Progress Apama – Complex Event Processing for the Financial Markets

1. Progress Apama – Complex Event Processing for the Financial Markets Alexander Sirotin Director of Sales. CIS, CEE RegionApama Capital Markets 11 November 2009

2. Trade settlement 5 days 2 hrs. Business Velocity Is Key to Efficiency mail express fax e-mail Document transfer Business Requirement Algorithmic trading 100 ms 20 ms Reduce processing time Airline operations 20 min 30 sec Design Strategy Call center inquiries 8 hr 10 sec Track financial position 1 day 5 min STP, zero-latency enterprise 15 min 1 day Supply chain updates Phone activation 3 days 1 min Refresh data warehouse 1 week 0.5 hour Build-to-order PC 4 weeks 1 day Typical Business SLAs106 105 104 103 100 10 1 0Seconds

3. ► 83% believe IT has a major influence on the ability of businesses to adapt and change ► 77% believe availability and timeliness of information is inadequate to support this change ► The velocity of information is not keeping up with the speed of business We’re told that information is not timely enough Survey of 500 European Business and IT Leaders Source: Vanson Bourne Research, 2008

4. Conventional Ways of Examining Business Information Always looking in therear view mirror How can I examine what is happening and react now?

5. Market Leadership • Industry Recognition:The Forrester Wave™ • Leadership in architecture, features, market presence and strategy “Progress Apama earned high marks for its event processing features, its development tools, and it business end-user tools, propelling it into its position as a Leader.” The Forrester Wave™: Complex Event Processing (CEP) Platforms, Q3 2009

6. CEP Market Size • Now: $141M globally • 2012: $803M • Compound Annual Growth of 55% Apama is a Leader in CEPFrom IDC report: “Complex Event Processing Opportunity Analysis and Assessment of Key Products”, February 2009

7. Trends in the Financial Sector

8. Equity data rates have been increasing Total number of equity trades Source: World Federation of Stock Exchanges

9. Equity data rates have been increasing Source: World Federation of Stock Exchanges

10. Derivatives data rates are exploding Source: OPRA

11. Derivatives data rates are exploding Source: Euronext Liffe

12. In general Order sizes = + Data! Trading volumes

13. Algorithmic trading is now everywhere

14. Algorithmic Trading – What & Why Automated trading When to trade Objective: seek alpha Continuously re-calculate analytics Monitor thresholds/rules Stat arb Spread Index arb How to trade Objective: best execution Order execution policy Slice up orders (wave trade) Route across liquidity pools (smart order routing) In market limit + timeouts Out of market limits (“electronic eye”) Calculate 10 minute moving average Calculate 5 minute moving average Monitor for moving averages crossing Wave trade order over next 2 hours based on historic volume profile Route child order to liquidity pool with best price

15. High Frequency Trading Rule 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% OR MSFT’s price moves down by 2% ) ) ! ALL WITHIN any 2 minute time period My Basket ! ! MSFT Moving Average ! NYSE NASDAQ THEN BUY MSFT SELL HPQ time • multiple data streams • temporal sequencing • complex event sequences real-time data streams • real-time constraints • automated actions

16. Apama The offering What our customers are doing

17. Apama Clients in Capital Markets include:

18. Key Applications Applications Examples Customers Solution Accelerators • Algorithmic Trading • Alpha Seeking & Execution • VWAP, TWAP, etc • Multi-Asset, Cross Asset • Buy Side, Sell Side, Prop Trading Algorithmic Trading • Market Making & Aggregation • Liquidity Discovery • Market Making • Smart Order Routing & Execution • Auto Hedging FX Aggregation • Surveillance • Compliance • Risk Management • Market Abuse Detection • Market Maker Monitoring • Op Risk, Business Control • Risk Firewall, Auto Hedging Market Surveillance • Best Execution • Smart Order Routing • Aggregated Execution • Compliance Smart Order Routing MajorTier 1Bank • Market Making & Pricing • Intelligent Pricing, Skewing, Tiering • Market Making Real-Time Pricing GlobalTier 1Bank 18

19. Real-time, Event-based Platform for Building Applications Inputs Market data Orders Any event Alpha-seeking & execution rules: Crossover Momentum trading Statistical arbitrage Index arbitrage Iceberg VWAP Market participation Order slicing ...and more… Business & IT Tools - Apama Workbench Graphical Development Event Modeler Dashboard Builder Code-based Development Actions/Output • Orders • Derived data • Dashboard interaction

20. Apama Solution Accelerators Solution Accelerators . . . Real-time Pricing … Algorithmic Trading Market Surveillance FX Aggregator Smart Order Router Capital Markets Framework Sub-Systems & Components Risk Firewall MarketData Position Services Order Mgmt TradeServices Order Book Status Utilities … Apama CEP Platform 50+ Market & Infrastructure Adapters

