Fragmentation in Financial Markets: The Rise of Dark Liquidity

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1 Fragmentation in Financial Markets: The Rise of Dark Liquidity Sabrina Buti Global Risk Institute April 7 th 2016

2 Where do U.S. stocks trade? Market shares in Nasdaq-listed securities Market shares in NYSE-listed securities NYSE 0% BATS 10% Direct Edge 11% Other SRO 2% NASDAQ 25% Nasdaq Venue TRF BATS 10% Direct Edge 10% Other SRO 2% NASDAQ 11% BX 3% PSX 1% ARCA 8% NYSE TRF 3% BX 2% PSX 1% NYSE Venue BATS Direct Edge Other Venues ARCA 11% NYSE 17% NASDAQ TRF 33% NASDAQ TRF 38% NYSE TRF 2% Off-exchange trading is reported through the two Trade Reporting Facilities(TRF). NASDAQ data represents shares matched on the NASDAQ book plus shares reported to the Consolidated Tape. Uses September 2013 data.

3 What about Canadian stocks? Source: Bank of Canada Review, Autumn 2013.

4 And European stocks? Source: Fioravanti and Gentile, 2011, The impact of fragmentation on European stock exchanges, Consob.

5 Evolution of US market structure 1994: Nasdaq collusion 2007: Reg NMS implemented. Increased competition 2009/2010: Increased focus on HFT and latency in markets 1997: Order handling rules 2005: Reg NMS approved 2010: Flash crash 2000: Decimalization 2001/2: Autoquote on NYSE. Beginning of algorithmic trading 2002: ECN consolidation : Response to flash crash. Equity market structure reviews.

6 State of the market Source: Barclays research.

A new world: Trading complexity 16 13 16 10 29 50

7 A new world: Trading complexity Lit Venues Dark Venues Source: Nasdaq

8 Dark liquidity Internalized flows Dark Pools Hidden liquidity on lit exchanges Total other venues 18% MARKET SHARE Source: SEC Total dark pools 13% Total ECNs 2% Lit exchanges 67% Source: CFA Institute 2012

Market Share (%) Dark trading 40 35 30 25 20 Total Dark Liquidity Number of

9 Market Share (%) Dark trading Total Dark Liquidity Number of Securities with over 40% Dark Market Share ,

10 What are dark pools? Alternative Trading Systems that do not provide their best-priced orders for inclusion in the consolidated quotation data Provide anonymity and opacity pretrade to institutions Derivative pricing, mid-quote, inside, at-quotes (controversial)

11 Dark pools relevance

12 Dark pools classification (I) Dark Pools classification based on: market model [periodic vs continuous crossing, blind vs advertisement based,...] ownership [traditional exchange vs single or a group of brokerdealers] access [buy or sell side, both retail vs institutional,...]

13 Dark pools classification (II) Independent/Agency pools Bank/Brokers pools Market Maker pools Consortium-Sponsored pools Exchange-Based dark pools

6% LEVEL 0.38% 3.09% 0.98% Bank / Broker Pools CITI MATCH 0.54% GOLD. SACHS SIGMA X 1.41% UBS PIN ATS 1.09% CS CROSSFINDER 1.88% BARCLAYS LX 1.

14 Dark pools volume: Dec 2012 Percentage of Consolidated US Volume Independent / Agency Pools ITG POSIT 0.77% INSTINET CBX 0.58% INSTINET VWAP 0.08% CVGX VORTEX 0.23% CVGX MILLENNIUM 0.26% KNIGHT MATCH 0.8% LIQUIDNET 0.24% LIQUIDNET H % Consortium-Sponsored Pools BIDS TRADING 0.6% LEVEL 0.38% 3.09% 0.98% Bank / Broker Pools CITI MATCH 0.54% GOLD. SACHS SIGMA X 1.41% UBS PIN ATS 1.09% CS CROSSFINDER 1.88% BARCLAYS LX 1.41% DB SUPER X 1.01% MS-POOL 0.76% Market Maker Pools GETMATCHED 0.77% KNIGHT LINK 1.4% 2.17% 8.1% Source: Rosenblatt Securities Inc. Total USA: 14.34%

15 A few questions about dark pools Who wants to hide in the dark?

16 Some theory: The starting point Price uncertainty: MARKET ORDER INFORMED TRADERS Lit market One single price Market maker UNINFORMED TRADERS KYLE (ECTA, 85) The informed trader faces a trade-off between VOLUME and price impact: the higher the volume, the larger the impact.

