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58 Seiten, Note: 1,3
List of Tables
List of Figures
List of Abbreviations
List of Symbols
2 Background Information
2.1 Tick Sizes
2.2 Trading Process
2.3 Price-Time Priority
2.4 Measures of Liquidity
3 Literature Review
3.1 Impact of Tick Sizes
3.1.1 Changes in Tick Size Rules
3.1.3 Fundamental Impact
4 Changes Brought About ByMiFID II
4.1 Tick Size Regime as defined in Article
4.2 Changes on the German EquityMarket
4.3 Implication for the European Equity Market
5 Empirical Design
5.1 Sample & Data
5.3 Analyzed Parameters
6 Empirical Results
6.1 Impact on Liquidity
6.1.1 Bid-Ask Spread
6.1.2 Order Book Depth
6.1.4 Price Volatility
6.2 Impact onMarket Shares
6.2.1 Market Share Distribution
6.2.2 Influence of the Regime
4.1 Tick size regime as defined in Article 49 ofMiFID II
4.2 Tick size changes bymarket segment
5.1 Changes in liquidity and turnover
6.1 Results of the DiD-regression for relative spread
6.2 Results of the DiD-regression for BestBidAsk volume
6.3 Results of the DiD-regression for turnover
6.4 Results of the DiD-regression for number of ask ticks
6.5 Results of the DiD-regression for European market shares
A.1 Subsamples according to index membership and price level
A.2 Daily average number of trades in DAX constituents
A.3 Changes in liquidity and turnover (“Medium-Term”)
A.4 Changes in liquidity and turnover (“Short-Term”)
A.5 Results of the DiD-regression for XLM for order volumes of AC25.000
A.6 Results of the DiD-regression for XLM for order volumes of AC50.000
A.7 Results of the DiD-regression for ask volume
A.8 Results of the DiD-regression for bid volume
A.9 Results of the DiD-regression for number of bid ticks
A.10 Market share development
4.1 Distribution of tick size changes by index and liquidity band
5.1 Turnover and liquidity measures
6.1 Distribution of market shares by index
A.1 Turnover and liquidity measures
Abbildung in dieser Leseprobe nicht enthalten
Abbildung in dieser Leseprobe nicht enthalten
Before the Markets in Financial Instruments Directive (MiFID I) was applied in 2007, exchanges were able to implement their own tick size without being concerned about competition, since trading was concentrated to the incumbent exchanges. The increased fragmentation and competition after the introduction of MiFID I in Europe started a race between the incumbent exchanges and alternative venues towards everfiner tick sizes in order to offer better prices and gain market share. Over the past few years, this trend has increased and caused adverse effects on the market quality. On March 3rd, 2018, MiFID II introduced a harmonized tick size regime that takes each stock’s price and liquidity into account in order to address the negative impact of the “race to the bottom” that began with MiFID I.
The tick size describes the minimum permissible price variation on a stock’s price. Nearly all stock markets around the world have introduced rules on their tick sizes with different variations of tick structures. For instance, prior to the introduction of the MiFID II regime, European markets generally used a stepwise tick system in which the tick size varied according to the price of the stock. Tick sizes play an important role in the trading process and have a direct influence on liquidity and the price formation process in a market. Harris (1994) suggests that if the tick size is too high, it would act as a binding constraint on the bid-ask spread and thus impose transaction costs on investors that are too high. On the other hand, Harris notes that setting the tick size too low may reduce the incentives for liquidity providers to submit orders and makes it easier to jump priority.
There are many empirical studies that investigate the impact of the increasing trend towards ever-finer tick sizes on market quality. There is evidence from the United States (Harris (1994); Ahn et al. (1996); Bollen & Whaley (1998); Goldstein & Kavajecz (2000); Ronen & Weaver (2001); Gibson et al. (2003)), Canada (Bacidore (1997); Porter & Weaver (1997)), Japan (Ahn et al. (2007); Ascioglu et al. (2010) and Singapore (Lau & McInish (1995)). These studies generally report that reductions in tick sizes lead to lower spreads, with mixed effects on trading volumes, market depth and other market quality factors (Chang (2014)). In contrast, there are only a limited number of studies investigating the effect of increasing tick sizes on equity trading. For instance, Hansena et al. (2017) provides a preview on the SEC “Tick Size Pilot Program” which imposes higher tick sizes on small-cap stocks in the U.S. stock market. Moreover, the Autorit´e des March´es Financiers (2018) presents the initial results of the impact of the MiFID II regime, which is mainly driven by increasing tick sizes in Europe.
