algorithmic trading in different landscapes
DESCRIPTION
Presentation on "Algorithmic Trading in different geographies" This presentation highlights the trading landscape in different geographies and compares them on four parameters: i) Technological protocols in various geographies ii) Regulatory environments iii) Competitive landscape iv) Market Volumes This presentation was presented by senior QI faculty and co-founder Rajib Ranjan Borah at the pre-conference workshop of the "4th Annual Conference: Behavioral Models and Sentiment Analysis Applied to Finance", in London in June 2014. The two day pre-conference workshop on "Market Microstructure, Liquidity and Automated Trading Workshop" was conducted at Fitch Learnings, London. To view a video recording of the presentation, please contact [email protected]TRANSCRIPT
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Algorithmic Trading in different geographies
- technologies- regulations- competition
- markets
Rajib Ranjan Borah
Market Microstructure, Liquidity and Automated Trading Workshop.Fitch Learning, London. 16-17 June 2014.
4th Annual Conference on ‘Behavioral Models and Sentiment Analysis Applied to Finance’, London, 16-20 June 2014.
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Most relevant factors in analyzing different geographies
Current AlgoTrading landscape in various geographies
The road ahead ?
Q&A
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Most relevant factors in analyzing different geographies
Current AlgoTrading landscape in various geographies
The road ahead ?
Q&A
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
How do you decide: where to trade?
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
As a trading manager, how do you decide which geographies to trade ?
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
How do you decide: where to trade?
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
As a trading manager, how do you decide which geographies to trade ?– Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ?• What are the listed instruments ?• What is the volume traded ?
– Will I be able to make profits ?• What is the level of sophistication of competition ?• Who are the leading players ?
– What are the complexities to connecting to these markets ?• Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols• Brokers to connect to these markets
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
How do you decide: where to trade?
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
As a trading manager, how do you decide which geographies to trade ?– Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ?• What are the listed instruments ?• What is the volume traded ?
– Will I be able to make profits ?• What is the level of sophistication of competition ?• Who are the leading players ?
– What are the complexities to connecting to these markets ?• Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols• Brokers to connect to these markets
Regulations
Market Size
Competition
Technology
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
How do you decide: where to trade?
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
As a trading manager, how do you decide which geographies to trade ?– Am I allowed to trade in that country (i.e. how conducive are regulations) ?
• Are foreigners allowed to trade ?• Are there restrictions on position-sizing / short-selling ?
– Are these markets interesting to trade ?• What are the listed instruments ?• What is the volume traded ?
– Will I be able to make profits ?• What is the level of sophistication of competition ?• Who are the leading players ?
– What are the complexities to connecting to these markets ?• Technological protocols used by these exchanges – common standard protocols OR unique
