High-frequency trading – a discussion of relevant issues - Xetra

High-frequency trading –a discussion of relevant issuesPress WorkshopLondon, 8 May 2013

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?2

High-frequency trading – a discussion of relevant issues May 2013Differentiation of “algorithmic trading” (AT) and HFTCommon factors of AT and HFT:• Pre-designed trading decisions• Used by professional traders• Observing market data in real-time• Automated order submission, automated order management• No human intervention• Use of direct market accessTypical characteristics of AT excl. HFT• Primary agent trading• Minimize market impact (for large orders)• Significant positions overnight• Typical holding periods: days/weeks/months• Working an order through time and across marketsTypical characteristics of HFT• Proprietary trading• High number of orders, rapid order cancellation• Mainly spread and arbitrage income• No significant position at the end of a day (flat position)• Short holding periods, small margin per trade• Low latency requirement• Focus on highly liquid instrumentsSource: Gomber et al. (2011)3

High-frequency trading – a discussion of relevant issues May 2013HFT is a technology applied to a broad spectrum of strategiesA conclusive definition of HFT is difficult since it is the technology necessary for implementing a broadrange of latency sensitive strategies.HFT is a technology, not astrategyLimited commondenominator of HFT-basedstrategiesDifferent perceptions in theindustry• HFT uses a wide range ofstrategies with very differentcharacteristics.• HFT is an advancedimplementation of pre-existingstrategies.• HFT-based strategies only haveone thing in common, the need tobe competitively fast in order toaddress profit opportunities and,more importantly, avoid beingtaken advantage of by others, i.e.avoid losses.• Everyone in the financial industryhas an individual idea of whatHFT is.• The opinions on HFT varyconsiderably depending on whatthe observer considers a typicalHFT strategy.• The majority of Eurex Exchange’soptions Market Makers do notconsider themselves HFT, whilethey would fulfill the existingdefinition of HFT.4

High-frequency trading – a discussion of relevant issues May 2013HFT is a natural evolution of financial markets based on technologicalprogress and competition• The term HFT was coined in approximately 2006.• However, there was no binary event at which HFT strategies/firms entered the market.• Speed has always been an essential factor for success in exchange trading, e.g. the pneumatic tube system of NYSE (1903).• The importance of speed in electronic markets has dramaticallyincreased.• On Eurex Exchange, since its foundation in the 90s, market makerscompeted fiercely on speed. It used to be about 1/10-seconds and nowit is 1/1000-seconds.• Latency is a necessary condition for theimplementation of various types of strategies,but advantages of latency are no longersufficient for the success.1990s 2000s FutureDuring the first years of the new century, the importance of latency in the industry increased enormously. Reasons include:• All relevant exchanges have introduced electronic trading.• Latency became a dimension of exchange competition.• Exchanges started to serve latency sensitive trading strategies, e.g. proximity service, co-location service, connectivityoptions.• Increasing interconnection between exchanges through electronic algorithms (best execution order routing).• Increased use of algorithm for execution of non-latency sensitive orders through institutional investors.• Nevertheless, the transition of existing markets occurred rather slowly.• At Eurex Exchange, the replacement of futures tick traders by computer driven algorithms essentially implementing thesame strategy, took years.• During the same time, the Eurex Exchange options market became faster, but the fundamental options market structuredid not change.5

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?6

High-frequency trading – a discussion of relevant issues May 2013The majority of HFT- based strategies belong to two types: Liquidityprovision and arbitrage*Liquidity provision• The majority of HFT-based strategies are liquidity provision strategies, as every form of liquidity provision in electronicmarkets requires extremely fast response times.• The reason is all provided bids and offers are based on certain sets of information.• When information changes, this implies different prices, bids and offers.• Accordingly, liquidity providers need to be as fast as possible in: a) receiving the new information, b) transforming thenew information into new prices, bids/offers and c) update the bids/offers provided to the exchange.• The faster the liquidity provider can act, the lower the risk of liquidity provision and the higher the quality of providedquotes.• Primary source of income: Spread.(Statistical) arbitrage• Take advantage of price differences (market inefficiencies) between economically identical or similar products.• Actors calculate fair product values/spreads, and in case of any deviations, they sell the more expensive product, andbuy the cheaper product.• This way, unjustified price differences between economically related products are eliminated.• Arbitrage assures clients fair pricing across all markets/products and thereby reduces their information costs infragmented markets.• Primary source of income: Short term market inefficiency.* Hagströmer, Nordén (2012) found that 63 - 72 % of HFT trading volume is provided by liquidity provision strategies .7

High-frequency trading – a discussion of relevant issues May 2013These other two strategy types exist as long as markets existShort term momentum-strategy• New information leads to new price levels.• These strategies attempt to generate profits by reacting swiftly to new information.• As a result, new information is reflected in the market prices extremely quickly.• Besides new information, market moves can generate trading signals (“riding the short term trend”).• Primary source of income: Short term shift in general price level.Liquidity detection-strategy• Detection of hidden orders or orders that are generated by execution algorithms.• The aim is to gather information about the direction of the customer flow and thus the market prices.• Often used by electronic liquidity providers in order to recognize the market direction at an early stage.• Primary source of income: To take advantage of short term trends or avoidance of losses when providingliquidity.8