The aim of this bachelor thesis is to investigate whether the introduction of the MiFID II tick size regime has achieved its desired affect of positively impacting the European equity market quality. Therefore, I will study and summarize the existing literature about the general effect of tick size changes on security markets, whereby I distinguish between tick size changes that are caused by changes in tick size rules and price movements. Furthermore, I will introduce the main concepts of the new regulatory framework Markets in Financial Instruments Directive II / Markets in Financial Instruments Regulation (MiFID II/MiFIR) with a focus on the new tick size regime and its consequences for the European market. The core of this paper is the empirical study on the effects of tick size changes brought about by MiFID II’s tick size regime on market quality, using data from the German home market Xetra. I will first investigate the overall impact of the regime on the most frequently traded stocks listed on Xetra by observing different measures of liquidity, such as transaction costs, market depth, trading volumes and price volatility. In addition, I provide separate results for the different effects of decreases and increases in tick size. Secondly, I examine the impact of the new regulatory framework and its tick size regime on the market share redistribution in Europe. This allows to determine whether the contentious exemption of systematic internalisers (SIs) from the regime creates an unfair advantage at the expense of regulated markets.
In order to determine the effects of the changes in tick sizes on the European equity trading, I will apply a difference-in-differences approach (Wooldridge (2008)) to exclude possible confounding effects. In this analysis, the treatment is the introduction of the MiFID II tick size regime in Europe, whereby the treatment group consists of DAX, MDAX and SDAX stocks that are exposed to the regime. Hence, for the control group, I will rely on the remaining stocks among this indices that do not experience a change in their tick size during the observation period, i.e., 54 trading days before and after the treatment.
This study makes two important contributions to the literature. Firstly, it provides further evidence on whether the introduction of the MiFID II tick size regime has it’s desired impact on market quality and whether it is beneficial to have government regulation of tick sizes (e.g., Autorit´e des March´es Financiers (2018)). Secondly, it adds further empirical findings on the effect of increases in tick sizes (e.g., O’Hara et al. (2014); Hansena et al. (2017)) to the literature, which predominantly focuses on decreases in tick sizes. Overall, the results show a significant increase in bid-ask spreads for most affected stocks and thus higher transaction costs for traders. Moreover, market depth which determines the market’s ability to absorb large orders seems to be negatively affected by the new regime, as the available volume at the best bid and ask is reduced. This is also true for daily trading volumes on Xetra, whereas the total The MiFID II Tick Size Regime: Impact on European Equities Trading 3 volume that is submitted to the buy and sell sides of Xetra’s order book seems not to be affected. However, the high number of tick size increases reduces the number of possible prices and thus reduces price volatility and the amount of messages that are sent to the order book. Additionally, the analysis shows that SIs indeed benefit from the exemption of the tick size regime. This indicates that MiFID II creates a new loophole for non-regulated trading platforms to attract order flow instead of fully closing all regulatory gaps and restricting non-transparent trading. Rather than stopping the “race to the bottom” and improving European market quality, my findings suggest that the introduction of a regulatory tick size regime results in a distortion of trading quality in Europe.
The remainder of the paper proceeds as follows: Section 2 provides general information on tick sizes, the trading process and the most prevalent measures of liquidity to simplify further understanding. Section 3 summaries the existing literature about the effect of tick sizes on equity trading. Section 4 introduces the essential regulatory requirements that are introduced with MiFID II/MiFIR, especially the tick size regime, and provides an insight into the impact on the European equity market. Section 5 outlines the research design of my empirical study and defines the analysed variables. Section 6 presents the empirical findings. Finally, section 7 and 8 discuss and conclude the empirical findings.