21. Algorithmic trading accelerator • Algorithms • Alpha-seeking & Execution • Cross-asset support • Backtesting facility • Strategy Design • Business & IT Tools • Dashboards • Pre-built • Customizable • Integrated CMF Components • Exchange simulator • Risk & position management • Trader P&L • Broad Connectivity • Market Data & Execution • Infrastructure • Customizable

23. Anatomy of the VWAP algorithm

25. Apama Connectivity 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

26. Exchange collocation – enables competition in: Cross-geography Speed/latency Software-as-a-Service Quick time to market Minimal investment Hosted 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 Trading in the Cloud Rapid customization Algorithmic Trading Cross-geography Speed/latency advantage Cross-asset class

27. CQG and Progress partnership

28. Integration PointSystems DBMS Middleware Other… Building and Deploying an Apama Application Adapters connect the event processing engine to the IT environment. Pre-packaged adapters can be dynamically deployed, configured, and modified. New adapters can be built quickly

29. Smart BlockAnalytics Integration PointSystems DBMS Middleware Other… Building and Deploying an Apama Application CEP Smart Blocks encapsulate common analytics and domain specific functionality (for example, libraries of statistical analytics)

30. Scenariomodelling Smart BlockAnalytics Integration PointSystems DBMS Middleware Other… Building and Deploying an Apama Application Event based scenarios can be modelled using a GUI tool. Business analysts can develop, configure and deploy scenarios themselves

31. Customers &partners End-User Dashboards Scenariomodelling Smart BlockAnalytics Integration PointSystems Database Middleware Other… Building and Deploying an Apama Application

32. What to do About it Now:Use Own Automated IP for differentiation Fears of the Black Box If everyone has the same algo then the competitive advantage is reduced Limited scope to use your skills – can only parameterise Markets are continually evolving with new opportunities emerging Need to develop new strategies fast Spot opportunity Design strategy Backtest and deploy Customization is now king If everyone has the same black boxes: no competitive advantage Leverage own intellectual property for competitive differentiation Custom “rules-based” trading is becoming critical

33. User Front Ends ECNS Exchanges Market Data Vendors Prop Trader Security and Compliance Staff Apama Connectivity APAMA PLATFORM at BROKERAGE MARKET DATA AND EXCHANGES

34. FSA Surveillance Case Study

35. All Participants Are Interested In Surveillance and Monitoring Orders (proprietary and client) Broker Surveillance and Monitoring Trading Venue (Exchange, ECN etc.) Regulator

36. What Needs To Be Done - The 4 Facets Of Monitoring Market Abuse Surveillance Proscribed scenarios e.g. front running, fictitious orders, painting the tape etc Liquidity and spread monitoring, associated market halts, price /volume spikes, abnormal concentrations Market Monitoring Operational Monitoring Throughput, competitiveness, movements from normal behaviour Both sides of book (efficient internal matching), rogue algorithms, best execution, internal controls and limits Management & Control

37. The Business Driver of FSA’s Sabre II The FSA are concerned that market abuse continues to be a significant issue. For example, FSA researchers have detected price movements, suggesting “informed trading” may have taken place prior to 28.9% of takeover announcements and 21.7% of the FTSE350 trading announcements, and which were identified as being most likely to contain information of use to an insider trader. Sally DewarDirector of Markets Division, FSAMay 2006 Speech

38. SABRE II Requirements • Process Information in Motion! • Market events, news events, multiple sources of events, multiple exchanges • Easy To Use, User Friendly System • Graphical display of complex data relationships (web and thick-client) • Tools that are easy to use and easy to configure • Intuitive Alert Programming Language • Well developed mature programming language • Powerful multi-exchange and multi-instrument type language features • Truly integrated alerting across all combinations of integrated data • Satisfy MiFID Requirements • MiFID data feed acquisition • MiFID policy calculations & reports • MiFID inter-regulatory reporting

39. Deep historical analysis Develop market connectivity Create and evolve alert rules Market conduct teams and “Super users” IT and data analysts Develop dashboards Monitor alerts Manage alerts Alert analysts & company monitoring Monitor companies Usage Model at FSAIntegrated RAD environment Fully integrated, rapid development environment

40. Apama The SABRE II ArchitectureA next-generation, world-class market surveillance and market abuse detection platform Market conduct teams, alert analysts, etc. Business IntelligenceHistorical abuse analysis Historical abuse patterns LSE Alert rule Instances LSE Adapter virt-x Adapter Abuse detectionscenarios

41. Example: Fraud DetectionThe UK Financial Services Authority

42. Conclusions

43. ComplexEventProcessing An event driven market surveillancearchitecture Market conduct teams, alert analysts, etc. Market data Rule definitionand refinement Abuse detectionscenarios Social Networking Historicalabuse analysis Replay androot-causeanalysis