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?9

ALVEONDTEBASSIESAPDAIBAYALVEONDTEBASSIESAPDAIBAYHigh-frequency trading – a discussion of relevant issues May 2013Speed is a risk management tool for participantsA Market Maker’s quote…• …is valid until cancelled.• …needs to be updated when theinformation changes.• …results in exposure/risk for the timeuntil the existing quote is either updatedor cancelled at the exchange.XLM (bp) – order size €1MN140120100806040200Oct-01Aug-11The higher the speed…• …the more immediate the transfer of risk.• …the more liquidity the Market Maker isprepared to offer.• …the tighter the bid-ask spread the MarketMaker is willing to quote.XLM (bp) – order size €2MN250200150100500Oct-01Aug-11Reduction infrictionalcoststo end-users10

High-frequency trading – a discussion of relevant issues May 2013Reduction in exchange latency improves situation of liquidityproviders which leads to better market qualityThe biggest risk for liquidityproviders is that new informationimplies new price levels and theliquidity provider is not able toupdate its quotes before otherstake advantage of the outdatedquote.The indicator for this is thenumber of "unwanted trades":We measure it by the number oftimes, when one party sought tomodify/delete its order/quote, butit is was already matched.Evidence from Eurex Exchangeshows that a significant reductionin exchange latency in 2009 haslead to a massive reduction of thenumber of unwanted trades.This enables the liquidityproviders to provide higher quotequality in terms of spread andsize to the market.11

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?12

High-frequency trading – a discussion of relevant issues May 2013Explicit transaction costs decreased substantially for Europeaninstitutional investors through technical advancement ….• The share of high touch order execution decreased drastically in the last few years through theincrease in the availability technology. At the same time, the cost of high touch executions wascut in half.• No touch (DMA) occurs at very low cost and accounts now for approximately 80% of totalexecution.Method of execution20002005 2011% trades fee (bps) % trades fee (bps) % trades fee (bps)High touch touch 100% 25-40 70% 15-20 20% 10-15No No touch (DMA) (DMA) N.A. 30% 7-8 80% 1-3Source: IMC estimation13

High-frequency trading – a discussion of relevant issues May 2013… part of the reduced cost results from decreasing marketinfrastructure fees• Reduction in the costs of tradingin all major financial centers(weighted average decrease of21%).• The cost of trading correspondsto the sum of fees charged by:– Trading platforms– Central counter-parties(CCP’s)– Central SecuritiesDepositories (CSD’s)Source: Monitoring prices, costs and volumes of trading and post-trading services by Oxera, May 2011.14

Basis pointsHigh-frequency trading – a discussion of relevant issues May 2013Liquidity varies over time, largely dependent on economic uncertaintyEurex Liquidity Measure (ELM)The ELM measures the round trip market impact cost ofsomebody executing a EUR 10 million market order onexchange.It is a proxy for liquidity. The smaller the price impact,the higher the liquidity.Visible liquidity decreasedLiquidity did not revert back to its high of Q2 2007.252010000000 - Avg. Advanced Price Movementin BPAt times of crisis, the market impact cost increases, asparticipants scale down their risk profile, resulting inwider spreads and reduced sizes.In general, the liquidity readily available in the orderbook looks slightly worse in Q3 2012 than in 2005.One of the key contributors to this trend is the use ofexecution algo by the buy-side, which has vastlyreduced the placement of resting orders by the buy-sidein the transparent order book.HFT adds significant liquidity, but their order sizes aretypically much smaller.1510501 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 32005 2006 2007 2008 2009 2010 2011 2012Avg. Quarters15

020406080100120140Spread wideningtradePriceHigh-frequency trading – a discussion of relevant issues May 2013… however, the market has become much more resilientHow to quantify liquidity resilience?Fierce competition in liquidity provision strategies, usingHFT technology, increased the resilience of liquidity inour benchmark futures.How to quantify liquidity resilience?We focus on the recovery period after a big trade (in the case below; abuy) widened the spread.The top chart shows a stylized example of the spreadrecovery following a large aggressive order.The time it takes the liquidity to recover is a function of(a) volatility (b) order size and (c) competition forliquidity provision.By accounting for (a) and (b) it should be possible to saysomething about (c). The bottom graph shows averagerecovery paths for eight similarly volatile days; four from2010 and four from 2012.Evidence of resilience improvementCompared to 2010, the liquidity in the DAX futures became much moreresilient. The averages converge around 500ms from the big trade.60%askbidTimeaverage 2010We see a tremendous increase in resiliency comparedto 2010, implying increased competition for liquidityprovision.We argue that the increase in resiliency makes up for(part of) the reduction in visible liquidity.40%20%0%average 2012Time since big trade (in ms)16

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?17

High-frequency trading – a discussion of relevant issues May 2013What does volatility mean and what does it cause?Volatility is a measure of price variation of an instrument.It reflects the uncertainty about the future price of an asset or the market as a whole.It is amplified by the breadth of possible outcomes.Possible outcomesInflationGrowthFiscal consolidationStrengthening the EUR by reformsDeflationRecessionSovereign defaultBreakdown of the EUR18