custom protocols• Brokers to connect to these markets
Regulations
Market Size
Competition
Technology
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Most relevant factors in analyzing different geographies
Current AlgoTrading landscape in various geographies
The road ahead ?
Q&A
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapes
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Americas
Bermuda SE 4
BM&FBOVESPA 67,550
Buenos Aires SE 279
Colombia SE 2,162
Lima SE 338
Mexican Exchange 14,780
NASDAQ OMX 798,729
NYSE Euronext (US) 1,141,704
Santiago SE 3,640
TMX Group 114,290
Total region 2,143,474
APAC
Australian SE 73,463
BSE India 7,046
Bursa Malaysia 12,323
Colombo SE 130 GreTai Securities Market 11,241
HoChiMinh SE 869 Hong Kong Exchanges 110,281
Indonesia SE 9,664 Japan Exchange Group - Osaka 17,594 Japan Exchange Group - Tokyo 525,411
Korea Exchange 107,050 National Stock Exchange India 39,913 New Zealand Exchange 752
Philippine SE 3,889
Shanghai SE 310,927
Shenzhen SE 321,542
Singapore Exchange 23,410
Taiwan SE Corp. 51,996 The Stock Exchange of Thailand 31,335
Total region 1,658,838
Europe
Athens Exchange 1,981 BME Spanish Exchanges 74,464
Budapest SE 869
Casablanca SE 263
Cyprus SE 3
Deutsche Börse 111,212
Irish SE 1,206
Ljubljana SE 33
Luxembourg SE 12
Malta SE 6
Moscow Exchange 20,167 NASDAQ OMX Nordic Exchange 52,153 NYSE Euronext (Europe) 138,490
Oslo Børs 10,200
SIX Swiss Exchange 56,413
Wiener Börse 2,154
Total region 469,626
MEA: Middle East + Africa
Abu Dhabi SE 1,816
Amman SE 285
Borsa Istanbul 34,947
Cyprus SE 3
Egyptian Exchange 1,077
Irish SE 1,206
Johannesburg SE 28,608
Kazakhstan SE 58
Mauritius SE 26 Muscat Securities Market 478
Qatar Exchange 1,714 Saudi Stock Exchange - Tadawul 30,202
Tel Aviv SE 4,475
Total region 104,895
Equity volumes – avg monthly volumes (USD million)
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Americas Options Future
BM&FBOVESPA 238 119.0 504 342.0Bourse de Montreal 3 550.8 555 764.0CBOE Future Exchange x NA
Chicago Board Options Exchange NA x
CME Group 9 987 400.0 46 628 400.0
Colombia SE x 19.2
ICE Futures US 6 516.0 2 962 600.0
International Securities Exchange NA NA
MexDer 1 761.5 30 896.1NASDAQ OMX (US) NA NANYSE Euronext (US) NA NA
APAC Options FutureASX Derivatives Trading 441 915.0 2 561.6
ASX SFE Derivatives Trading 46 330.5 1 204 770.0Bombay SE 1 168 300.0 10 210.9Bursa Malaysia Derivatives NA 71 423.6
China Financial Futures Exchange NA 22 909 400.0Hong Kong Exchanges 1 838 560.0 4 539 370.0Korea Exchange 67 864 200.0 5 855 830.0National Stock Exchange India 4 668 890.0 498 918.0
Osaka SE NA 7 468 830.0
Shanghai Futures Exchange 0.0 0.0Singapore Exchange NA NA
TAIFEX 1 485 740.0 1 480 410.0
Thailand Futures Exchange NA NATokyo SE Group NA 2 630 990.0
EMEA Options Future
Athens Derivatives Exchange 432.3 28 113.5BME Spanish Exchanges 60 489.2 672 335.0
Borsa Istanbul 35.1 63 631.4
Budapest SE 0.0 341.8
EUREX 13 764 800.0 18 691 000.0ICE Futures Europe 0.0 0.0Johannesburg SE 2 946.5 487 400.0Moscow Exchange 118 079.0 752 618.0NYSE.Liffe Europe 3 297 390.0 6 282 720.0OMX Nordic Exchange 151 241.0 573 599.0
Oslo Børs 439.1 1 752.9
Tel Aviv SE 641 250.0 976.1
Wiener Börse 56.2 22 030.8
Index FO – annual volumes (USD million)
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Americas Options Future
BM&FBOVESPA 994 498.0 NABourse de Montreal 73 960.1 0.0
Buenos Aires SE NA NA
Chicago Board Options Exchange NA NA
Colombia SE NA 480.6
International Securities Exchange NA NA
MexDer 90.0 13.4NASDAQ OMX (US) NA NANYSE Euronext (US) 104 464.0 NA
BM&FBOVESPA 994 498.0 NABourse de Montreal 73 960.1 0.0
APAC Options Future
ASX Derivatives Trading 284 474.0 11 867.0
Bombay SE 3 076.7 7 442.2Hong Kong Exchanges 167 335.0 1 485.5Korea Exchange 0.0 56 761.0
National Stock Exchange India 416 644.0 811 791.0
