The Journal of Finance publishes leading research across all the major fields of finance. It is one of the most widely cited journals in academic finance, and in all of economics. Each of the six issues per year reaches over 8,000 academics, finance professionals, libraries, and government and financial institutions around the world. The journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics.
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The Flash Crash: High‐Frequency Trading in an Electronic Market
Published: 01/25/2017 | DOI: 10.1111/jofi.12498
ANDREI KIRILENKO, ALBERT S. KYLE, MEHRDAD SAMADI, TUGKAN TUZUN
We study intraday market intermediation in an electronic market before and during a period of large and temporary selling pressure. On May 6, 2010, U.S. financial markets experienced a systemic intraday event—the Flash Crash—where a large automated selling program was rapidly executed in the E‐mini S&P 500 stock index futures market. Using audit trail transaction‐level data for the E‐mini on May 6 and the previous three days, we find that the trading pattern of the most active nondesignated intraday intermediaries (classified as High‐Frequency Traders) did not change when prices fell during the Flash Crash.
Reusing Natural Experiments
Published: 05/24/2023 | DOI: 10.1111/jofi.13250
DAVIDSON HEATH, MATTHEW C. RINGGENBERG, MEHRDAD SAMADI, INGRID M. WERNER
After a natural experiment is first used, other researchers often reuse the setting, examining different outcome variables. We use simulations based on real data to illustrate the multiple hypothesis testing problem that arises when researchers reuse natural experiments. We then provide guidance for future inference based on popular empirical settings including difference‐in‐differences, instrumental variables, and regression discontinuity designs. When we apply our guidance to two extensively studied natural experiments, business combination laws and the Regulation SHO pilot, we find that many results that were statistically significant using single hypothesis testing do not survive corrections for multiple hypothesis testing.