High-frequency trading – a discussion of relevant issues May 2013HFT strategies typically benefit from volatility, but do not increase it• HFT strategies are intraday strategies.• Mean reversion is the basic strategy of most liquidity providers/Market Makers.19

High-frequency trading – a discussion of relevant issues May 2013What does research say?HFT dampens volatility• Credit Suisse (2010)• CME Group (2010)• Brogaard (2011)• Castura, Litzenberger, Gorelick,Dwivedi (2009)• Hasbrouck and Saar (2011)• Hagströmer, Nordén (2012)HFT has no effect on volatility• Chaboud, Chiquoine, Hjalmarssonand Vega (2009)• Frino, Lepone, Mistry (2010)• Hendershott and Riordan (2009)• UK Treasury Foresight Committee(2011)• Groth (2010)• Bank of international Settlements(2011)• Jarnecic, Snape (2010)HFT causes volatility• Zhang (2010)• Boehmer (2011)20

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?21

High-frequency trading – a discussion of relevant issues May 2013The accusation of front running is misleading and false• In public discussions, the accusation is that, from time to time, HFT firms pursue front running ofcustomer flow• This accusation is wrong. By definition, they are not able to pursue front running: they do not havecustomer flow and therefore, no private order flow information that they could abuse.If the accusation of front running is incorrect, where does it come from?• Usually, institutional investors have large orders, which they execute with the help of algorithms over time to minimizethe market impact (implicit transaction cost).• In contrast, numerous HFT firms are liquidity providers.• The greatest threat to a liquidity provider is that one or several large orders move the market. This created losses forthe liquidity provider, as they are the first counterparts to the large order and thereafter the market moves againstthem due to the large order size.• To compete successfully in the market, liquidity providers need to identify, as quickly as possible, when the marketmoves in a certain direction through large orders (usually generated by institutional customers).• Liquidity providers may witness price changing orders through liquidity detection strategies only, after parts of thisorder are present in the market and have already been filled.• This leads to a natural conflict which always existed: Large orders shift the market and institutional investors try tokeep the impact as small as possible. To achieve this goal, they have to work off the orders as inconspicuously aspossible. If they succeed, liquidity providers will be damaged who in turn, use liquidity detection strategies, for theirprotection.• Liquidity providers at no point of time, have the knowledge about the size of the original order, not to mention anyother private information necessary for front running.22

High-frequency trading – a discussion of relevant issues May 2013Tighter spreads reduce “bid-ask sizes”, and thereby create theperception of reduced liquidity• Electronic trading has tightened the average bid-ask spread.• This development was amplified by a number of markets reducing thetick size in response to the tightening of spreads.• As a result of both factors, the quantities available at the best bid-askhave become smaller in many markets. Institutional investors perceivethis as a reduction of liquidity as they reluctantly trade through the bestbid-ask.• A major driver for smaller displayed size in the order book has been theinstitutional investors themselves, as they hardly place any resting ordersin the public order book due to the use of execution algorithms and darkpools.• This negative effect on liquidity has been compensated for by growingHFT participation, as evidenced by improved liquidity.23

HFT market shareof relevant BBO-1.000 ms- 800 ms- 600 ms- 400 ms- 200 ms100 ms300 ms500 ms700 ms900 mscontractsMarket share of the relevant BBOlarge tradeHigh-frequency trading – a discussion of relevant issues May 2013In futures contracts, there is no evidence of HFT orders fading awaywhen large orders hit the marketIntroductionSome buy-side firms complain that theliquidity seen in the public order bookis not really available to them. In thisrespect, HFT is also accused of frontrunning.This allegation is obviously related tothe experience in fragmented (cash)markets, where sometimes a buy-sideorder, by the time it hits the second orthird market is meeting an order bookwhere some of the liquidity providersresponded faster to the fills in the firstmarket.Our analysis of futures revealed:a) there is no evidence of HFT pullingout before large orders hit themarket andb) right after a large order has hit themarket, the HFT-share of the justhit best bid or just hit best offer isincreasing above the averageparticipation level.How to quantify spuriousness?Retreating liquidity is especially painfularound large trades (when liquidity isalready under stress).a large buy orderconsumes part ofthe best askbidsWhat do we expect?askspriceFinding a liquidity reduction after a largetrade is not enough. We’re interested inevidence of HFTs pulling out more thannon-HFTs before or after a large trade.not spuriousspuriousTimeActual HFT participationThe grey lines depict the daily average market share ofHFTs on the relevant side of the BBO before and aftera large trade (10 time the trailing 10 minute average) inthe front month EURO STOXX 50® futures.65%60%55%50%Time from a big trade (in ms)24

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?25

ContractsIndex PointsHigh-frequency trading – a discussion of relevant issues May 201325 August 2011: Within a few minutes institutional orders caused arapid decline in prices: highly liquid order book damped price impactTrading in FDAX contracts on 25 August 2011 (one-minute intervals)DescriptionWithin 17 minutes the FDAX wentdown by more than 4%, and cameback by 2%.Cause of the price decline: a biginstitutional order (6,000 contracts),which was converted by algorithmsinto a large number of sell ordersflooding the market during that time.Monthly average = 300contracts per minHighly liquid order book prevented agreater decrease: high volumeorders were processed with onlysmall price increments- peakturnover 4,700 contracts per minute,compared to monthly average of 300contracts per minute.26