New Zealand 0.0 NA
Osaka SE NA NA
Shanghai Futures Exchange 0.0 0.0
TAIFEX 177.6 22 743.6
Thailand Futures Exchange NA NATokyo SE Group NA NA
EMEA Options Future
Athens Derivatives Exchange 17.0 2 450.0BME Spanish Exchanges 31 668.0 15 271.2
Borsa Istanbul 14.4 11.9
Budapest SE 0.0 2 684.7
EUREX 784 435.0 752 475.0ICE Futures Europe 0.0 0.0Johannesburg SE 311.3 16 625.5Moscow Exchange 2 829.0 106 339.0NYSE.Liffe Europe 343 406.0 455 497.0OMX Nordic Exchange 52 967.4 4 658.3
Oslo Børs 1 874.3 1 836.7
Tel Aviv SE 4 335.2 NA
Wiener Börse 307.0 0.0
Equity FO – annual volumes (USD million)
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Americas Options Future
BM&FBOVESPA 435 060.6 4 196 493.1Bourse de Montreal 68.2 0.0
CME Group 2 076 378.0 25 281 026.0
Colombia SE NA 10 674.9
ICE Futures US 3 410.0 658 019.0
MexDer 181.9 135 749.3
APAC Options FutureHong Kong Exchanges NA 13 948.8Korea Exchange NA 532 393.2
National Stock Exchange India 252 897.5 614 399.2
Osaka SE NA 61 932.8
Thailand Futures Exchange NA NA
EMEA Options Future
Borsa Istanbul NA 4 658.1Johannesburg SE 8 934.8 25 155.6Moscow Exchange 4 040.0 483 914.0NYSE.Liffe Europe 2 324.6 37.3
Tel Aviv SE 108 322.8 0.0
Currency – annual volumes (USD million)
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Americas Options Future
BM&FBOVESPA 3 600 770.0 18 193 900.0Bourse de Montreal 569 518.0 23 217 400.0
Buenos Aires SE NA NA
CME Group163 885
000.0614 271
000.0
Colombia SE NA 32 850.9
MexDer NA 93 456.0NYSE Euronext (US) NA NA
APAC Options Future
ASX SFE Derivatives Trading 393 778.0 47 596 300.0
Bombay SE NA NA
China Financial Futures Exchange NA 50 232.7Hong Kong Exchanges NA 7.2Korea Exchange NA 4 084 080.0
National Stock Exchange India NA NA
Shanghai Futures Exchange 0.0 0.0
TAIFEX NA 2.2Tokyo SE Group NA NA
EMEA Options FutureBME Spanish Exchanges 0.0 1 413.4
EUREX 11 544 400.0 76 220 100.0Johannesburg SE 47.7 54 109.3London Metal Exchange NA NAMoscow Exchange 0.0 5 323.7NYSE.Liffe Europe 175 658 000.0 443 350 000.0OMX Nordic Exchange 915 175.0 3 560 020.0
Tel Aviv SE NA NA
Interest Rate – annual volumes (USD million)
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Americas ETF ETF Opt
BM&FBOVESPA 11 366.8 138.7
Colombia SE 1 070.1
Lima SE 9.8Mexican Exchange 104 903.9 1.8
NASDAQ OMX 6 695 703.4 NANYSE Euronext (US) 3 589 241.4 48 077.3
Santiago SE 117.1
TMX Group 73 824.8Bourse de Montreal NA 5 123.0
CME NA NA
ISE NA NA
APAC ETF ETF Opt
Australian SE 7 487.3
BSE India 1 118.3Bursa Malaysia 43.6Hong Kong Exchanges 116 431.5 16 776.7
Indonesia SE 2.1
Japan Exchange Group - Osaka 73 386.2 NA
Japan Exchange Group - Tokyo 163 170.1 NAKorea Exchange 178 724.6
National Stock Exchange India 2 132.8New Zealand Exchange 59.6
Shanghai SE 109 240.5
Shenzhen SE 36 707.2
Singapore Exchange 2 591.1
Taiwan SE Corp. 9 496.8
The Stock Exchange of Thailand 250.3
EMEA ETF ETF OptAthens Exchange 14.7BME Spanish Exchanges 5 732.2
Borsa Istanbul 4 350.9
Budapest SE 1.9Deutsche Börse 162 958.7
Irish SE 19.3Johannesburg SE 5 624.3 ~ 0
Ljubljana SE 0.0Luxembourg SE 0.0
NASDAQ OMX Nordic Exchange 15 593.7NYSE Euronext (Europe) 100 747.8
Oslo Børs 4 736.7
Saudi Stock Exchange - Tadawul 18.6SIX Swiss Exchange 98 074.8
Wiener Börse 5.3
ETF – annual volumes (USD million)
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Americas Options Future
BM&FBOVESPA 602.9 21 666.2
CME Group10 561 200.0 47 823 300.0
Colombia SE NA 6.6ICE Futures Canada 47.4 57 599.8
ICE Futures US 305 023.0 1 347 450.0NYSE Euronext (US) NA NA
APAC Options Future
ASX SFE Derivatives Trading 5 284.0 17 687.1
Bursa Malaysia Derivatives NA 151 944.0
Dalian Commodity Exchange NA 7 676 520.0Korea Exchange NA 161.1
New Zealand 0.0 132.1
Shanghai Futures Exchange NA 9 852 290.0
TAIFEX 717.9 1 146.7
Zhengzhou Commodity Exchange NA 3 074 910.0
