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High Frequency Trading: To be Nurtured or Banned?

High Frequency Trading: To be Nurtured or Banned?. By Hans Degryse KU Leuven and CEPR Brussels Exchange Forum, April 25, 2014. Hot topic Michael Lewis book “Flash Boys” Investigation by FBI … Let me aim to summarize academic evidence …. Outline. High Frequency Trading (HFT):

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High Frequency Trading: To be Nurtured or Banned?

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  1. High Frequency Trading: To be Nurtured or Banned? By Hans Degryse KU Leuven and CEPR Brussels Exchange Forum, April 25, 2014

  2. Hot topic • Michael Lewis book “Flash Boys” • Investigationby FBI • … • Let me aimtosummarizeacademicevidence…

  3. Outline • High FrequencyTrading (HFT): • Definition • Identification • HFT in the US and Europe: somestylizedfacts • Impact of HFT: what does theorysuggest? • HFT and market quality • HFT and market stability • HFT, socialwelfare and regulatory responses

  4. 1. High-Frequency Trading: Definition • Difficultanimaltodefine. SEC (2014) definesthem as: • 1. Use of extraordinarily high speed and sophisticated programs for generating, routing, and executing orders. • 2. Use of co-location services and individual data feeds offered by exchanges and others to minimize network and other latencies. • 3. Very short time-frames for establishing and liquidating positions. • 4. Submission of numerous orders that are cancelled shortly after submission. • 5. Ending the trading day in as close to a flat position as possible (that is, not carrying significant, unhedged positions overnight).

  5. 1. HFT: Identification • Different methods • Direct classification based upon trader IDs, i.e. HFT Flag • E.g. NASDAQ dataset (usedby e.g. Brogaard, Hendershott and Riordan (2013), Hirshey (2013), Zhang (2013)); ESMA dataset (Degryse, De Winne, Gresse and Payne (in progress)) • Pure HFT firms • Typicallyall HFT flags have co-location • Quantitative method employing “order-to trade ratios”, “intraday inventory management”, or “order modification and cancellation speed” • Apply to all IDs, apply to specific trades • E.g. E-mini datasets (e.g. Kirilenko et al. (2011)); Canadian dataset (e.g. Malinova, Park and Riordan (2013), Euronext(e.g. Verschelden (2014)).

  6. 1. HFT: stylized facts (US)

  7. 1. HFT: stylized facts (Europe)

  8. 1. HFT: stylized facts (Europe (2)) • HFT more important on MultilateralTradingFacilitiesthanRegulated Markets

  9. 1. HFT: stylized facts (Europe (3)) • Order-to-traderatios of HFT muchlargerthanotherparticipants

  10. 1. HFT: stylized facts (Europe (4)) • HFT more active in stocks that are more fragmentedacrosstradingvenues -> HFT “klit” together different tradingvenues (see Menkveld (2014))

  11. 1. HFT: stylized facts – general • HFT is not a monolithicphenomenon but encompasses a diverse range of tradingstrategies • Notall HFT trading is passive • NASDAQ dataset (Brogaard, Hendershott and Riordan (2013)): more than half of trading is attributableto liquidity taking (market) orders, even more so in small cap stocks • UK dataset (Benos and Sagade (2012)): lessthan half of trading is liquidity taking • HFT muchlessactive in small stocks in the US; seemsless the case in Euronext (Verschelden (2014)) • Quitesomevariationacrosscountrieswithin Europe (ESMA (2014))

  12. 2. HFT – Theory • Theoryessentiallymodelstwoforces : speed and information • Implicationsfor HFT, othertraders, social welfare • Speed • Hoffmann (JFE forth) • fasttradersreduceexposure topicking off risk -> beneficialfor HFT and socialwelfare • Presenceof fasttraders changes strategies of slow tradersthatsubmit limit orders with a lowerexecutionprobabilitysuchthattradingratedeclines • Speed endogenized: speed is market power and allowsto extract rentsfrom slower traders => arm’s race leadingtooverinvestmentfrom a social welfare perspective • Calls forrandomized “speed bumps” as nowinplemented in some FX markets • Menkveld and Jovanovic (2012): • HFT may lead to more competitionreducing spreads

