Cross-Asset, Cross-Border Algorithmic Trading

Transcription

1 Cross-Asset, Cross-Border Algorithmic Trading Apama Track Dan Hubscher, Principal Product Marketing Manager, Progress Apama Progress Exchange Brasil 2009 Progress Exchange Brasil de Outubro São Paulo Brasil O Mais Importante Evento para a Comunidade Progress no Brasil

2 Apama Background Progress Software (NASDAQ: PRGS) Apama Complex Event Processing Platform Focus on Capital Markets Algorithmic Trading Risk Management Market Making Best Execution Multiple Asset Classes 120+ Global Customers Including Regulators, Exchanges, Banks and Buy Side institutions FI FX Other F&O EQ 2

3 The Capital Markets Trading Community Today Global rise of the alternative venues Market fragmentation Price/speed competition Regulatory drivers RegNMS, MiFID, etc. Volume & volatility Technology arms race Increasing market data The need for speed Automated trading evolution 2004 Broker algorithms News-driven Algorithms Smart Order Routing Proprietary algorithms

4 Cross-Asset Algorithmic Trading What & Why Automated trading When to trade Objective: seek alpha How to trade Objective: best execution Multi-Asset Trading Single platform Multiple asset classes Independent strategies Cross-Asset Trading Single platform Multi-asset strategies 4

5 Complex Event Processing Static Data Processing: How many orders were placed for a stock? time Complex Event Processing: When 3 orders are placed for the same stock within any 5 second window, stop any further orders being placed until all have filled 5

6 4 Frontiers of Algorithmic Trading Competition Rapid customization Cross- Algorithmic Speed/latency geography Trading advantage Crossasset class 6

7 Algorithmic Trading Rule Equities Example WHEN MSFT price moves outside 2% of MSFT Moving Average FOLLOWED-BY ( My Basket moves up by 0.5% AND ( HPQ s price moves up by 5% ALL WITHIN any 2 minute time period THEN BUY MSFT SELL HPQ multiple data streams temporal sequencing complex event sequences real-time constraints automated actions NASDAQ NYSE MSFT Moving Average My Basket 7

8 Apama Experience In Foreign Exchange Key FX Use Cases Aggregation Pricing Auto-Hedging & Risk Management Algorithmic Trading 8

9 Algorithmic Trading Rule Foreign Exchange Example!"#!" $!" %&!"'!"!" %&!" # $ "!" +!"%!"!" & ' +' &( *.$' ()*+,!" - %.- 9

10 Use Cases - Algorithmic Trading in FX Proprietary trading Monitor for opportunities Statistical arbitrage over time Statistical arbitrage between currencies Hedge or order implementation Minimize market impact Manage risk exposure ()*+,!" - %.- 10

11 Fixed Income Custom Rules-based Mean Reversion Algorithm WHEN 10yr:5yr VWAP Spread < Lower Band THEN BUY 10yr:5yr VWAP Spread WHEN 10yr:5yr VWAP Spread > Profit Line OR 10yr:5yr VWAP Spread < Stop Line THEN SELL Position Lower Band Mean Spread 11

12 Real-time Algorithmic Pricing Fixed Income MTS BrokerTec espeed Client Tiering MTS BT es Inter-dealer market Rules-based Algorithms Aggregated View Real-time Pricing Engine In-house bond-pricing analytics Trader parameters Skewing factors Target positions Inventory 12 Client history Traditional Bond Pricing Engine (?) RFQ Market factors, e.g. interest rates

13 Futures Spread Trading Example Apama Spreader hosted by FFastFill Hosted, integrated solution Manual and automated spread trading Multi-leg, multi instrument, multi-exchange models Links to external modeling tools, charting packages and news feeds Managed legging risk 13

14 Futures Automated Execution Example Apama AutoEx for CQG Integrated Client Hosted, integrated solution Apama automatic order execution Apama tools to adjust execution strategies on the fly CQG network of collocated low-latency Hosted Exchange Gateways Comprehensive end-to-end performance from signal generation to execution 14

15 Commodities: PTRM for Energy Markets Programmatic Trading and Risk Management Programmatic Trading Limit orders / Guard algorithms Spreads (statistical arbitrage) - Calendar - crack - location - spark/dark Smart Order Routing Automation loss of control?? Real-time risk assessment 15 Limit management Risk Firewall Stop-loss & Algo Auto-hedging Smart Risk for trade performance Concentration Risk Heat Map

16 Commodities: PTRM for Energy Markets Asset Optimization via Asset-backed Trading Internal Market Crossing Asset topology modelling for integrated utilities Asset-backed trading across the value chain Supply-demand matching Optimised plant despatch 16

17 Modeling Trading Strategies Event Modeler Monitor Spread Orders Placed Orders Filled Orders Timed Out 17

18 Real-time, Event-based Platform for Building Applications Business & IT Tools - Apama Workbench Graphical Development Dashboard Builder Code-based Development Event Modeler Alpha-seeking & execution rules: Equities Foreign Exchange Fixed Income Futures Commodities Cross-asset...and more Inputs Market data Orders Any event Actions/Output Orders Derived data Dashboard interaction 18