The tick size is the minimum variation in the price of a security and therefore acts as a constraint on the trading price. For instance, in the German home market Xetra, the tick size is one cent for a stock with a price between one and two euros and a daily number of transactions below ten. This means that Xetra will accept orders to trade at AC1.00 or AC1.01, but will not accept any order priced at AC1.001. Most venues around the world have adopted different tick sizes, whereby European exchanges generally use decimal-based tick sizes which vary with the price and liquidity of the respective stock as of January 3rd, 2018. Similarly, most Asian stock exchanges also impose higher tick sizes on stocks with higher prices. The United States market was the last one to convert to a decimal-based tick size regime after the U.S. Securities and Exchange Commission (SEC) ordered all stock markets to adapt to decimalization by April 9th, 2001. Before the conversion, all markets within the U.S. used ticks denominated in eights or sixteenths. Tick sizes significantly impact the trading costs payed by market participants and highly influence the overall market quality. The main purpose of tick sizes is to maintain price-time priority rules of the order book. They thus serve to protect traders who have revealed their trading interest to the market by making other traders pay an economically significant amount more to trade ahead of them (Government Office for Science (2012)).
Stock exchanges provide platforms where buyers and sellers of an asset can meet and transact. Moreover, liquidity providers, such as market makers, operate on most exchanges in order to provide inter-temporal liquidity by buying from sellers and selling to buyers at any given point in time, whereby they continuously quote quantities and prices for an asset at which they are willing to buy (bid) or sell (ask). However, liquidity providers have to be compensated for their risk of holding assets. Therefore, they charge a spread on every asset they cover, which is better known as the bid-ask spread. Moreover, most exchanges grant further compensation to liquidity suppliers in the form of rebates or refunds in order to create more incentives to supply further liquidity. An order that is submitted to the order book at a specific bid or ask price along with the quantity is called a limit order. In comparison, a market order is submitted without any price and is therefore immediately executed at the best possible price currently available. Furthermore, a market in which prices are only determined by the bid and ask quotations made by market makers and where all trades have to be executed through dealers is called a quote-driven market. An order-driven market is the opposite of a quote-driven market and displays the bid and ask prices as well as the corresponding number of shares of the individual traders.
The price-time priority is important to determine the order in which entered limit orders are executed. In general, orders are first ranked by their price, whereby orders of the same price are then ranked depending on the chronological order they were submitted into the order book. An investor can therefore post an order at a better price than the existing best price in order to get to the front of the queue. For example, if one trader enters a buy limit order at a price of AC10 at 10:00 am and another trader submits a limit order at the same price and quantity two minutes later, then the order of the first trader will be executed at the order book first. In order to gain priority, the second trader would have to enter his limit order at a better price. However, the tick rule prohibits the seconders trader to enter his order at a price of, for example, AC10.00001, otherwise he would be able to get at the front of the order book, even though the price improvement is infinitesimally small. The existing minimum tick size forces market participant to outbid the existing price by an economically significant amount to gain priority within the order book. If the existing tick size is, for instance, AC0.05, then the trader would have to enter a price of at least AC10.05 to improve the bid price.
The size of the minimum price increment has a significant effect on a security market’s liquidity, whereby the term liquidity merely describes the extent to which an asset can be quickly traded without causing changes to the asset’s price. Proponents of tick size reductions argue that smaller ticks improve market liquidity, whereas opponents argue that reductions in tick sizes adversely affect liquidity. This discussion usually focuses on the three most common measure of liquidity: bid-ask spread, market depth and turnover.
The bid-ask spread is the most prevalent measure of liquidity. It reflects the difference between the ask price and the bid price – or in other words, the bid-ask spread is the difference between the highest price that buyers are willing to pay for an asset and the lowest price that sellers are willing to accept to sell it. For example, if the bid price for a specific asset is AC9 and the ask price is AC10, then the bid-ask spread equals AC1. Moreover, the relative bid-ask spread depicts the spread in percentage terms in relation to the best ask price. In the example above, the relative spread would equal 10%. Although the bid-ask spread is not a fee that is charged by stock exchanges, it represents the hidden costs of immediate execution, which compensates market participants for providing liquidity. Therefore, a low bid-ask spread indicates higher liquidity and quality within an equity market. However, the spread is constrained by the minimum price variation and thus can not be smaller than the tick size.
Market depth generally refers to a market’s ability to absorb large market orders without causing a market impact, i.e., without impacting the asset’s price. It is measured as the number of open orders waiting at different price levels within the limit order book. Therefore, the higher the number of buy and sell orders at each price, the higher the depth in the market. High market depth allows traders to submit large orders without significantly affecting the asset’s price. On the other side, large sell and buy orders can significantly affect prices in cases where there is a poor depth of an asset. Moreover, if market depth is visible, i.e., the limit order book is displayed, traders can determine in which direction the price of an particular asset could be moving as orders are filled, updated, or canceled.
