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Progress Apama – Complex Event Processing for the Financial Markets

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Presentation on theme: "Progress Apama – Complex Event Processing for the Financial Markets"— Presentation transcript:

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

2 Business Velocity Is Key to Efficiency
Strategic Imperative: Companies must continuously find ways to speed up their business to respond to customer demands and competitive pressures. mail express fax Document transfer Business Requirement Algorithmic trading Reduce processing time 100 ms 20 ms 20 min 30 sec Airline operations Design Strategy 8 hr 10 sec Call center inquiries STP, zero-latency enterprise 1 day 5 min Track financial position 1 day 15 min Supply chain updates 3 days 1 min Phone activation 1 week 0.5 hour Refresh data warehouse Trade settlement 5 days 2 hrs. Build-to-order PC 4 weeks 1 day The Business Pipeline Pipeline Velocity is Accelerating in all businesses E.g. Financial Trading is 10x the volume of 5yrs ago SLAs on most manufacturing is half what it was 10 years ago Virtually all retail fulfillment is next day ship… remember “allow 4-6 weeks for delivery”? It wasn’t that long ago. Note’s from Roy’s presentation: Many business managers are focused on reducing the time it takes to execute their business processes and activities. Speed underlies many modern management strategies, including the zero-latency enterprise (ZLE), "time-based competition," straight-through processing (STP), and "just in time" inventory (note that real-time enterprise and event-driven enterprise generally are synonyms for ZLE). When an order is placed online, the expectation is that the goods will arrive "faster" than in the past. When someone applies for an insurance policy or submits a claim, he or she expects a quicker decision and more visibility into the process. These expectations require remaking supply, distribution, service and marketing infrastructures. A classic example of increased business velocity can be found in PC manufacturing. The entire process — talking to the customer, configuring a system, manufacturing, testing, shipping and transferring funds from the customer's bank account — takes less than 24 hours (in some cases). Short "quote to cash" cycle times require fast, closely knit applications, often implemented using EDA, with or without BPM. Action Item: Business managers and analysts must identify which of their business processes should be accelerated to produce meaningful improvements in business results. Not all processes need to run fast. Typical Business SLAs Seconds

3 We’re told that information is not timely enough
Survey of 500 European Business and IT Leaders ► 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 Survey methodology The survey carried out on behalf of Progress Software was conducted by Vanson Bourne Research in March blue chip companies were surveyed in a number of industries across Europe to assess enterprise IT capabilities in today’s fast-moving and complex business environment. The survey was carried out using a mixture of telephone polling and questionnaires among a sample of 500 made up in equal parts of 250 CIOs/ IT Directors and 250 business leads and departmental heads. The surveys were conducted across the following European countries: Belgium, Finland, France, Germany, Italy, The Netherlands, Spain, Sweden, Switzerland, and United Kingdom. The survey covered businesses in the following sectors: Financial Services, Manufacturing, Professional services, Retail, Telecommunications, Travel, Transportation and Logistics. Source: Vanson Bourne Research, 2008

4 Conventional Ways of Examining Business Information
Always looking in the rear view mirror Conventional BI is about running reports on the past. Valuable but if you want to know what’s happening NOW, it’s not good enough. 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 Now: $141M globally 2012: $803M CEP Market Size
Compound Annual Growth of 55% Apama is a Leader in CEP From IDC report: “Complex Event Processing Opportunity Analysis and Assessment of Key Products”, February 2009 Comment: what proportion outside capital markets? IDC (September 2008): CAGR of 55% between 2008 and 2012 Market worth $141M globally in 2008 rising to $803M by 2012

7 Trends in the Financial Sector

8 Equity data rates have been increasing
Total number of equity trades According to a recent report from DB Trading volume in S&P 500 is up 50% in 12 months. Average size of trade down 25% Between the end of 2006 and 2007 the number of equity trades increased by about 40% on Nasdaq On NYSE by 60% This is combined with smaller order sizes. Between 2006 and 2007 average value of orders dropped by 40% Picture is of the crab nebula 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
Now let’s look at derivatives. Who are the Options Price Reporting Agency? Some kind of central american body for reporting on options pricing. Between 2004 and 2008 (estimated) the number of orders will have risen by 20 fold. Source: OPRA

11 Derivatives data rates are exploding
So, not only are equities volumes rising, but those on derivatives exchanges are exploding. Between 2004 and 2008 (estimated) total trades on Euronext Liffe will have nearly doubled. Source: Euronext Liffe

12 + = In general Order sizes Trading volumes Data!
Algo trading has caused this. Algo trading is the answer to this too! Trading volumes Data!