EMEA Options Future
Borsa Istanbul NA 807.7
Budapest SE 0.0 138.5ICE Futures Europe 31 495.0 29 469 200.0Johannesburg SE 349.9 50 124.3London Metal Exchange 663 968.0 13 965 900.0Moscow Exchange 309.6 46 291.3NYSE.Liffe Europe 1 918.0 403 586.0
Commodity– annual volumes (USD million)
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Automated Trading System components
Application
Order Manager
Market Data
Complex Event Processing engine
Exchange 1
Storage
Application Server Exchange
Strategy Settings UI
State Mgmt (PnL + Position)
Order / Execution Monitor
Within application RMS
Maths Calc
RMS
Admin Monitor
Exchange 2
FIX
FIX
Data Normalizer
Order Router
Back office record
MktData Store
Event History
Adaptor for third party apps – R, Matlab, etc
Data Retrieval
Data Vendor
Replay of stored data
Simulator exchange
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
To connect to any exchange, you need to build(i) market data adaptor for that exchange’s protocol
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Automated Trading System components
Application
Order Manager
Market Data
Complex Event Processing engine
Exchange 1
Storage
Application Server Exchange
Strategy Settings UI
State Mgmt (PnL + Position)
Order / Execution Monitor
Within application RMS
Maths Calc
RMS
Admin Monitor
Exchange 2
FIX
FIX
Data Normalizer
Order Router
Back office record
MktData Store
Event History
Adaptor for third party apps – R, Matlab, etc
Data Retrieval
Data Vendor
Replay of stored data
Simulator exchange
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
To connect to any exchange, you need to build(ii) OMS adaptor to convey transaction information as per exchange protocol
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Technology Protocols globally
One of the most popular protocol is FIXFinancial Information eXchange protocol Data transferred as sequence of tag=value pairs
e.g.: 8=FIX.4.2 | 9=77 | 35=0 | 49=MCXSXTRADE | 56=xxxxx | 34=24 | 43=N | 52=20140607-05:14:05 | 112=DNLDCOMPLETE | 10=127
1 Account2 AdvId3 AdvRefID4 AdvSide5 AdvTransType6 AvgPx7 BeginSeqNo8 BeginString9 BodyLength10 CheckSum11 ClOrdID12 Commission13 CommType14 CumQty15 Currency16 EndSeqNo17 ExecID18 ExecInst19 ExecRefID
20 ExecTransType21 HandlInst22 IDSource23 IOIid24 IOIOthSvc (no longer used)25 IOIQltyInd26 IOIRefID27 IOIShares28 IOITransType29 LastCapacity30 LastMkt31 LastPx32 LastShares33 LinesOfText34 MsgSeqNum35 MsgType36 NewSeqNo37 OrderID38 OrderQty
39 OrdStatus40 OrdType41 OrigClOrdID42 OrigTime43 PossDupFlag44 Price45 RefSeqNum46 RelatdSym47 Rule80A(aka OrderCapacity)48 SecurityID49 SenderCompID50 SenderSubID51 SendingDate (no longer used)52 SendingTime53 Shares54 Side55 Symbol56 TargetCompID57 TargetSubID
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
ExchangeTransaction / Market Data Protocol Family Protocol
ASX - Australian Stock Exchange Transaction FIX ASX-Trade24-FIX
ASX - Australian Stock Exchange Transaction OUCH ASX-OUCH
BATS Transaction FIX BATS-FIX
BATS Transaction BATS Europe Binary Order Entry (BOE) BATS-Europe-BinaryOrderEntry
BATS Transaction BATS Binary Order Entry (BOE) BATS-BinaryOrderEntry
BME Spanish Exchanges Transaction FIX BME-SpanishExchanges-FIX
Bombay Stock Exchange Transaction IML IML/ETI
Bombay Stock Exchange Market Data EMDI NFCAST, ACAST, EMDI
Borsa Italia Transaction TradElect LSE-TradElect
Borsa Italia Transaction FIX Borsaltaliana-FIX
Borsa Italia Transaction Millennium Native Trading Borsaltaliana-Native Trading
Boston Exchange (BOX) Transaction SOLA Access Information Language (SAIL) BOX-SAIL
Bursa Malaysia Transaction/MarketData AMP BursaMalaysia-AMP
CBOE Transaction CMi Protocol (trading spec only) CBOE-CMi
CBOE Transaction CMi version 2 CBOE-CMi-v2
CHI-X Transaction CHI-X Australia FIX CHIX-Australia-FIX
CHI-X Transaction CHI-X Australia OUCH CHI-X-Australia-OUCH
