Relative Tick Size and the Trading Environment

Abstract

Recent proposals to raise the tick size on small stocks bring attention to the role played by market structure in shaping the trading environment and ultimately in capital formation. In this paper, we look at the how the relative tick size influences liquidity and the biodiversity of trader interactions in the market. Using unique order-level Our empirical analysis of relative tick size effects focuses on one such fundamental structure issue, and in this concluding section we discuss the implications of our results for the current debate regarding raising minimum tick sizes for small firms.Advocates of raising the tick size stress the linkage from tick size to market maker profits. Two avenues are suggested for how these profits would then drive additional investor trading. First, more profitable market making could lead to an increase in liquidity provision for the stocks, which would attract additional volume from investors who are wi!ling to trade liquid stocks but shy away from illiquid ones. Second, the higher profitability of market making operations at sell-side firms could lead to nrc>e>T<>r coverage, enhanced promotion by and increased willingness of companies to go public. In particular, the argument is that the fall in tick sizes to decimals has both reduced incentives to post limit orders and dramaticaUy reduced compensation to market making in those stocks. The resulting illiquidity has made such stocks unattractive to investors and, combined with the fall in analyst coverage of small firms, also made listing new stocks unattractive to issuers. Raising the minimum tick size addresses these concerns by improving the trading environment for small stocks.Our analysis essentially follows the first linkage above (tick size to liquidity to volume) by looking at the trading environment for stocks with different relative tick sizes. In our analysis, stocks in our Gl sample face relative tick si:zes that are approximately 10 times larger than those of the control stocks, G2 face relative tick sizes that are 4 times larger, and G3 stocks face relative ticks that are 2 times larger. Because our Maureen O'Hara (mo19@cornell.edu) and Gideon Saar (gs25@cornell.edu) are from the Johnson Graduate School of Management, Cornell University, and Zhuo Zhong (zz225@cornell.edu) is from the Department of Economics, Cornell University. We thank Viral Acharya, Simon Gervais, Charles Jones, and Andrew Lofor helpful comments on a presentation of this project at FINRA's Economic Advisory Committee meeting. NYSE provided us with data and financial support for analyzing the data. All conclusions are those of the authors and do not represent the views of the NYSE. 1 analysis controls for other factors that also affect liquidity (e.g., market capitalization, industry, investor clientele, and volatility), we can extract the effects of tick size on liquidity and the liquidity provision process. Does a larger relative tick size increase liquidity? We find little evidence of this. Percentage spreads are not significantly di...

One size fits all? High frequency trading, tick size changes and the implications for exchanges: market quality and market structure considerations

“…Hagströmer and Nordén (2013) demonstrate that the share of trading activity attributed to HFT strategies increases with the minimum tick size. O'Hara et al (2015) show that, in contrast to the recent SEC proposals, in today's ''high frequency'' markets, there is little evidence that stocks with a higher relative tick size (a large tick size relative to the stock price) have greater liquidity. Equally, Yao and Ye (2015) show that a large relative tick size decreases liquidity but increases HFT liquidity provision.…”

“…A third set of studies relies on assets that are cross-listed, that is assets that are trading on more than one exchange where the change affects trading in only one of the exchanges (see Lin et al 2009;Oppenheimer and Sabherwal 2003). This is also related to a more recent set of studies concerned with the association of the minimum tick size regulations and the incidence of HFT, in addition to the interaction of market systems (see Bartlett and McCrary 2013;Mahmoodzadeh and Gençay 2014;O'Hara et al 2014). …”

“…The majority of published papers use NYSE and NASDAQ TAQ data (see Chou and Chung 2006;Jones and Lipson 2001;Johnson et al 2014;O'Hara et al 2014), and some more recent studies use the national best bid and offer (NBBO) US data. There are also variations in the sample time period.…”

“…A further area of interest originates from the interaction of HFT with alternative trading systems (or dark pools). To this end, Bartlett III and McCrary (2013) and O'Hara et al (2015) show that there is often a trade-off between HFT and trading in alternative venues: reducing the tick size leads to an increase in HFT (that is, an increase in displayed liquidity) and a decrease in trading in alternative trading systems (that is, a decrease in un-displayed liquidity). The authors further argue that the recent proposal to increase the minimum tick size for small capitalization stocks may potentially harm organized exchanges and HFT and shift trading to alternative trading systems.…”

“…Some papers use odd-lot trades as a proxy for individuals' transactions and investigate time of the week and of the year price anomalies (see Dyl and Maberly 1992;Lakonishok and Maberly 1990). After the advent of high frequency trading however, the assumption that odd-lots are mainly originated by individual investors is inappropriate; accordingly, O'Hara et al (2014) show that odd-lot trading is partly attributable to HFT and they document a bias in empirical studies which ignore odd-lots. Developing O'Hara et al (2014), Johnson et al (2014) compare circumstantial odd-lots and intentional odd-lots.…”