17 Ye (WP, 2011): Informed go dark The informed trader still faces a trade-off between VOLUME and price impact. Incentives to move to the DP, where there is NO PRICE IMPACT. BUT the more you trade on the DP, the lower is the probability of execution. Go dark as long as it is profitable to do so! INFORMED TRADERS Lit market One single price Market maker UNINFORMED TRADERS Execution uncertainty: UNKNOWN IMBALANCE Derivative Price Dark Pool (DP): Crossing Network UNINFORMED TRADERS

18 Zhu (RFS, 2013): Informed go lit Informed traders tend to trade in the same direction. INFORMED TRADERS Execution uncertainty: UNKNOWN IMBALANCE They crowd on the heavy side of the market, and face a higher execution risk in the DP, relative to uninformed traders. Lit market Bid-ask Dealer Derivative Price Dark Pool (DP): Crossing Network Informed traders prefer lit exchanges!

19 To summarize Ye (WP, 2011): DPs attract informed traders, harm price discovery and decrease adverse selection on the lit market DPs have incentives to get rid of informed traders Zhu (RFS, 2013): Exchanges are more attractive to informed traders, and DPs are more attractive to uninformed traders Adding a DP could concentrate price-relevant info on the exchange and improve price discovery, but reduce exchange liquidity (spread)

20 Now to the data! Buti, Rindi and Werner (WP, 2011): DP activity in the U.S. results in improved price efficiency based on short-term volatility measures Comerton-Forde and Putnins (JFE, 2015): in Australia, orders executed in the dark are less informed that orders executed in the lit dark trades increase adverse selection on the main market, worsening market quality low levels of dark trading are benign or even beneficial for informational efficiency, but high levels are harmful

21 A few questions about dark pools Who wants to hide in the dark? Price improvement in dark pools? Should we be afraid of the dark?

22 Better prices in dark pools? Source: Nasdaq analysis

23 SEC Reg NMS Rule 612 Introduced on August 29, 2005 Established minimum price variation for lit markets: $0.01 for stocks priced higher than $1 $ for stocks priced at $1 and below Dark markets are exempt from Rule 612 provided: execute less than 5% of the volume do not display their orders So Rule 612 allows for: broker-dealer internalization dark trading in sub-penny

24 Queue jumping Exchange A 2 Dark pool or Internalization a 5 a 4 A 1 v B 1 a 3 a 2 a 1 b 1 b 2 Sub-penny trade B 2 Market order b 3 b 4 b 5

25 How does sub-penny trading work? In theory Rule 612 states that no market participant can accept, rank, or display orders priced in sub-pennies. In practice On Jan the SEC fined a dark pool operator $14.4 million for accepting and ranking hundreds of millions of orders priced in increments smaller than one cent that were submitted to his dark pool.

26 Growth in sub-penny trades (US) Source: Nanex

27 Canadian experiment On October 15, 2012, Canadian regulators made providing liquidity in the dark more expensive The new rule specifies the improvement that dark liquidity providing orders must offer relative to the best lit bid and offer: At least 1 cent (1/2 if the lit spread is 1 cent) Applies to marketable orders below 5,000 shares or $100,000 in value Does not affect midpoint orders and block trading Dark markets moved from fractional pricing (90/10 and 80/20) to midpoint Source: IIROC

28 Canadian experiment: Outcome Dark pool volume dropped by 42%. Source: IIROC

29 What is going on? Dark trading activity is significantly reduced: Volume on Alpha IntraSpread, on which dark trading interacts with a segregated flow of retail orders, is most strongly impacted when these market-making opportunities are reduced Volume on TCM, in which dark participants trade mainly to minimize information leakage and market impact, is less impacted Consistently, active retail traders and passive High Frequency Traders show the greatest reduction in dark trading