High-frequency trading – a discussion of relevant issues May 2013Large number of buyers absorbed the initial shock; HFTs providedliquidity, since they were buying in falling marketsNumber of individual buyers and sellers per minuteDescriptionHigh number of trading participantsinvolved on both sides of the marketshows high variety of tradinginterests.A total of around 200 differenttrading participants acted as buyersin the falling market, including butnot limited to high-frequency traders.High liquidity was in large partprovided by HFTs, as theseparticipants initially absorbed themajor sell positions and then passedthem on to protect the market. Theoften assumed acceleration ofdownward movements throughcomputer-based trading strategieswas not observed.27

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What impact does the German HFT Bill have for HFTs?28

Algorithmic /high-frequency tradingHigh-frequency trading – a discussion of relevant issues May 2013Regulation of algorithmic and high-frequency trading is in the scopeof MiFID II (1)EU Commissionlegislative proposalEuropean ParliamentamendmentsEuropean CouncilamendmentsArt. 2.1 (d) MiFIDRegulation andSupervision of HFTsHFTs to be supervised andregulated under MiFID IIHFTs to be supervised andregulated under MiFID IIHFTs to be supervised andregulated under MiFID IIArt. 4 MiFIDAlgorithmic Trading /HFT / HFT StrategyDefinitionDefinition for algorithmictradingNo definition for high-frequencytradingDefinition of algorithmic trading(30) / HFT (30a) and of HFTstrategy (30 b). HTF strategy isbased on two out of fivecriteria*Definition of algo trading (30) /and of high-frequency algotrading strategy (30 a). Thelatter is characterized by threecriteria**Art. 17.3 MiFIDLiquidity ProvisionContinuous liquidity provisionfor algorithmic tradingstrategies (firm quotes at alltimes)Applies only for thoseinvestment firms that areengaged in market making(scheme set by market venue)Applies only to thoseinvestment firms that follow amarket making strategyArt. 17.1 MiFIDRisk controlsInvestment firm that engages inalgorithmic trading shall havein place effective systems andrisk controls (Art. 17.1)Investment firm shall have inplace effective systems andcontrols (Art. 17.3)Investment firm that engages inalgorithmic trading shall havein place effective systems andrisk controls (Art. 17.3)* ‘High-frequency trading strategy' means a trading strategy for dealing on own-account in a financial instrument which involves high-frequency trading and has at least two of the following characteristics:(i) it uses co-location facilities, direct market access or proximity hosting; (ii) it relates to a daily portfolio turnover of at least 50 %; (iv) the proportion of orders cancelled (including partial cancellations)exceeds 20 %; (v) the majority of positions taken are unwound within the same day; (vi) over 50% of the orders or transactions made on trading venues offering discounts or rebates to orders whichprovide liquidity are eligible for such rebates.** High-frequency algorithmic trading strategy’ means an algorithmic trading strategy characterised by: infrastructure intended to minimise network and other types of latencies including proximity and colocation;system determination of order initiation, generating, routing and execution without human intervention for each individual trade or order; high message rates (orders, quotes or cancellations).29

Algorithmic /high-frequency tradingHigh-frequency trading – a discussion of relevant issues May 2013Regulation of algorithmic and high-frequency trading is in the scopeof MiFID II (2)EU Commissionlegislative proposalEuropean ParliamentamendmentsEuropean CouncilamendmentsArt. 51 a MiFIDMinimum OrderResting TimeIntroduction of a minimumorder resting time of 500milliseconds to slow downtradingArt. 51.3 MiFIDRatio of unexecutedorders to transactionsSlow down of order flowthrough limit of ratio ofunexecuted orders totransactionsSlow down of order flowthrough limit of ratio ofunexecuted orders totransactionsSlow down of order flowthrough limit of ratio ofunexecuted orders totransactionsArt. 51.5 a MiFIDOrder cancellation feeHigher fee for placing an orderthat is subsequently cancelledthan an order which isexecutedArt. 51.6 MiFIDOrder flaggingFlagging orders generated byalgorithmic trading, the differentalgorithms used for the creationof orders and relevant personsinitiating these orders30

High-frequency trading – a discussion of relevant issues May 2013AgendaHFT – background• How do you define high-frequency trading (HFT)?• What are the most common HFT strategies?• Why is the speed so important?• What is the impact of HFT on market quality?HFT – issues• Do HFT users cause volatility?• Why are there critical voices on HFT from institutional investors?• How do HFT firms (re-)act in critical times?HFT – Regulation• How do regulators deal with HFTs?• What does the passed German HFT Act mean for HFTs31