19 Cross-Asset Statistical Arbitrage CEP easily enables cross-asset capabilities in the same platform Opening up a range of advanced opportunities BM&F Algorithmic Engine Cross-Asset StatArb Algorithm Customized rules Trader Bovespa Customer Example: Alpes 19

20 Algorithmic Trading Rule - Cross-Asset Statistical Arbitrage Example When there is a discrepancy between the actual and expected delta one-to-one price of cash and future of a US Treasury Then automatically buy one and sell the other with the best price available across espeed and BrokerTec available across espeed and BrokerTec 20

21 Cross-Asset Auto-Hedging Many firms are taking positions in derivatives to hedge positions US Treasuries against CBOT futures EuroGovvies against Eurex futures Equities against futures Algorithms can automatically re-hedge these positions as the underlying factors cross specified thresholds espeed BrokerTec CBOT Algorithmic Engine Auto-hedging Algorithm Customized rules Trader Eurex 21

22 Cross-Asset Algorithmic Trading Sample Customer Projects Rapid customization Options against futures Crossgeography Algorithmic Trading Speed/latency advantage Cash treasuries against treasury futures Cross-asset class FX spot against FX futures Cross-border listed equities with a spot FX leg Exchange-traded multi-leg spreads (two or more legs) 22

23 4 Frontiers of Algorithmic Trading Competition Rapid customization Cross- Algorithmic Speed/latency geography Trading advantage Crossasset class 23

24 Apama Connectivity Broad range of proven adapters Market data, liquidity venues, bank portals Continuing expanding list Adapter framework offers cross-asset support Low latency normalization of disparate formats Integration Adapter Framework Adapter Adapter Adapter Adapter 24 24

25 Apama Connectivity Market Data Reuters Activ Financial Dow Jones Elementized News Feed KOSPI (Korean Composite Stock Price Index) Nexa Tickstream Wombat Lime Brokerage (Citrius) Equities Markets Market Data Market Data sources (listed above) Bovespa Other direct connectivity 2 Order Execution FIX Bovespa EMS/OMS/FIX Gateways (listed right) Direct Bank/Broker Connectivity (listed below) Other direct connectivity 3 Analytics MATLAB Quantlib (select functions) Intel Math Library (select functions) CQG Direct Foreign Exchange Markets EBS Spot Ai Hotspot FX Currenex FXall Accelor Lava FX Spot FX Reuters Dealing 3000 BGC Direct Futures & Options Markets Euronext.Liffe Intercontinental Exchange (ICE) Chicago Mercantile Exchange (CME/NYMEX) Eurex ELX BM&F Direct Bank Connectivity Barclays Deutsche Bank Autobahn UBS Goldman Sachs ITG Penson Brokerbox Lime Brokerage Morgan Stanely Direct Fixed Income Markets ICAP Brokertec BGC (espeed) Tick Databases Vhayu/Reuters Tick Capture Engine KX Systems kdb+ EMS/OMS/FIX Gateways Transact Tools Aegis Gateway (Athena Trader) Ulbridge (Odisys) GL Trade Cameron Trading Technologies (TT) Pro Nexa Fastpath IRESS CQG FlexTrade Fidessa Infrastructure Adapters JMS JDBC ODBC Sonic Tibco Rendezvous Tibco Talarian Sonic 1. If a source or destination is not shown, please inquire with your Apama representative as to its status, as new adapters are always being built and can be built as required. 2. Direct connectivity can be provided as an alternative to market data sources listed 3. The Apama FIX adapter can be configured for direct connectivity to any FIX destination 25

26 Markets Served West Coast Mexico City Chicago Toronto Boston New York Stockholm London Paris Madrid Amsterdam Eastern Europe & Russia Bologna Middle East Seoul Tokyo China India Hong Kong Singapore Currently Sao Paolo South Africa Sydney Melbourne Developing 26 26

27 Trading in the Cloud Exchange collocation enables competition in: Cross-geography Speed/latency Rapid customization Software-as-a-Service Quick time to market Minimal investment Crossgeography Algorithmic Trading Speed/latency advantage Cross-asset Hosted class Easy access Optional connectivity to any other trading venues and market data sources Apama Examples CQG Automated execution for commodity & FX futures BGC Algorithmic trading for Fixed Income cash & futures FFastFill Automated futures spread trading & global exchange collocation 27

28 Real-time, Event-driven Model Event Modeler Any business update is an event Asset neutral Market agnostic Broad connectivity Leverage trader s market knowledge Monitor Risk Orders Placed Cash Futures 28

29 Conclusions Attract new business Compete across borders and asset classes Seek alpha, best execution, manage risk Customize leveraging market knowledge Markets are continually evolving First Mover Advantage Customization is now KING Create intellectual property for competitive differentiation Custom rules-based trading is critical Trading firms look to Apama for a platform Create trading strategies that exploit their unique trading ideas 29

30 THANK YOU Q&A SESSION CONTACT US Dan Hubscher Principal Product Marketing Manager, Progress Apama Web: Blog: 30