The turnover – or order book turnover – refers to the value of assets traded on a stock exchange within a specific period. It is calculated by the price of the traded stocks times the corresponding quantities. Therefore, a daily turnover of AC1 billion simply means that the total value of assets traded during the day amounts to AC1 billion. Moreover, the term turnover can be used to measure the trading volume of an individual market participant, asset or exchange. It further indicates the liquidity and quality within a market. A high turnover indicates a liquid market, where market participants are confident and trading activity is high (often referred as a “bull market”). On the other hand, low turnover indicates trader’s insecurity and that they are holding or selling their assets at a low price (often referred as a “bear market”).
This section summarizes previous studies on the impact of tick size changes on the liquidity and overall quality of equity markets. These studies are divided into two categories. The first one examines exogenous changes of tick size due to changes in tick size rules (3.1.1), whereas the second one examines endogenous changes, which occur when stock prices move from one tick size category to another (3.1.2). Finally, I present the fundamental impact of tick sizes on market quality (3.1.3).
Many previous studies investigate changes in market quality following a change in an exchange’s tick size rules. Harris (1994) was the first to predict the effect of tick size decreases from $1/8 to $1/16 at the New York Stock Exchange (NYSE) and the American Stock Exchange (AMEX). He finds that a decrease in minimum price variation reduces the bid-ask spread, displayed quotation sizes and increases turnover. Harris suggests that a lower tick size reduces the constraints on bid-ask spread and thus lowers traders’ execution costs. However, a too small tick size reduces the costs of acquiring order precedence and therefore increases the risks of submitting large orders. Quote matchers try to profit on information or free trading options provided by large orders and therefore quote their own orders on the same market side. Moreover, quote matchers may “front-run” to get their order filled ahead of the large size, if the costs of acquiring order precedence are low enough. Hence, traders reduce quotation sizes in order to reveal less information to the market and protect themselves. However, reductions in quotation size do not necessarily indicate that market depth is declining. Harris further states that trading volumes depend on the bid-ask spread because it partially determines trading costs. Smaller tick sizes and spreads are therefore associated with higher volumes.
Ahn et al. (1996) examine the switch of $1/8 to $1/16 for stocks traded between $1 and $5 at the AMEX on September 3rd, 1992. They observe a significant decline in spreads and thus trading costs. The average spread decreases from 18.4 cents in the pre-event period to 16.7 cent in the post-event period. Moreover, they find that the effect of tick size decreases is positively related to the trading frequency. While the most frequent traded stocks show a decrease of 19% in spread, the least frequent traded show a spread decline of only 4%. This is explained by the fact that fixed costs such as the market maker’s compensation costs are more efficiently allocated and informativeness of stock prices increases with the rising number of trades. However, Ahn et al. do not determine any significant effect on turnover nor on market depth. Hence, traders benefit from lower transaction costs, whereas market makers suffer from narrower spreads without significant increases in turnover. The AMEX extended its tick size rules to include all stocks on May 7th, 1997, which is examined by Ronen & Weaver (2001). Their findings are coherent with those of Ahn et al. (1996). They find that a decline in tick sizes is accompanied by a decline in spreads but does not have any significant effect on depth or turnover. Moreover, this study is the first one to observe the impact of tick changes on volatility. While spread decline and volume and depth are largely unchanged, price volatility reduces. This observation is in line with the prediction of Harris (1990) that price changes are partially caused by tick-size-induced rounding errors. Discreteness of prices may lead to ‘sticky’ prices, i.e., investors will not quote new prices unless the reservation price changes by at least one tick. This results in price deviations of at least one tick which, in turn, indicates that smaller tick sizes lead to a decline in discreteness-induced price volatility.