CHI-X Transaction CHI-X Canada FIX CHIX-Canada-FIX
CHI-X Transaction CHI-X Japan OUCH CHI-X-Japan-OUCH
Technology Protocols globally
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
ExchangeTransaction / Market Data Protocol Family Protocol
Chicago Mercantile Exchange (CME) Transaction FIX CME-iLink-FIX
Deutsche Boerse Transaction Eurex v12 Enhanced Transaction Solution DBS-Eurex-ETS
Deutsche Boerse Transaction Eurex v13 Enhanced Transaction Solution DBS-Eurex-ETS-13
Deutsche Boerse Transaction Eurex v14 Enhanced Transaction Solution DBS-Eurex-ETS-14
Deutsche Boerse Transaction Eurex Enhanced Trading Interface DBS-Eurex-ETI
Deutsche Boerse Transaction Eurex FIX DBS-Eurex-FIX
Deutsche Boerse Transaction Xetra Enhanced Transaction Solution (v14 and v13) DBS-Xetra-ETS
Direct Edge Transaction FIX DirectEdge-FIX
Direct Edge Transaction MEP / XPRS (binary order entry) DirectEdge-Edge-XPRS
Fidessa Transaction/MarketData Fidessa API (European MultiMarket Access) Fidessa-EMMA
Hong Kong Exchanges (HKEx) Transaction AMS3 OpenGateway HKEx-AMS3-OpenGateway
Hong Kong Exchanges (HKEx) MarketData FIX FAST
Hong Kong Mercantile Exchange (HKMEx) Transactions EMAPI HKMEx-EMAPIICAP Transaction ICAP BrokerTec OUCH ICAP-BrokerTec-OUCHICE Transaction FIX ICE-FIXInternational Securities Exchange (ISE) Transaction FIX FIX
International Securities Exchange (ISE) Transaction Optimise Direct Trading Interface (DTI) ISE-Optimise-DTI
Johannesburg Stock Exchange Transaction Millennium Native Trading JSE-Millennium-Native-Trading
Technology Protocols globally
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
ExchangeTransaction / Market Data Protocol Family Protocol
Johannesburg Stock Exchange Transaction TradElect LSE-TradElect
Korea (KRX) Transaction KRX/Koscom PowerBASE Order-Entry API KRX-Korea-PowerBASE-NFS
Korea (KRX) Transaction KRX KMAP order-entry API KRX-KMAP
London Metals Exchange Transaction LME FIX LME-FIX
London Stock Exchange Transaction LSE-FIX LSE-FIX
London Stock Exchange Transaction Millennium Native Trading LSE-Millennium-NativeTrading
London Stock Exchange Transaction Turquoise FIX Turquoise-FIX
London Stock Exchange Transaction Turquoise Native Trading Turquoise-NativeTrading
London Stock Exchange Transaction TradElect LSE-TradElect
London Stock Exchange Transaction Interactive LSE-TradElect
Miami Exchange (MIAX) Transaction MIAX Express Interface (MEI) MIAX-MEI
NASDAQ OMX Transaction FIX NASDAQ-FIX
NASDAQ OMX Transaction Nasdaq FIX Lite NASDAQ-Flite
NASDAQ OMX Transaction Nasdaq OUCH v3.3 NASDAQ-OUCH-3
NASDAQ OMX Transaction Nasdaq OUCH v4.2 NASDAQ-OUCH-4
NASDAQ OMX Transaction NASDAQ OMX Nordic OUCH NASDAQ-OMX-OUCH-NORDIC
NASDAQ OMX Transaction NOM2 Ouch to Trade Options (OTTO) NASDAQ-NOM2-OTTO
NASDAQ OMX Transaction NOM2 Specialized Quote Interface (SQF) NASDAQ-NOM2-SQF
NASDAQ OMX Transactions Nasdaq RASHport NASDAQ-RASHport
Technology Protocols globally
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
ExchangeTransaction / Market Data Protocol Family Protocol
National Stock Exchange of India (NSE) Transactions NEAT Futures and Options NSE-India-NEAT-FuturesAndOptions
National Stock Exchange of India (NSE) TransactionsNon-NEAT Futures and Options
NSE-India-NonNEAT-FuturesAndOptions
NYSE Transaction Designated MarketMaker protocol NYSE-DMM
NYSE Euronext Transaction NYSE Euronext UTP-Direct NYSE-UTPDirect
NYSE Euronext Transaction NYSE US CCG Binary (UTP-Direct) NYSE-UTPDirect-US
NYSE Euronext Transaction NYSE CCG FIX NYSE-UTP-CCG-FIX
NYSE Euronext Transaction NYSE Liffe CCG Binary NYSE-LIFFE-CCG-Binary
NYSE Euronext Transaction ArcaDirect 4.x NYSE-ArcaDirect-4
NYSE Euronext Transaction Arca MarketMaker Direct NYSE-ArcaMarketMakerDirect
Osaka Stock Exchange Transactions Trading Interface OsakaSE-TradingInterface
