On Frequent Batch Auctions for Stocks

Ravi Jagannathan

No 26341, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: I show that frequent batch auctions for stocks have the potential to reduce the severity of stock price crashes when they occur. For a given sequence of orders from a continuous electronic limit order book market, matching orders using one second apart batch auctions results in nearly the same trades and prices. Increasing the time interval between auctions to one minute significantly reduces the severity stock price crashes. In spite of this and other advantages pointed out in the literature, frequent batch auctions have not caught on. There is a need for carefully designed market experiments to understand why, and what aspect of reality academic research may be missing.

JEL-codes: G0 G1 G12 G2 (search for similar items in EconPapers)
Date: 2019-10
New Economics Papers: this item is included in nep-des and nep-mst
Note: AP
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Published as Ravi Jagannathan, 2022. "On Frequent Batch Auctions for Stocks," Journal of Financial Econometrics, vol 20(1), pages 1-17.

Downloads: (external link)
http://www.nber.org/papers/w26341.pdf (application/pdf)

Related works:
Journal Article: On Frequent Batch Auctions for Stocks* (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:26341

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w26341

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().