Shortly afterwards, on June 24th, 1997, the NYSE also started to trade it’s stocks in $1/16. Bollen & Whaley (1998) examine that quoted spreads decrease by 13% on NYSE. In contrast to the previously reviewed studies, they find that a reduction in market depth comes along with the decline in spreads. The number of shares at the prevailing bid ask quotes decreases by 38% following the shift to $1/16. In order to distinguish between these two offsetting effects, Bollen and Whaley use a market quality index calculated as the ratio of the average share depth at the prevailing bid and ask price quotes to the percentage quoted spread. The market quality index slightly increases by 1.44%, indicating a small change in market quality. Moreover, the study reveals that low-priced stocks profit the most from decreases in tick sizes. This shows that it is unlikely that the $1/8 tick size acts as a binding constraint for high-priced stocks. A study conducted by Goldstein & Kavajecz (2000) supports these findings for the NYSE. They observe a decline in quoted spreads of 14% and a reduction in quoted depth of 48%. Both effects result in a cost improvement for liquidity demanders of small trade sizes, however, they also lead to a cost deterioration for traders who submit larger orders. On July 25th, 2000, the NYSE started to convert from fractionalpricing to decimal pricing. The switch led to further reductions in bid-ask spreads as the fractional system allowed market makers to enjoy spreads and thus profits that were higher than their actual costs (Gibson et al. (2003)).
The Toronto Stock Exchange (TSE) switched from a fractional-pricing system to a decimal-pricing system on April 15th, 1996. The tick size was reduced from $1/8 to 5 cents for stocks priced above $5. Stocks priced between $3 and $5 experienced a tick size decline from 5 cents to 1 cent, whereas the tick sizes for stocks priced below $3 were unaffected. Studies on this event conducted by Bacidore (1997) and Porter & Weaver (1997) present results for stocks priced above $5 that are coherent with Ahn et al. (1996). The switch to decimalization results in a significant reduction of trading costs as measured by the bid-ask spread. However, stocks priced between $3 and $5 as well as stocks below $3 even experienced an increase in spreads. Liquidity providers may have used rents from the greater-than-$5 stocks to subsidize stocks priced below $5 prior to decimalization. The decline in spreads might have reduced these rents, which resulted in a decline of the subsidies provided to lower-priced stocks. Moreover, findings of Bacidore (1997) show that the spread reduction is greater for frequently traded and lower-priced stocks. This is in line with the prediction of Harris (1994) that the tick size is more likely to be binding for frequently traded stocks as the higher volume distributes the fixed costs component of the spreads more efficiently as well as that it is more likely to be binding for lower-priced stocks since the costs associated with a minimum tick size are larger in relative terms. In addition, Bacidore finds that depth significantly declines for greater-than-$5 stocks but again not for stocks among the lower price ranges. In consequence, trading costs decline for traders of smaller trade sizes, which is in line with previous studies. Moreover, the depth-to-spread ratio (similar to Bollen & Whaley (1998)) significantly increases for stocks above $5 and thus indicates a better market quality. Therefore, it seems that traders of large sizes are not harmed by the decimalization. Furthermore, although trading costs decline, trading activity does not increase following the switch.
Although the majority of studies conducted on tick size changes present an overall improvement of market quality, the optimal tick size might be different for different stocks. A too low tick size might result in a decline in liquidity provision which can not be compensated by the reduction in trading costs. Therefore, in October 2006 the United States Securities and Exchange Commission SEC launched the “Tick Size Pilot Program” in order to observe the impact of tick size increases on thinly traded small capitalization stocks. The study is conducted on 1200 small-cap stocks that were subject to a five-fold increase in tick size (from one cent to 5 cents). The motivation for the first increase in the minimum tick size since the decimalization in 2001 is to increase the profitability of market making in order to attract liquidity for small-cap stocks. The SEC predicts an increase in quoted depth at the best bid and ask prices as well as a decrease in price volatility, however, at the cost of increasing trading costs and the risk that trading migrates to non-displayed markets like dark pools. In fact, the working paper by Hansena et al. (2017) previews the effect of the pilot project on the examined stocks and demonstrates that the increased tick size doubles the depth at the best bid and ask prices but also increases stock return volatility by 16% and reduces average turnover by about 6%. Stocks issued by small-cap firms as well as low-priced and less frequently traded stocks are more severely impacted compared to higher-priced and more frequently traded stocks. The rationale for this is that these stocks already had a large relative tick size, so the new relative tick size is even larger. They also find that stocks with former average spreads substantially higher than the five-cent tick are also significantly affected. While the spreads themselves do not significantly change, these stocks experience the largest decrease in turnover and the smallest increase in depth. Moreover, the observed fall in trading volumes is mainly caused by the migration of order flow to non-displayed markets as predicted. O’Hara et al. (2014) also examine opposing effects of larger relative tick sizes on NYSE stock trading. Spreads do not significantly differ, however, depths are higher as liquidity providers contribute to depth at quote when the tick size is large. Nevertheless, accessing or even perceiving this available depth may be difficult as this depth only replenishes slowly after trades and, moreover, orders are more likely to be hidden.
