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Microsoft StreamInsight Capital Market Solutions
 

Microsoft StreamInsight Capital Market Solutions

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Presentation given at Microsoft's Drive Customer Connections events - May 26th 2010, New York

Presentation given at Microsoft's Drive Customer Connections events - May 26th 2010, New York

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Microsoft StreamInsight Capital Market Solutions Microsoft StreamInsight Capital Market Solutions Presentation Transcript

  • StreamInsight A Capital Markets Tale
  • Agenda 2 StreamInsight: A Capital Markets Tale About Lab49 (Very Brief) Overview Of Microsoft StreamInsight Complex Event Processing (CEP) Capital Markets StreamInsight Solutions • Market Strategy Engine • Market Real-Time Risk (RTR) - SQL Server 2008 R2 • Market Real-Time Risk - Windows AppFabric Caching (Velocity) Lessons Learnt
  • About Lab49
  • Lab49 4 About Us We create advanced solutions for the We combine the skills of our practices to financial services industry through strategic deliver innovation: and technical consulting: • Strategy group • Working with the world’s largest investment • User Experience practice banks, hedge funds and exchanges. • Development practices • Designing and delivering some of the most alongside the adoption of some key tenets: sophisticated and forward thinking financial applications. • Domain Driven Development • Applying user-centred principles to the world of • Lean Agile Process bespoke software. Our History • From concept to complete, ui to server. Lab49 was founded in 2002 and now comprises approximately 200 people, with offices in New York and London.
  • 5 About Us Matt Davey Part of the TAP program since July 2009 Requester for various StreamInsight V1 features: • Count Window • Dynamic Query Composition at Runtime
  • Overview Of Microsoft StreamInsight Complex Event Processing (CEP)
  • CEP in Finance 7 CEP in Finance • Banks are using CEP for feeding data into algorithmic trading systems as well as for finding dealing opportunities and trading pairs across asset class. • Risk monitoring, fraud detection and surveillance are also growth areas for CEP
  • StreamInsight Features 8 StreamInsight Features • Process large volumes of events across multiple data streams in < 1 second • Provides built-in support for different event types and rich query semantics • Reduces development cost by utilising existing skill sets and investment in Microsoft development platform • Flexible deployment options
  • StreamInsight (CEP) Application at Runtime CEP Engine Event Standing Queries Event Event Event Input Output Event Adapters Adapters 9 StreamInsight Event Event Event Event
  • 10 Market Strategy Engine StreamInsight Deployment
  • Capital Markets StreamInsight Solutions
  • Market Strategy Engine
  • Markets are Changing 13 Market Strategy Engine • Markets are becoming more complex • StreamInsight offers a cleaner way to process events in this complex world • Algorithmic trading has become mainstream • StreamInsight enhances the cleansing/validation of market data, order execution/management, pricing engines and more • Speed and latency are critical to maximising profitability • StreamInsight’s leverages the Microsoft development platform to improve speed of development coupled with Microsoft’s commitment to “Process large volumes of events across multiple data streams” in “low latency” • Back testing in the search for new strategies • StreamInsight’s adapter architecture allows easy access to historical market data repositories e.g. kdb+
  • The Problem - Butterfly Strategy 14 Market Strategy Engine Leg Buy/Sell Working Leg Price Weight Size Weighting Bobl Buy Yes 1 1 Bund Sell No -0.28 0.28 Schatz Sell No -1.19 1.19 Buy 10 Bobl 10 Fly @ -49 Sell 3 Bund Sell 12 Schatz
  • StreamInsight Engine Flow 15 Market Strategy Engine (1) (3) (2)
  • Take Aways 17 Take Aways Benefits over existing non-CEP based strategy engines • StreamInsight offers the advantage and benefits of CEP principles • Working and reasoning with Time - dealing with out of order arrivals Benefits over existing competitor CEP based strategy engines • LINQ/.NET implementation • Easy integration to other Microsoft products • Lower total cost of ownership
  • Market Real-Time Risk: SQL Server 2008
  • Market Risk 19 Market Risk Market risk is the risk that the value of a portfolio, either an investment portfolio or a trading portfolio, will decrease due to the change in value of the market risk factors
