The second special issue on big data in finance showcases advancements in research related to data of large size, high dimension, and complex structure since the first NBER/RFS big data conference. The papers published in this next chapter address some questions that were proposed in the initial special issue in 2021. Other papers are more directly connected to recent developments in the markets. We discuss some new research directions, following on the papers published here. They include evaluating market microstructure reforms, understanding medium-frequency trading, improving missing data imputations, and deepening data valuation. We look forward to more developments to follow.

Big data is revolutionizing the finance industry and has the potential to significantly shape future research in finance. This special issue contains papers following the 2019 NBER-RFS Conference on Big Data. In this introduction to the special issue, we define the “big data” phenomenon as a combination of three features: large size, high dimension, and complex structure. Using the papers in the special issue, we discuss how new research builds on these features to push the frontier on fundamental questions across areas in finance—including corporate finance, market microstructure, and asset pricing. Finally, we offer some thoughts for future research directions.

Independent technological glitches forced two separate trading halts on different U.S. exchanges during the week of July 6, 2015. During each halt, all other exchanges remained open. We exploit exogenous variation provided by this unprecedented coincidence, in conjunction with a proprietary data set, to identify the causal impact of Designated Market Maker (DMM) participation on liquidity. When the voluntary liquidity providers on one exchange were removed, liquidity remained unchanged; when DMMs were removed, liquidity decreased market-wide. We find evidence consistent with the idea that these DMMs, despite facing only mild formal obligations, significantly improve liquidity in the modern electronic marketplace.

Security trading now fragments into more than ten almost identical stock exchanges in the United States. We show that discrete pricing is one economic force that prevents the consolidation of trading volume. The uniform one-cent tick size (minimum price variation), imposed by the SEC's Rule 612, leads to more dispersed trading for lower priced securities. When a security reverse splits, its price increases and relative tick size (one cent divided by the price) decreases. We find that reverse splits consolidate trading of securities, using securities with identical underlying fundamentals that do not reverse split as the control group.