13 Algorithmic trading is now everywhere
At least 80% of equity trades in US/EU go through an algo Probably half of FX trades 40% of exchange traded derivatives 25% of bonds. It’s everywhere in the world. It’s part of the DNA of trading organisations.

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 What are the big uses of algo trading? Productivity. Fewer traders covering more of the market. Traders doing the boring, easy trades. Have time to spend on the more advanced stuff. This doesn’t necessarily need HFT, just “good-enough” frequency trading. Then, of course, there’s alpha generation. High frequency is important for this. But for now, Controversy about algorithmic trading dominates the news worldwide, currently under the umbrella term high frequency trading. Coverage has appeared in the US the last few months in the WSJ, NYTimes, Time Magazine, and now even on a Comedy television program called the Daily Show, which is a for the general audience and makes fun of everything that’s in the news. By this point there is no doubt that algorithmic trading has become a key component of the trading arsenal of many firms. But all the hype clouds the issues, so let’s start with what algorithmic trading is, and what it sets out to achieve. In the Apama view, algorithmic trading is the automation two things - Alpha & Execution – specifically like this: <CLICK> The investment decision - What and When to Trade: strategies that leverage computing power and sophisticated mathematical and statistical models to identify alpha investment opportunities. <Click> The execution decision - How and Where to Trade: identification, placement, and execution of orders based on predefined trading goals. Algorithms are designed to capture real-time trading opportunities by identifying tiny market inefficiencies based on various factors, including price, volume, liquidity, benchmarks, and so on- basically, achieving best execution. Some of the drivers for Algo Trading Automation in Capital Markets include: Increased electronic trading, volatility, volumes, and market fragmentation More complex instruments Reduced spreads Regulatory imperatives, e.g. MiFID, RegNMS And perhaps most importantly… Increasing competition

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 NASDAQ NYSE MSFT Moving Average My Basket THEN BUY MSFT SELL HPQ time multiple data streams Let’s take a look at a high frequency trading rule That results from a model such as on the previous slide as an example of how this is done. Starting with the following real-time data streams:… [Animate & Read] temporal sequencing complex event sequences real-time data streams real-time constraints automated actions 15

16 The offering What our customers are doing
Apama The offering What our customers are doing

17 Apama Clients in Capital Markets include:

18 Solution Accelerators
Key Applications Applications Examples Solution Accelerators Customers 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 The solution accelerators are, to use a phrase, Apama’s “Productization of a Solutions-based approach” to solving business problems in trading. < Click through > So here is a vew of key applications in trading, mapped to the Apama accelerators that jumpstart the development and deployment of those applications, and mention of a few customers that use them. We will talk about some more of these acclerators later today in the other sessions. But the point to remember now is that the more you automate in the future, across both trading functions and across asset classes, the more we can help. Smart Order Routing Aggregated Execution Compliance Smart Order Routing Major Tier 1 Bank Market Making & Pricing Intelligent Pricing, Skewing, Tiering Market Making Real-Time Pricing Global Tier 1 Bank 18 18

19 Real-time, Event-based Platform for Building Applications
Business & IT Tools - Apama Workbench Graphical Development Event Modeler Dashboard Builder Code-based Development Alpha-seeking & execution rules: Crossover Momentum trading Statistical arbitrage Index arbitrage Iceberg VWAP Market participation Order slicing ...and more… Inputs Market data Orders Any event Apama’s run-time environment includes the Event Correlator, the technology expression of CEP. The alpha-seeking and execution rules are expressed within the correlator as a set of WHEN/THEN (rather than IF/THEN) conditions, which: Monitor the inputs such as market data Analyze events in those data streams according to the WHEN/THEN rules, such as a Stat arb algorithm, And Act – initiating orders to the market in real time And if there’s one unique point about Apama that I want you to remember from this slide here it is… we are talking about the ability to handle both the event stream processing, AND the business logic analysis and action, in the same paradigm, both of which therefore benefit from an advanced architecture. There is no need when creating an application to leave the Apama context after building the event collection and pattern detection, and then implement the business logic and automated action in a different language that doesn’t benefit from the performance characteristics that Louie will describe in just a minute. This offers benefits to your trading applications that others will either struggle to implement in their architectures or struggle to optimize for performance when handing off to an environment that doesn’t benefit from the event based architecture. In this complete architecture everything happens in real time… this is the essence of being able to Run FAST, the speed/latency frontier of algo trading competition. Actions/Output Orders Derived data Dashboard interaction 19 19