High-frequency trading – a discussion of relevant issues May 2013Announcement of German HFT Bill to be expected in May 201330 Jul 201217 Aug 201226 Sep 201223 Nov 201229 Nov 201216 Jan 201330 Jan 201327 Feb 201328 Feb 201322 Mar 2013May 2013Publication of Discussion Paper for Participation of OrganizationsConsultation Deadline for Departments and OrganizationsDecision Bundeskabinett (Federal Cabinet)First Review Bundesrat (Upper House of German Parliament) (incl. statement)First Reading Bundestag (Lower House of German Parliament)Hearing in Financial Committee of the Bundestag (Lower House of German Parliament)Consultation in the Bundestag Financial CommitteeFinal Consultation in the Bundestag Financial CommitteeSecond and Third Reading Bundestag (Lower House of Parliament)Second Review Bundesrat (Upper House of German Parliament)Announcement of German HFT Bill (expected)32

High-frequency trading – a discussion of relevant issues May 2013German HFT Bill foresees several measures and procedures toregulate algorithmic trading and HFTMain Aspects:1Additional rights for the Exchange Supervisory Authority/BaFin2Price discovery protection (e.g. volatility interruptions)3Requirements to set appropriate tick sizes4Organizational requirements for investment firms (IFs)5Order to Trade Ratios (OTR);Excessive System Usage Fees (ESU-Fee)/ Transaction Limits6Flagging of algorithmically generated orders7Registration obligation as Financial Service Institutions33

High-frequency trading – a discussion of relevant issues May 2013Additional rights for supervisors, protection of price discoveryprocess and appropriate tick sizesTopicDescription1Additional rightsfor supervisors• Supervisors (Exchange Supervisory Authority and BaFin) are allowed torequest information about algorithmic trading, the used systems, and adescription of strategies or parameters, wherever grounds for checks with oneof the provisions that are covered in the bill.• Supervisors are allowed to prohibit algo trading strategies.2Protection of pricediscovery process• Exchange* has to ensure that orderly price discovery is granted even insituations of large price fluctuations (changes of market model, volatilityinterruptions under consideration of static or dynamic price corridors or limitcontrol systems).3Set Tick Sizes • Exchange has to ensure an appropriate tick size to prevent adverse effects onmarket integrity and liquidity.• When determining tick sizes, Exchange needs to consider that the pricediscovery mechanism and the goal of reaching a suitable OTR are notaffected.• Further provisions can be delivered by Exchange Rules.** Similar for MTF34

High-frequency trading – a discussion of relevant issues May 2013Organizational requirements required for investment firms that usealgorithmic trading and introduction of ORTs and fees for excessivesystem usageTopic45Organizationalrequirementsfor IFsOrder to TradeRatios andExcessiveUsage FeeDescriptionSecurities Trading Act §33 (1a)Applies for investment firms that use algorithmic trading. The firm must facilitate system andrisk controls in order to ensure1. its trading systems are resilient, have sufficient capacity and are subject to appropriatetrading limits2. that orders are not transmitted erroneously or a malfunctioning of the system is avoided,which would cause disruptions on the market or would contribute to these disruptions.3. its trading systems cannot be used for a purpose that is contrary to the European ornational rules preventing market abuse or the regulations of a trading venue to which it isconnected.The firm must further have in place emergency measures in order to deal with unforeseendisruptions in its trading system and ensure that its system are fully tested and orderlysurveilled. It must also ensure that every change of a computer algorithm used for trading isdocumented.Exchange Act §26a and §19• Participants are required to ensure suitable Order-to-Trade Ratio (OTR).• OTR tbd. by Exchange Rules*; per instrument; per month, per function of tradingparticipant, per asset classExchange Act §17• Introduction of Excessive System Usage-Fee.• Fees tbd. by Management Board of Exchange35

High-frequency trading – a discussion of relevant issues May 2013Order flagging required for orders generated by investment firms’computer algorithmsTopic6Algorithmictrading definedDescriptionSecurities Trading Act §33 (1a)• An investment firm• Trading in financial instruments• Order parameters are determined automatically by a computer algorithm• Parameters include decisions to initiate the order on time, price or quantity of the order or how the order should be processed after its initiation, whereas it involveslimited or no human interactionExemptions:• Systems that merely route orders• Systems that confirm orders6Labeling ofalgorithmicordersExchange Act §16 (2) (c)• Designation of orders that are generated by Algorithmic Trading by tradingparticipants and• Identification of the respectively used trading algorithms36

High-frequency trading – a discussion of relevant issues May 2013License for firms under German Banking Act needed if they perform“High-frequency algorithmic trading” on own account7English convenience translation (non binding):Article 2: Extension of banking act (Section 1 paragraph 1a Sentence 2 number 4) by following financial service:d) „ The purchase or sale of financial instruments on own account as a direct or indirect participant of a domesticorganised market or multilateral trading system via high-frequency algorithmic trading technologies, which arecharacterized by the usage of infrastructures that intend to minimize latency, as well as systems creating,transmitting and executing an order without any human intervention for single trades or orders and quotes,and by a high intraday message amount in form of orders, quotes or cancellations also without providingservices for others (proprietary trading).”BaFin revealed criteria*‚Latency minimizinginfrastructure‘‚High intraday messagerate‘Only use of fastest connectivity option, i.e. 10 Gbit connection in co-locationDaily threshold of 75,000 messages (order entries, quotes, deletions, modifications)per member (to be converted into an annual figure); separate for Xetra and Eurex*Workshop on the HFT Act on 30 April 2013 – http://www.bafin.de/SharedDocs/Veranstaltungen/EN/WA11_20130430_hft_workshop_en.html37