Another way to examine the impact of minimum tick sizes on market quality is to observe stocks whose tick size changes due to moves from one tick size category to another. Bessembinder (2000) conducted a study on 765 stocks listed on Nasdaq whose tick sizes have changed as their prices passed through $10 during the year 1995. Although there was no tick size rule on Nasdaq during 1995, it was common to use $1/8 ticks for stocks priced above $10 and $1/32 for stocks priced below $10. Bessembinder suggests that lower tick sizes result in lower spreads, which is similar to the result of the studies that deal with the impact of tick size rule changes. However, he does not observe any reduction in liquidity due to the decline in spreads. Moreover, he provides evidence that return volatility is lower for stocks with lower tick sizes. Ke et al. (2004) shows that stocks with larger tick sizes are generally associated with wider bid-ask spread and higher return volatility, while trading volumes do not significantly differ for different tick sizes on the Taiwan Stock Exchange. On the Tokyo Stock Exchange, Ascioglu et al. (2010) find that the question of whether the minimum tick size acts as a binding constraint for a stock is mostly determined by characteristics such as order size, the number of trades, and price. In point of fact, volumes are more important determinants of the tick size constraint than the price. Therefore, they argue that a stock’s tick size should depend on its trading activity and price rather than only on its price. These findings are coherent with a study conducted by Aitken & Comerton- Forde (2005) which also suggests that the optimal tick size depends on both price and volume rather a simple price mechanism (Chang (2014)). Furthermore, Chung et al. (2011) present that large tick sizes on high-priced stocks have negative impact on liquidity because they frequently act as a binding constraint on bid-ask spreads. Thus, imposing smaller tick sizes on high-priced stocks significantly reduced trading costs.
Another way to examine stocks that move from one tick size category to another are stock splits. A stock split is a corporate action where a company divides the number of existing stocks in order to increase it. Although the number of shares increases, the market capitalization remains unchanged. However, a stock split leads to an immediate change in the stock’s price and thus a company might split its stock to move its share price into the range where the tick size is optimal relative to the share price in order to boost liquidity. A wider tick size enhances liquidity by increasing incentives for limit orders and market makers to provide liquidity. However, a wider relative tick size also increases the minimum quoted bid-ask spread (Angel (1997)). Wu et al. (2011) determine the impact of stock splits on transaction costs under tick sizes of $1/16 and $0.01 on NYSE-listed stocks. They focus on the 2:1 stock split which is the most common. The stock split results in a reduction of quoted dollar spread and an increase of quoted percentage spread. However, the effect of stock splits differs depending on the tick size. Percentage spreads increase by 44% with the smaller tick size of $0.01, but increase by 56% with the larger tick size of $1/16. Additionally, stock splits with tick sizes of $1/16 increase quoted depth, whereas stock splits with tick sizes of $0.01 decrease quoted depth. Therefore, the study indicates that the overall market quality worsens following a stock split. However, this study also shows that the decimalization on the NYSE improves market quality and reduces the negative impacts of stock splits as the increase in transaction cost is less under the more granular tick size regime. Schultz (2000) also conducts an study on splits of 146 Nasdaq and 89 NYSE/AMEX stocks during 1993 and 1994. He finds that the number of small shareholders who own a stock increases following the split, as minimum bid-ask spreads increase and brokers have more incentive to promote a stock. While transaction costs increase, he does not find strong evidence that the costs of market-making decline following the split. In contrast, Han (1995) examines the effect of reverse stock splits on liquidity. By increasing the stock price, the reverse split helps to change the market’s perception of the stock as it becomes less of a “penny stock”. This should result in a higher acceptance of the stock amongst institutional investors, as they are primarily concerned about the justification of their stock selection. In addition, the increase in share prices might help buyers to purchase the stock in margin and improve the marketability of the stock. Han’s results show that there is a significant decrease in bid-ask spreads, an increase in turnover and a reduction of the number of non-trading days following the reverse split.