20 Apama Solution Accelerators
Algorithmic Trading Market Surveillance FX Aggregator Smart Order Router Real-time Pricing . . . Capital Markets Framework Sub-Systems & Components Market Data Trade Services Position Services Order Book Order Mgmt Status Utilities Risk Firewall Apama CEP Platform So here is a view of the accelerators and other parts of the tool kit, in the context of the rest of the Apama product. The BLUE platform in the middle is an expression of the event processing architecture and other technology components around it, and we’ll talk a more about that in just a little bit. Underneath that is a framework of over 50 Adapters that is always growing and provides two things: Built-in Connectivity to capital markets destinations and general infrastructure elements An open toolkit for modifying existing adapters and building more. On top of the platform is the Capital Markets Framework, a set of capital markets specific subsystems, components, and smart blocks that perform reusable common functions such as trade and position services and risk checking And on top of that is our set of solution accelerators, accelerating the deployment of applications built around key capital markets business areas – and right now we are speaking specifically of Algorithmic trading. But so that you know what the future holds as you tackle more and more trading issues on a global scale with automation, here are a few other accelerators 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


23 Anatomy of the VWAP algorithm


25 Apama Connectivity Market Data Equities Markets Analytics
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 4.0 – 4.4 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 FlexTrade Fidessa Infrastructure Adapters JMS JDBC ODBC Sonic Tibco Rendezvous Tibco Talarian 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 Speed/latency advantage
Trading in the Cloud 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 Algorithmic Trading Cross-asset class Speed/latency advantage Rapid customization Cross-geography Crossing borders with low-latency Trading in the cloud offers Progress Apama's advanced capabilities to a wider trading community. Through our partnerships, clients can take advantage of hosted, connected, and integrated solutions to accelerate their time to market, minimizing investments in time, space, infrastructure, and integration. And, collocation lowers latency through physical proximity, and further enables trading organizations to cross borders to trade on markets around the world. With a cloud solution, traders can now leverage their own ideas through Apama’s graphical development tools to quickly and easily create, manage, and deploy cross-asset alpha and execution strategies.

27 CQG and Progress partnership
This illustrates a hosted offering. Charts, quotes and graphs (CQG) provides a hosted market data and trading signals platform. With AutoEx, these trading signals can automatically trigger an execution algo. Hosted means that it can be paid for out of an operational, rather than a cap-ex budget. That it is simple for a client to adopt. Appeals to mid-tier firms that don’t necessarily have IT expertise to build something themselves.

28 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 Middleware DBMS Point Systems Integration Other…

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

30 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 Scenario modelling Smart Block Analytics Middleware DBMS Point Systems Integration Other…

31 Building and Deploying an Apama Application
Customers & partners End-User Dashboards Scenario modelling Smart Block Analytics Middleware Database Point Systems Integration Other…

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 Why would you want to build trading strategies in this way? Because Markets are continually evolving with new opportunities emerging And being able to capitalize on those opportunities not only requires speed of execution, but speed to develop unique strategies. If everyone has the same algorithm – if your trading system is a black box and you cannot see or change what’s inside - then the competitive advantage is reduced Need to develop new strategies first, which means, to 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 Semejnyj Recept

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

34 FSA Surveillance Case Study

35 All Participants Are Interested In Surveillance and Monitoring
Orders (proprietary and client) Broker Trading Venue (Exchange, ECN etc.) and Monitoring Surveillance There are 3 audiences to potentially adopt this type of solution - Regulators - Trading Venues - And Brokers And in addition – the brokers clients are interested to know that they are being protected in a fair and efficient market; Or, they need to know to keep their intentions clean, because they are being watched Regulator 35

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 Market Monitoring Liquidity and spread monitoring, associated market halts, price /volume spikes, abnormal concentrations Operational Monitoring Throughput, competitiveness, movements from normal behaviour Management & Control Both sides of book (efficient internal matching), rogue algorithms, best execution, internal controls and limits 36

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 Dewar Director of Markets Division, FSA May 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 Usage Model at FSA Integrated RAD environment
Market conduct teams and “Super users” Deep historical analysis Create and evolve alert rules Develop dashboards IT and data analysts Develop market connectivity Monitor alerts Monitor companies Alert analysts & company monitoring Manage alerts Fully integrated, rapid development environment

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

41 Example: Fraud Detection The UK Financial Services Authority

42 Conclusions

43 An event driven market surveillance architecture
Market conduct teams, alert analysts, etc. Market data Complex Event Processing Rule definition and refinement Replay and root-cause analysis Abuse detection scenarios Social Networking Historical abuse analysis


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