High-frequency trading – a discussion of relevant issues May 2013Passporting of license in order to continue trading on a Germantrading venueIssueDescription7EEA*-based firmsWith permission for“dealing on ownaccount”• If not already passported to Germany: Need to passport their license toGermany via home supervisor• If already active in Germany with European passport: No additional licenseneeded (merely notification)Without permission • Need to get license from home supervisor and then passport the license• Alternative: Set up branch in Germany and get a license7Non-EEA*-based firmsWith permission similarto MiFID’s “dealing onown account”• No information provided in billWithoutpermission• No information provided in bill38*EEA = European Economic Area (EU countries plus Iceland, Liechtenstein and Norway)

High-frequency trading – a discussion of relevant issues May 2013Transitional Periods are granted for firms that are not yet regulatedfor HFTIssueDescription77EEA-based firmsWith permission for“dealing on ownaccount”Without permissionNon-EEA-based firmsWith permission similarto MiFID’s “dealing onown account”• Application for passporting is filed with home supervisor within six months• After license has been obtained: application for passporting is filed with homesupervisor within six months• Alternative (Set up branch in Germany): complete application is filed withBaFin within nine months• Complete application is filed with BaFin within nine months (branch to be setup first)Withoutpermission• Complete application is filed with BaFin within nine months (branch to be setup first)39

High-frequency trading – a discussion of relevant issues May 2013SummaryHFT is a natural evolution resulting from technological developments and competition• HFT is a natural reflection of competition between market participants using the advances in computertechnology.• HFT is a technology that enables for the implementation of a wide range of trading strategies.• All actors in financial markets need to address this natural development– Proprietary traders/Market Makers: Implementation of speed-sensitive strategies requires constant and significanttechnology investment.– Brokers: Address customer needs for faster and more advanced execution of customer orders in a growing numberof electronic markets.– Exchanges: Invest in faster systems with larger capacity and a variety of safety mechanisms.– Regulators: Provide a framework for fair and transparent markets. Receive more information than ever to monitorthe markets. Challenge is the efficient use of the large amount of data.• A “deceleration of the markets” by regulatory intervention is not a solution.– Either the markets go somewhere else or the actors find ways of bypassing.• As a result of public pressure the risk of over-regulation for HFT is high, as exemplified by the multitudeof regulatory initiatives (MiFID, ESMA Systems & Control, national rules, e.g. German HFT Bill).40

High-frequency trading – a discussion of relevant issues May 2013Thank you for your attention41

High-frequency trading – a discussion of relevant issues May 2013ContactsEurex ExchangeDr. Randolf RothExecutive Director - Head of Market StructureXetraSandra BramhoffSenior Vice President – Market DevelopmentMedia RelationsHeiner SeidelSpokesman Eurex GroupPhone: +49 69-2 11-1 77 64Email: heiner.seidel@deutsche-boerse.com42

High-frequency trading – a discussion of relevant issues May 2013This publication does not necessarily deal with every important topic or coverevery aspect of the topics with which it deals. It is not designed to provide legal orother advice. Deutsche Börse AG has made every effort to ensure that allstatements and information contained in this publication are accurate as of thedate of this publication but accepts no liability in case of errors or omissions.All materials provided by Deutsche Börse AG in this publication are and remainthe intellectual property of Deutsche Börse AG and all rights therein are reserved.All trademarks, logos etc. depicted or otherwise used in this document, includingDeutsche Börse Group entities names and logos, are owned by the respectiveDeutsche Börse Group entity and may not be used without such owners' priorwritten express consent.43

High-frequency trading – a discussion of relevant issues May 2013Backup44

High-frequency trading – a discussion of relevant issues May 2013HFT requires high investments in the exchange infrastructure• Our trading and clearing systems have to process anexponentially growing number of technical transactions(message throughput).Number of processed transactions at Eurex Exchange& response times• Eurex Exchange addresses this with the roll-out of acompletely new trading architecture. The clearingarchitecture will be renewed as well.• Furthermore, Eurex has massively invested in tools, whichenable Eurex Exchange, Eurex Clearing, Exchangeparticipants and Clearing Members to identify and addressproblems swiftly and independently.• In addition to our investments in infrastructure andfunctionalities, we also protect the integrity of ourmarketplaces through a “transaction limit regime”, whichprovides participants with limits to their maximum systemcapacity usage. Violations trigger appropriate penalties.TransactionsResponse times(in milliseconds)45

High-frequency trading – a discussion of relevant issues May 2013Risk of algorithms getting out-of control addressed by overlappingsafety mechanism• The overarching goal is the avoidance of a situation where an algorithm gets out of control and causes aserious market failure.• This not only applies to HFTs but to all computer algorithms applied to our markets.• Electronic exchanges such as Eurex Exchange have developed several tools to enable ExchangeParticipants, Clearing Members, Eurex Exchange itself and Eurex Clearing as the CCP, to identify andprevent possible misconduct as quickly as possible.• In addition, trading participants and Clearing Members are also investing significantly into the monitoringof their algorithms in the dimensions of IT-governance, test protocols, access safety standards, riskmonitoring and change management.• HFT firms as well as exchanges such as Eurex Exchange welcome any regulatory definition regardingminimum standards for systems and controls.• All parties have a keen interest in the integrity and efficiency of our markets.• On the following pages there is an overview of the tools available at Eurex Exchange and Xetra.46