The vast majority of empirical studies have observed a decline in spread and an increase in liquidity following a reduction in tick sizes. Nevertheless, some studies are also concerned with the effect of this reduction on quoted depth and thus the ability of the market to absorb large trades. Both kinds of studies, whether based on changes in a stock’s tick size rules or on price movements, provide results that are generally in line with Harris’ (1994) predictions. Large tick sizes are associated with large bid-ask spreads and thus higher transaction costs. If the tick size is too large, it would constantly act as a binding constraint on the bid-ask spread and thus result in unnecessarily high transaction costs on investors. However, higher tick sizes also increase market maker’s profits and therefore increase incentives to provide liquidity. In contrast, a too small tick size might reduce the displayed order sizes and quoted depth, as it lowers the costs of front-running. Liquidity providers are less willing to provide liquidity due to the increasing risk of adverse selection and quote-matching. The depth decline would especially harm traders of large order sizes. On the other hand, traders of smaller order sizes and retail investors would benefit from the lower tick sizes because bid-ask spreads decrease. This reduction in transaction costs should boost trading activity and increase the traded turnover. However, Harris might overestimate the impact on trading volumes since studies such as Ahn et al. (1996), Ronen & Weaver (2001) and Bollen & Whaley (1998) do not provide strong evidence for increases in turnover following tick size decreases.
Moreover, the effect’s magnitude of tick size changes depends on the stock’s price and trading activity. Lower-priced stocks are more heavily affected by tick size changes because the probability that a binding constraint exists is higher as the relative tick size is already large in relation to the stock price (Harris (1994)). This also applies to more frequently traded stocks because it is more likely for them that the current tick size already acts as a binding constraint for the bid-ask spread. When a stock’s tick size is binding, it indicates that it is above its competitive level and thus restricts price competition (Kurov & Zabonita (2005)). A relaxation of the binding constraint would therefore lead to a significant decline in spreads. Thus, the optimal tick size depends on it’s trading activity and price and may change over time or be different across stocks (Ascioglu et al. (2010)). Ultimately, the optimal tick size represents the trade-off between lower transaction costs due to a narrower bid-ask spread and decreased incentives to market makers to provide liquidity. A smaller tick size might be beneficial for liquid stocks, whereas a larger tick size might be optimal for illiquid stocks.
In 2004, the Markets in Financial Instruments Directive was created by the European Commission and went into effect in 2007. The directive’s main goal was to create a harmonized European regulation and increase investor protection by enhancing the market’s transparency and accessibility. Another intention was to break up the monopoly positions of the incumbent exchanges and increase competition between trading venues by introducing multilateral trading facilities (MTFs) as alternatives to the traditional stock exchanges. This, however, led to a highly fragmented market. Furthermore, the resulting fragmentation of the equity market in Europe, the use of smaller tick sizes by MTFs as well as the use of smart order routing systems, in combination with the best execution requirement, resulted in the migration of order flow to the MTFs. As a consequence, trading venues have raced to reduce their tick sizes in order to attract trading volume and gain market share. This “race to the bottom” had a negative impact on the quality of the European equity market and led to an increase in order book noise and a deterioration of the price formation process.
In order to address the problems caused by market fragmentation and dark trading as well as to extend the benefits of MiFID I to the equity market, the European Securities and Markets Authority (ESMA) introduced the new financial market regulation Markets in Financial Instruments Directive II / Markets in Financial Instruments Regulation (MiFID II/MiFIR), which had to be applied by investment firms and regulated markets from January 3rd, 2018. The main concepts that are introduced by the new directive are a new category of trading venues for non-equity instruments to be traded on a multilateral platform called the organized trading facility (OTF), a new trading obligation for derivatives and shares and a double volume cap mechanism for equity trading. OTFs are multilateral systems in which third parties can trade bonds, structured finance product, emissions allowances or derivatives (Article 4(1)(23) of MiFID II). The introduction aims to shift transactions previously categorized as off-venue onto a multilateral trading environment and thus to enhance transparency, price formation processes and investor protection. According to Article 28 of MiFIR, the trading obligation requires transactions in derivates which are subject to the EMIR clearing obliThe gation1 to be traded on regulated markets, MTFs, OTFs or equivalent third country venues2. Furthermore, the trading obligation for shares (MiFIR, Artilce 23) requires investment firms to ensure that trades they undertake in shares admitted to trading on a regulated market, or traded on a trading venue, take place on a regulated market, MTF, systematic internaliser, or an equivalent third-country trading venue. The intention is to enhance transparency, price formation processes and liquidity on lit markets by restricting OTC equity trading. The double volume cap mechanism (MiFIR, Article 5) limits the use of the reference price waiver (Article 4(1)(a) of MiFIR) and the negotiated transaction waiver (Article 4(1)(b)(i) of MiFIR) to 4% (8%) of the total value traded on a specific venue (on all venues) in order to restrict dark pool trading. Moreover, to put an end to the “race to the bottom” of tick sizes between trading venues, MiFID II introduced a harmonized tick size regime (Article 49 of MIFID II) which had to be applied to all equity trading in the EU and aims to improve the overall quality of the European equity market.