  • Why The Need For Real-Time Risk (RTR)? 20 Why The Need For Real-Time Risk (RTR)? Investment banks need to hedge their positions Latency T-1 and warehousing - PnL Explain Servers are cheaper and faster than workstations Improved Aggregation and drill-down
  • High Level Architecture 21 High Level Architecture Streaminsight F# Agent Market Depth Strategy Strategy Definition LINQ Orders Agent Agent (F#) Market Agent (F#) Agent (F#) LINQ Leg Orders Trade LINQ Cancel Aggregation Shocking Curve Engine Market Risk HPC (GPU?)
  • Aggregation Engine Architecture 22 Aggregation Engine Architecture Static Data Microsoft StreamInsight Position Database Microsoft Analysis Input Output SQL Adapter Adapter Server 2008 R2 Services LINQ Risk Real-Time OLAP Input Push Output Cube Adapter Adapter XMLA Server Client Excel
  • RTR Highlights 23 RTR Highlights • StreamInsight process Risk data, feeding SQL Server 2008 R2 • StreamInsight provides the XMLA service with real-time push notifications - e.g. portfolio ID’s • “XMLA” Server sits between the client and SQL Server intercepting client requests, and providing “push” services (smart polling, subscription manager)
  • Live Demo
  • Take Aways 25 Take Aways Compared To Other Solutions • The Microsoft solution offers a modularised real-time risk solution that is customisable • It’s a complete Microsoft (.NET) stack • Leveraging SQL Server 2008 R2 Analysis Services - (ROLAP for T, and MOLAP T-x) Performance • We can improve further by adding another Microsoft product......
  • Market Real-Time Risk: Windows AppFabric Caching (Velocity)
  • Velocity RTR Architecture 27 Velocity RTR Architecture Static Risk Warehousing Data Microsoft StreamInsight Position Database SQL Microsoft Analysis Input Output Adapter Adapter Server 2008 R2 Services LINQ Risk Real-Time Input Push Output OLAP Adapter Adapter Cube Windows Server XMLA Server AppFabric XMLA Server Caching (Velocity) Client Excel
  • Database vs Cache 28 Database vs Cache Database Cache Notification Notification Service deprecated in SQL Server 2008 Windows AppFabric Cache Notification OLAP Cube Analysis Service Custom build of an in-memory cube Scalability Out the box partitioning, hot-hot support Distributed Cache
  • Take Aways 30 Take Aways Compared To Other Solutions • The Microsoft solution offers a modularised real-time risk solution that is customisable • It’s a complete Microsoft (.NET) stack • Best of both worlds • SQL Server - backup, warehousing (ROLAP for T, and MOLAP T-x) • Distributed Cache - performance
  • Closing
  • Lessons Learnt 32 Lessons Learnt Business • StreamInsight improves the delivery timeline of business solutions Technology • CTI and AdvancedTimeImportSetting • V1 Ugly Code Issues • Nested classes • Static UDF • UDF’s offer lots of extensibility • Reactive Framework (Rx) usage • .NET 4 Not currently supported
  • thank you for your time… any questions? matt davey (matt.davey@lab49.com) mdavey.wordpress.com | Tales from a trading desk
  • Principles of CEP 34 Principles of CEP • Events are technology-neutral occurrences of interest, such as a new purchase, a change of address, or an attempt to break into a network. Events can come from people, devices, applications, networks, or databases. • Events have context, that is, an instance of an event implies timing (when it happened, both in absolute terms and relative to other events), sequence (again relative to other events), and linking relationships to other events (patterns of events, either expected or implied). • Events can also carry information about themselves. For example, a "purchase" event might contain the product purchased and the purchaser. • Events can be evaluated, either based on their context, their data, or additional data that may not accompany the event but is relevant (for example, is the purchaser a gold customer?). • Events form patterns in time and/or sequence that may be interesting. For example, a change of address followed by the reporting of a lost ATM card may indicate an attempt to profit from identity theft. • Events comprise ad hoc processes, a sequence of activities that results in the execution of a process. For example, a revenue recognition process may be composed of the events "contract signing," "purchase order received," and "product shipped." An explicitly defined process automated using events is called an Event Flow. • Events may be abstracted into other events. For example, a change of address event followed by the reporting of a lost ATM card event may be represented by the compound event "Attempted Fraud." • Events can optionally generate responses, or actions. For example, an "Attempted Fraud" event may trigger, in some cases, a "Put Account on Referral" action to make sure downstream account activity is legitimate.