High-frequency trading – a discussion of relevant issues May 2013Protection points across the value chain tackle potential risks arisingfrom HFTIllustration of major protection points at Eurex Exchange and XetraTradingParticipant1Description1 DMA control 2 Plausibility checks 7CentralCounterparty67ClearingMember23453 Architecture throttle 4 Trading safeguards 5 Stop button 6 Real-time risk management = Protection pointExchange(Eurex Exchange/Xetra)7 Advanced Risk Protection • Protection mechanisms built into the market structure safeguard fair and orderly markets.• Established procedures and practices exist to mitigate potential risks arising from trading / high-speed trading.• Procedures exist along the whole value chain, involving traders, market operators, clearing firms and CCPs.• Protection mechanisms handle errors on the level of order entry (“fat finger”), human mistakes or an erroneous algorithm.47

High-frequency trading – a discussion of relevant issues May 2013Direct market access to Eurex Exchange/Xetra requires electroniccontrol at the level of the firm1DMA controlIllustrationCentralCounterpartyTradingParticipant1Exchange(Eurex Exchange/Xetra)ClearingMemberDescription• With Eurex Exchange/Xetra orders submitted by anorder-routing system (DMA) pass an electronic filterinstalled at the company. The filter verifies alloutgoing orders according to parameters predeterminedby the Exchange Participant.• The firm has to inform the exchange (EurexExchange/Xetra) about the user ID of the Exchangetrader under which the orders are entered.• The exchange (Eurex Exchange/Xetra) may prohibitthe connection of automated order-entry systems, ifthe connection jeopardizes the orderly exchangetrading or system safety.48

High-frequency trading – a discussion of relevant issues May 2013Plausibility checks at the exchange entry to prevent “fat finger errors”2Plausibility checksIllustrationDescriptionCentralCounterpartyTradingParticipantClearingMember• A fat finger error describes errors when inputting textvia keyboard (typo).• When entering an order, typos can have massiveeconomic consequences (e.g. adding a “zero” to theorder size will tenfold increase the size), if they arenot prevented.• Eurex Exchange/Xetra check for maximum orderquantities upon reception of each order.2Exchange(Eurex Exchange/Xetra)• Furthermore, Eurex Exchange/Xetra perform amandatory check and offers an optional pricereasonability check.49

High-frequency trading – a discussion of relevant issues May 2013Architecture throttle limits the maximum message to avoid trafficcongestion and resulting slow-down3Architecture throttleIllustrationDescriptionCentralCounterpartyTradingParticipant3Exchange(Eurex Exchange/Xetra)ClearingMember• Each trading session of a Participant includes atechnical architecture throttle mechanism that limitsthe maximum throughput per second.• The architecture throttle limits the transaction ratessubmitted per session. It avoids applications withextremely high transmission rates from endangeringthe overall integrity of the Eurex Exchange/Xetratrading system.• The rate can be changed intraday, if marketconditions require*.* In addition to these measures, there are also limits for capacity usage rate for the members. They are enforced by an excessive usage fee. However,violations of the capacity usage limits are rare.50

High-frequency trading – a discussion of relevant issues May 2013Trading safeguards as protection against extreme, unreasonableprice moves4Trading safeguardsIllustrationDescriptionCentralCounterpartyTradingParticipantClearingMember• Trading safeguards exist to protect the orderly priceformation process.• Trading safeguards at Eurex Exchange and Xetra arecalled “volatility Interruptions”.• Trading is interrupted* “before the damage is done” –i.e. before a trade is made at volatile prices.• For options markets, Eurex Exchange offers MarketMaker protection tools to limit their risks.4Exchange(Eurex Exchange/Xetra)* From a technical perspective, trading is not interrupted. Instead, the market model is merely switched from “continuous trading” to “call auction”. Therefore,the process of trading still resumes, as Participants can still delete, modify and enter orders in anticipation of the auction price.51

High-frequency trading – a discussion of relevant issues May 2013Stop button enables Clearing Members to discontinue all tradingactivities of a Trading Participant5Stop buttonIllustrationDescriptionTradingParticipant5• The stop button functionality enables ClearingMembers to control (discontinue or release again) thetransactions of their trading participants.• At Eurex Exchange, this is also possible for tradingparticipant.CentralCounterpartyClearingMember5Exchange(Eurex Exchange/Xetra)52

High-frequency trading – a discussion of relevant issues May 2013Real-time risk and position information facilitate highly efficient riskmanagement6Real-time risk managementIllustrationDescriptionTradingParticipant• Real-time information on positions and resultingmargin requirements is calculated and distributedthroughout the trading day to Trading Participantsand Clearing Members.CentralCounterparty6ClearingMember• Intra-day margining is an important feature of the riskmanagement framework. It reduces the counterpartycredit risk of the CCP because the intra-day margincall allows the CCP to quickly respond to increasedprice volatility or the growing positions of ClearingMembers.Exchange(Eurex Exchange/Xetra)53