The new tick size regime is based on Article 49 of MiFID II and the Commission Delegated Regulation 2017/588 of 14 July, 2016 (see European Union (2016) and ESMA (2018)) and requires trading venues to adopt minimum tick sizes on shares, depositary receipts and exchange-traded funds (RTS 11). However, according to Recitals 2 and 3 of the Commission Delegated Regulation 2017/588 non-equity financial instruments, fixed income products and certificates are free from the MiFID II tick size regime. In order to ensure that comparable instruments are subject to the same tick size, RTS 11 defines the minimum tick, which applies to instruments depending on their price and liquidity (see Table 4.1). The tick size table contains six liquidity bands which are based on the average daily number of transactions (ADNT) executed on the most relevant market and define the minimum tick sizes allowed for each instrument in a given liquidity band. For example, if the average daily number of transactions of a share exceeds 50, then the share is subject to the third liquidity band. If the price of the share is AC20, then the minimum allowed tick is AC0.1, and if it is AC19.90, then the minimum tick is AC0.05. The average daily number of transactions values are calculated on a yearly basis and published by the ESMA. The first update for the average daily number of transaction values is expected to take place on April 1st, 2019. However, changes in values may occur any time outside the yearly update, e.g. due to corporate action. Therefore, the liquidity band for a share can change from one day to another. The application of the new tick size regime extends to all orders submitted to a trading venue, e.g. market orders, limit orders, large-in-scale orders pegged to a mid-point price as well as orders held in an order management system. However, according to Article 4(1)(a) and Article 4(1)(b) of MiFIR, the tick size regime does not apply to trades matched on the basis of a reference price or to negotiated trades. As stated in Article 49(1) MiFID II, the tick size regime has to be adopted by regulated markets. Furthermore, a cross-reference in Article18(5) MiFID II imposes that investment firms which operate MTFs or OTFs must adopt the new tick sizes as well (European Union Emissions Trading Scheme (2018)). One venue type, which does not have to follow the tick size requirements, is that of systematic internalisers (SIs). The term systematic internaliser was introduced by MiFID I in 2007 and was limited to equities transactions. Under MiFID II, SIs have an increased scope and are defined as investment firms which, on an organized, frequent and systematic basis, deal on their account by executing client orders outside a regulated market, MTF or OTF without operating a multilateral system (Article 4(1)(20) of MiFID II). Therefore, this type of venue might attract significant amount of order flow away from lit markets due to its increased price flexibility (NASDAQ (2018)). However, to reduce the unfair advantage and ensure consistency, ESMA published a Consultation Paper on November 9th 2017 proposing an amendment to Article 10 of RTS 1 in order to clarify that ”the prices published by systematic internalisers shall reflect prevailing market conditions where they are close in price, at the time of publication, to quotes of equivalent size for the same financial instrument on the most relevant market in terms of liquidity as determined in accordance with Article 4 for that financial instrument” (European Securities and Markets Authority (2017 a)).
1 The European Market Infrastructure Regulation (EMIR) states that OTC derivatives transactions that have been declared subject to a clearing obligation must be cleared centrally through a Central Counterparty authorized or recognized in the Union.
2 ESMA considers that only a third-country trading facility as a trading venue if it operates a multilateral system, is subject to authorization in accordance with the legal and supervisory framework of the third-country and is subject to supervision and enforcement on an ongoing basis (European Securities and Markets Authority (2017 b))
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