2021-02-16T18:01:52Z | |
dc.date.issued | 2020-08 | |
dc.identifier.issn | 0002-8282 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/129767 | |
dc.description.abstract | “Big data” financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others’information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others’ demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies. However, in the long run, as data processing technology becomes increasingly advanced, both types of data continue to be processed. Two competing forces keep the data economy in balance: data resolve investment risk, but future data create risk. The efficiency results that follow from these competing forces upend two pieces of common wisdom: our results offer a new take on what makes prices informative and whether trades typically deemed liquidity-providing actually make markets more resilient. | en_US |
dc.language.iso | en | |
dc.publisher | American Economic Association | en_US |
dc.relation.isversionof | 10.1257/AER.20171349 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | American Economic Association | en_US |
dc.title | Long-Run Growth of Financial Data Technology | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Farboodi, Maryam and Laura Veldkamp. “Long-Run Growth of Financial Data Technology.” American Economic Review, 110, 8 (August 2020): 2485-2523 © 2020 The Author(s) | en_US |
dc.contributor.department | Sloan School of Management | en_US |
dc.relation.journal | American Economic Review | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2021-02-09T15:13:53Z | |
dspace.orderedauthors | Farboodi, M; Veldkamp, L | en_US |
dspace.date.submission | 2021-02-09T15:14:55Z | |
mit.journal.volume | 110 | en_US |
mit.journal.issue | 8 | en_US |
mit.license | PUBLISHER_POLICY | |
mit.metadata.status | Complete | |