Oslo Bors Transaction Native Trading OsloBors-NativeTrading
Pure Trading (CNSX market) Transaction/MarketData STAMP TorontoSX-STAMP
Singapore Stock Exchange (SGX) Transaction SGX FIX Trading Interface SGX-QuestST-FIX
SIX Swiss Exchange Transaction Quote Trading Interface SWX-QTI
SIX Swiss Exchange Transaction SWX Capacity Trading Interface SWX-CTI
SIX Swiss Exchange Transaction SWX Standard Trading Interface SWX-STI
SIX Swiss Exchange Transaction Swiss Exchange OUCH market data interface (OTI) SIX-OUCH
Technology Protocols globally
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
ExchangeTransaction / Market Data Protocol Family Protocol
Taifex Transaction/MarketData FIX Taifex-FIX
Thailand Stock Exchange (SET) Transaction/MarketData EMAPI SET-EMAPI
TMX group Transaction/MarketData STAMP TorontoSX-STAMP
TMX group Transaction/MarketData MX SAIL MontrealExchange-SAIL
Tokyo Stock Exchange (TSE) Transaction Arrowhead ESP TokyoSE-Arrowhead-ESP
Tokyo Stock Exchange (TSE) Transaction Tdex+order-entry TokyoSE-Tdex+
Tokyo Stock Exchange (TSE) Transaction FIX J-FIX
Warsaw Stock Exchange Transaction Order Entry Protocol WSE-CCG
SHFE Transaction FIX FAST
CZCE Transaction FIX FAST
Montreal Stock Exchange Transaction FIX FIX
Montreal Stock Exchange TransactionSOLA Access Information Language (SAIL) STAMP/ SOLA
Technology Protocols globally
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Country Regulation
European Union (HFT = 39%)
MiFID IIFTT proposed (11 countries agreed to participate – Austria, Belgium, Estonia, France, Germany, Greece, Italy, Portugal, Slovakia, Slovenia, Spain)
Germany (40%)
HFT firms to register with BaFin and obtain HFT licensesSupervisors at BaFin and the Exchange Supervisory Authority are allowed to requestdocument all algorithms used - descriptions of trading strategies or parameters and are permitted to deny the use of anyalgorithmic trading strategy they believe is undesirableappropriate order-to-trade ratio, todevelop a minimum tick size, fee for excessive system usage, includingamendments and cancelations of orders, and it requires traders to flag each order generated by analgorithm
France
Non-Transaction tax of 0.01% (replace / cancel)exceeding 80% of all orders transmitted in a monthTax if orders modified or cancelled in less than 0.5 second0.20% trasaction tax on purchased shares of companies with market cap > €1 billion (France’s share of EU equity turnover dropped from 23% in 2011 to <13% in 2013)
Regulations
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Country Regulation
USA (48.5% in 2013. 61% in 2009)
Pre- trade controls; post- trade controls; system safeguards; mandatory registration and ‐ ‐reporting;Standardized order types; testing of algorithms; documented evidence of capacity, integrity, resiliency, availability, and security adequate to maintain operational capability; scheduled testing; continuity and disaster recovery plans; system redundancy; financial transaction TaxesProposed: Inclusive Property Act 0.5% sales tax on most financial instruments,. Wall Street Trading and Speculators Tax Act: 0.03% tax on trading by financial institutions
Singapore 0.20% stamp duty on equity trading
Hong Kong (20%)0.1 % stamp taxHFT – detailed records and audit logs for at least 2 years. System testing once a year
ChinaStamp duty between 0.1% to 0.3%Complex rules wrt FII in China
Taiwan All orders to go through FMC
Regulations
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapesChina Singapore Hong
Kong Japan Korea Taiwan
Regulations Market –Equity Market - Currency x x xMarket - Cmdty x Market– Interest Rate x x x
Market - ETF Market - Options x TechnologyConstraints
Competition
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapesIndia Thailand Malaysia Israel Turkey Indonesia
Regulations Market –Equity Market - Currency x xMarket - Cmdty xMarket– Interest Rate x