30 Successful experiment? Reduction in dark volume without meaningful price improvement Minimal market-wide impact as most measures of market quality showed no deterioration However Talis and Putnins (JFE, forthcoming) analyze the same experiment and find that midpoint crossing systems do not benefit market quality, but dark limit order markets are beneficial to market quality

31 Why separate? There are two main reasons why trades execute on alternative trading systems at fractions of penny: Undercutting orders posted at the top of public limit order books (queue-jumping& mid-crossing) The execution system of some dark pools and brokerdealers internalization systems follows a derivative pricing rule: trades execute at the midpoint of the primary market inside spread (mid-crossing) Mid-crossing therefore does not necessarily include only undercutting and could potentially mix different trading strategies

32 Back to the U.S. October 1st November 30th, 2010 (42 trading days) Stratified sample of 90 Nasdaq and 90 NYSE listed common stocks, sorted into terciles by market capitalization and price as of the end of 2009 Sub-penny trading is further divided into: Mid-crossing Queue-jumping

33 Example in TAQ data: IBM ID Symbol Date Time Exchang e Price Size Rounded Price Price Improvement Type of Sub- Penny 1 IBM :00:00 K 135, ,76 0 None 2 IBM :00:00 K 135, ,77 0 None 3 IBM :00:00 K 135, ,84 0 None IBM :00:00 17 IBM :00:00 T 135, ,84 0 None 18 IBM :00:01 D 135, ,64 0 None 19 IBM :00:01 D 135, ,74 0,0025 Queue-Jumping 20 IBM :00:01 N 135, ,67 0 None IBM :00:01 28 IBM :00:03 B 135, ,76 0 None 29 IBM :00:03 D 135, ,76 0 None 30 IBM :00:03 D 135, ,83 0,005 Mid-Crossing Mid-crossing: price improvement = Queue-jumping: price improvement 0.005

34 Mid-crossing vs. queue-jumping Mid-crossing (MID) for stock i and day t is defined as: Volume executed in MID Total consolidated volume Queue-jumping (QJ) for stock i and day t is defined as: Volume executed in QJ Total consolidated volume

35 Sub-penny trading and market quality Simultaneous equations (2SLS) to address endogeneity following Hasbrouck and Saar (JFM, 2013): Where: NOT i,t are other stocks listed on the same exchange and in the same market capitalization group as stock i SP is QJ or MID and MQM can be either bid depth, share volume, quoted, or relative spread

36 Empirical analysis Bid depth and QJ Full sample Small Large a *** * (3.358) (0.240) (2.338) a *** 0.371*** 0.645*** (10.266) (4.294) (8.665) Observations 7,560 2,520 2,520 Bid depth and MID Full sample Small Large a (0.940) (-0.198) (0.790) a *** 0.368*** 0.719*** (13.768) (4.279) (9.500) Observations 7,560 2,520 2,520 Relative spread and QJ Full sample Small Large a *** * (-3.749) (-1.837) (-2.339) a *** 0.582*** 0.684*** (11.720) (5.614) (9.592) Observations 7,560 2,520 2,520 Relative spread and MID Full sample Small Large a (-1.360) (-0.209) (-1.283) a *** 0.719*** 0.669*** (17.162) (12.300) (5.874) Observations 7,560 2,520 2,520

37 Should we be afraid of the dark? Dark pools seem to be used mainly by uninformed traders and not to have a negative effect on price efficiency No evidence that SPT harms liquidity: QJ seems to improve market quality at least for liquid stocks and MID shows no significant effect, both in US and Canada But too early to draw final conclusions we still need better data!

The State of the U.S. Equity Markets

The State of the U.S. Equity Markets September 2017 Figure 1: Share of Trading Volume Exchange vs. Off-Exchange 1 Approximately 70% of U.S. trading volume takes place on U.S. stock exchanges. As Figure