High-frequency trading – a discussion of relevant issues May 2013Protection mechanisms built into the market structure safeguard fairand orderly markets7Avanced Risk ProtectionIllustrationDescriptionTradingParticipant• Advanced Risk Protection functionality enablestrading participants and/or Clearing Members to setup to three limits on aggregate risk metrics, such asthe total margin requirement.7CentralCounterparty7ClearingMember• Upon breach of the first limit, an alert message issent.• At the second limit, the system automatically throttlesorders and quotes.Exchange(Eurex Exchange/Xetra)• At the third limit, the “stop button” functionality isautomatically triggered, thus halting all tradingactivities.54

High-frequency trading – a discussion of relevant issues May 2013Literature review (I/III)Author(s) / Title Dataset FindingsMarkets Committee, Bank for InternationalSettlements (BIS)“High-frequency trading in the foreign exchangemarket”, September 2011Brogaard"High frequency trading and its impact on marketquality", August 2010Brogaard“High Frequency Trading and Volatility”, October2011Hendershott, Riordan“High Frequency Trading and Price Discovery”(working paper)Jarnecic, Snape"An analysis of trades by high frequencyparticipants on the London Stock Exchange",June 2010CME Group"Algorithmic trading and market dynamics", July2010UK Treasury Foresight Committee (2011)“The Future of Computer Trading in FinancialMarkets”Various FX venues, notably Reuters and EBS,and various dates, notably May 6,2010 and March 17, 2011HFT vs. other trades. U.S. equities onNASDAQ, various periods in2008 –2010HFT vs. other trades. U.S. equities onNASDAQ, various periods in2008 –2010HFT vs. other trades. U.S. equities onNASDAQ, various periods in2008 –2010HFT vs. other trades. LSE equities,April – June, 2009Automated vs. other trades. CME futures, May2008 – May 2010Literature review of computer based tradingdevelopmentsHFT is found to be beneficial during normal marketperiods, with similar behavior to traditional marketparticipants during high volatility periodsHFT helped to narrow bid – ask spreads, improved pricediscovery and may have reduced volatilityHFT activity tends to decrease idiosyncratic and intradayvolatility.HFT trades were positively correlated with permanentprice changes and negatively correlated with transitoryprice changes, Suggesting that HFT improves pricediscoveryHFT improved liquidity and was unlikely to haveincreased volatilityAutomated trading was associated with improvedliquidity and reduced volatilityEconomic research thus far provides no direct evidencethat high frequency computer based trading hasincreased volatility.55

High-frequency trading – a discussion of relevant issues May 2013Literature review (II/III)Author(s) / Title Dataset FindingsCredit Suisse“Sizing Up US Equity Microstructure”, April 2010Hasbrouck, Saar"Low-Latency Trading“, May 2011Hendershott, Riordan“Algorithmic Trading and Information”, August2009Chaboud, Hjalmarsson, Vega and Chiquoine“Rise of the Machines: Algorithmic Trading in theForeign Exchange Market”, October 2009RGM Advisors(Castura, Litzenberger, Gorelick, Dwivedi)“Market Efficiency and Microstructure Evolution inUS Equity Markets: A High FrequencyPerspective”, October 2010X. Frank Zhang“The Effect of High-Frequency Trading on StockVolatility and Price Discovery” November 2010Boehmer, Fong, Wu (2012)“International evidence on algorithmic trading”U.S. equities, 2003 - 2010U.S. equities, full NASDAQ order book June2007 and October 2008Automated vs. other trades. Deutsche Börseequities, January 2008Automated vs. other trades.EBS forex market, 2006-2007U.S. equities, 2006 - 2010Firms from the Center for research in securityprices (CRSP) and the Thomson ReutersInstitutional Holdings databases during 1985–2009.Large sample from 2001 – 2009 thatincorporates 39 exchanges and an average of12,800 different common stocksBid -ask spreads have narrowed, available liquidity hasincreased and short-term volatility (normalized by longerterm volatility) has declinedLow latency automated trading was associated withlower quoted and effective spreads, lower volatility andgreater liquidityAutomated trades made prices more efficient and did notcontribute to higher volatilityAutomated trades increased liquidity and may havelowered volatilityBid-ask spreads have narrowed, available liquidity hasincreased and price efficiency has improvedThis study examines the effect of high-frequency tradingon stock price volatility and price discoveryWe find that greater AT intensity is, on average,associated with more liquidity, whether measured at thetransaction level or at the daily level, faster pricediscovery, and greater volatility56

High-frequency trading – a discussion of relevant issues May 2013Literature review (III/III)Author(s) / Title Dataset FindingsHagströmer, Nordén (2012)“The diversity of high frequency traders”NASDAQ OMX Stockholm, equity market,August 2011, February 2012Market maker cause the biggest amount of HFT tradingvolume (63-72%) and limt order traffic (81-86%). FurtherMarket maker have higher order-to-trade ratios, lowerlatency, lower inventory and provide liquidity more oftenthan opportunistic traders57