Market - ETF x x xMarket - Options ~ x ~ x x xTechnologyConstraints Competition
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapesPhilippines Dubai Abu Dhabi Saudi
Arabia Vietnam Bahrain
Regulations Market –Equity x Market - Currency x x x x Market - Cmdty x x x x xMarket– Interest Rate x x x x x x
Market - ETF x x x x x xMarket - Options x x x x x xTechnologyConstraints
Competition
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapesEuronext OMX Eurex
Regulations Market –Equity Market - Currency xMarket - Cmdty xMarket– Interest Rate
Market - ETF Market - Options TechnologyConstraints Competition
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapesSpain SIX Swiss Moscow Oslo
Regulations Market –Equity Market - Currency x x xMarket - Cmdty x x xMarket– Interest Rate x x
Market - ETF x Market - Options TechnologyConstraints
Competition
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapesBM&F Bovespa
NASDAQ NYSE TMX
/ Mn CME MexDER ICE
Regulations
Market –Equity x xMarket - Currency x x Market - Cmdty x x x x Market– Interest Rate x x Market - ETF x xMarket - Options TechnologyConstraints Competition
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Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Algo trading in various landscapesJohannesburg Nigeria
Regulations Market –Equity Market - Currency xMarket - Cmdty xMarket– Interest Rate x
Market - ETF Market - Options xTechnologyConstraints Competition
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Most relevant factors in analyzing different geographies
Current AlgoTrading landscape in various geographies
The road ahead ?
Q&A
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Shift in market volumes
Likely threat of introduction of a HFT tax (financial transaction tax),
+Over crowding of US and European automated trading markets
Likely shift of volumes towards Asian, LatAm(increasing number of global firms setting up shop in India, Singapore, Hong Kong,
Brazil, etc)
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
↓
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Growth of market segments
Regulations in certain markets are going to introduce new destinations for algorithmic traders:
• Swaps traded electronically in SEFs instead of OTC– Post Dodd-Frank Wall Street Reform and Consumer Protection Act, four
categories of interest rate swaps and two categories of credit default swaps are going to be listed on SEFs (Swap Execution Facilities)
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
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Technology Simplification/Consolidation
Different exchanges shifting to standardized technology protocols instead of maintaining proprietary protocols
(Bombay Stock Exchange in India adopting Eurex Platform.Budapest, Bursa Malaysia adopting CME GlobexMultiple developing economy exchanges like Bursa Istanbul adopting FIX protocol)
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Technology Arms race no more ?
In a lot of aspects, we are reaching the limits of technology
+The cost of technology is also coming down
↓Therefore technology might no longer be the sole asset of privileged
market participants
↓Trading Alpha will again shift towards statistical excellence rather than
technological upper-hand
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Agenda
Relevant factors for analyzing different markets → Current landscape in different geographies → The future → QA
Most relevant factors in analyzing different geographies
Current AlgoTrading landscape in various geographies
The road ahead ?
Q&A
© Copyright 2010-2014 QuantInsti Quantitative Learning Private Limited
Copyright © 2014 by QuantInsti Quantitative Learning Private Limited.
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