  13. 2. HFT – Theory (2) • Information – advantage of machines over humans is abilitytoprocess vast amounts of information at superhuman speed • Jovanovicand Menkveld (2012): • HFT processhard information fasterwhichlowers adverse selectionforthem • But theythrowan adverse selectionproblem on others • Calibrationexercise shows thatsocial welfare improves • Biais, Foucault and Moinas (2013): • HFT have a higherlikelihood of findingtradingopportunitieswhichinduces a highertradingratewhich is goodfor welfare • but HFT expose in this way adverse selection on othersreducingtradingrates and thuswelfare. • 3) Combination of these two: • Bernales and Daoud(2013) • HFT benefit in twoways: (1) picking off “stale” orders (2) reactfaster on information => slow tradersmodifytheirstrategies and trade more through market orders • Benefit or costto slow tradersdepends on theirrelativepresence: ifmany slow traders, picking off risk dominates and they are worse off; if few slow traders, HFT are beneficial. • HFT withinformational advantage is goodfor welfare; HFT withonly speed advantage is bad for welfare; havingboth is betterfor welfare => suggests 70% of HFT is optimal • Bongaerts and Van Achter (2013): • endogenizenumber of HFT and slow traders => HFT drive some slow traders out of market. • Withsubstantialasymmetric information, HFT shun the market inducing slow tradersalsotoleave => endogenous market freezes and small crashes.

  14. 3. HFT and Market Quality • Fragmentation in “litmarkets” (proxy for HFT) improved market quality but darktradingdecreasedit(see e.g. Degryse, de Jong and van Kervel (2013)) • HFT effect on market quality: • Passive HFT strategies have beneficialeffects: lower spreads and intraday volat • Jovanovic and Menkveld (2012) findthat the entry of a large, primarilypassive HFT reduces spreads by 15% in Dutch markets • Malinova, Park and Riordan (2013) exploitchock in exchange feesthat affect HFT traders and findthat bid-ask spreads increase in Canadian markets • Liquidity consumingactivities of HFT lessbeneficial: • More price impact (Zhang and Riordan (2011) for large stocks, Zhang (2013), Brogaard, Riordan and Hendershott (2013)) • Competitionbetween HFT harmful? • Breckenfelder (2013) findsthatwhen HFT competethere are more liquidity consumingtradesby HFT • HFT may lead to “ghost liquidity” for slow traders • van Kervel (2013) shows thattradesexecuted in onevenue lead tosubstantialcancellations on othervenues

  15. 4. HFT and Market Stability • Do HFT increase financial instability and systemic risk in financial markets? • Example: the flash crash, May 6, 2010 • Role of HFT in Flash Crash (see e.g. Kirilenko (2011)): not triggering the shock but maybe deepening the volatility • Hagstromer and Norden (2013): more passive HFT activityreducesintradayvolatility. • Systemic risk concern: • HFT have littlecapital • HFT trade a lot witheachother -> contagion?

  16. 5. HFT, Social Welfare and Regulatory Responses • Evidencesuggeststhat market quality has improved and marketsmay have become more informationalefficient • Shouldbebeneficialtofirms and real economy • However, • Slow tradersmayneedto change tradingstrategy and mayultimatelybeworse off => switch from limit orders to market orders • Is gain in informational efficiency sociallyproductive? Information would have been incorporated at slightlylower speed anyhow • HFT mayimprove slow tradersoutcomeswhenthey act as market makers, but reduce slow trader welfare whenpicking-off risk increases • Should HFT beallowedtobuypreferential treatment? Probablynot! • Earlier access to information releases is disturbing fair level playing field • Co-locationforeveryone -> should look into business model of RM and MTF toseehowthis is allocated

  17. 5. HFT, Social Welfare and Regulatory Responses (2) • Regulatory responses: • Fair level playing field in terms of access to information • If HFT by quote stuffing or excessive order flow delay otherparticipants -> introduce order withdrawal fees; but difficultto separate “good” from “bad” order flow • MiFID II: HFT strategies subject toregulatoryauthorization • Change market structure: batch auctionsevery “xxx” milliseconds • Someconcludingthoughts • HFTs have allowed new trading platforms toarrive and have inducedcompetition in trading and post-tradingfees. Both are important as “cum-fee liquidity” has improvedsubstantially(see e.g. Colliard and Foucault (RFS2012) and Degryse, Van Achter and Wuyts (2013)) • In sum, HFTs have been beneficial but regulators needto take care of potentialexternalities • Too muchdarktradingmightbe a more important concern (MiFID II)

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