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