Climbing mount complexity, one event at a time

CLIMBING MOUNT
COMPLEXITY, ONE
EVENT AT A TIME

David VINCENT – CTO

© 2009 smartTrade Inc.

Presentation Agenda

1. Liquidity Management Playground

2. Liquidity Management Foundations

3. Implementation challenges

4. QuickFix/J and SmartTrade LMS

5. ESPER and SmartTrade LMS

© 2009 smartTrade Inc

Liquidity Management Play Ground


Flows in presence


Various objectives

• Best execution

• Best services to clients ( market impact, orders management )

• Algo

• Market

• Venues

• Cross-Asset


Business and Economical Dimension

• Business

• Pricing / Rules / Decision making

• Automated Market-Making ( active / passive orders ) to clients and
venues

• Creating Dark Pools

• Pre-matching, Best Exec (RegNMS, MIFID,...)

• Access to Liquidity / Connectivity

• High Velocity flows

• Economical

• Market impact

• Execution and clearing fees control

• More Value/Less Risk/ More Flows


Functional Dimension

• Supporting various market discovery modes

• Streaming

• Request For Stream

• Supporting various trading modes

• Orders

• RFQ

• Multi Leg patterns

• Basis trading

• Synthetic products


Technical Dimension

• Moving targets – always

• Complex interacting processes

• Old legacy systems part of the game

• Low latency

• Scalability

• High Availability – zero error acceptance

• Integration – openness, flexibility, interoperability, acceptability by
IT teams


Liquidity Management Foundations


Foundation of Liquidity Management

Liquidity Aggregator Liquidity Crosser Liquidity Orchestrator Liquidity Connect

All components can be used individually, or combined,
to help solve entire Liquidity Management needs.


The Internal Market Paradigm

• Virtualization of all trading flows at the enterprise level: complete
internal market state model

• Full lifecycle management of all inbound and outbound instructions
and orders

• Complex distribution and liquidity management strategies
(orders types, price aggregation, smart routing, internal crossing,
internalization, multi-leg strategies, price-tiering)

• Easy-to-add new products and automated rules

• Seamless integration to current & existing infrastructures for a short
time-to-market implementation (including transport)

• Connectivity: Liquidity Connect


Generic Liquidity Management System


Implementation challenges


Key Technology Factors

• Common Data Model
• Explicit messages & structures of data shared across the platform are defined
in a domain specific XML file data model
• Extensive Cross-platform code generation ( Java, .NET, C++ )
• Extensibility – static and dynamic data model fields & structures
• Open Messaging
• Decouples messaging middleware dependencies from internal architecture
• Allows several messaging transports to connect to the same container
• Leveraging client’s existing deployments
• Dependencies Injection
• Offers a easy way to create assemblies of components; allows very flexible
configurations
• Deployment Supervision
• Mix between Agent based approach (non-intrusive) & JMX
• Component configuration ; Supervision & Lifecycle Management
• Web based application allowing monitoring of:
- Hardware state ( CPU, Processes, Disks, Memory )
- Application state ( Threads, Heap )
- Custom Metrics via JMX plug-ins framework

Development Approach

• SCRUM Methodology
• Agile approach to software development & program management,
enabling fast and iterative deliveries to clients.
• A key principle of Scrum is its recognition that during a project the
customers can change their minds about what they want and need,
so its gives valuable flexibility to these unpredicted challenges.

• XP (Extreme Programming)
• A disciplined approach to software development.
• XP empowers developers to confidently respond to changing
customer requirements, even late in the life cycle.
• It stresses customer satisfaction. So projects will experience greater
success and developer productivity.

• High Involvement in Open Source World
• Open Source development philosophy internally
• Contributor in multiple OpenSource projects
• Project lead of QuickFixJ OpenSource Java FIX engine


QuickFix/J : a pure Java FIX Engine


What is FIX ?

• Financial Information eXchange

• Created in 1992.

• Free, open technical specification for electronic communication
of trade-related messages.

• Maintained by FIX Protocol Ltd.
• Volunteer team

• In wide use (exchanges, banks, …)

• Global adoption


FIX protocol layers

• Session Protocol
• Message format, header, footer
• Logon/Logoff
• Heartbeats
• Sequence number synchronization

• Application Protocol
• Message formats and semantics
• Order submittal and execution
• Quoting
• Market data
• Other (email, news, …)

• Representation
• ASCII Tag/Value
• FIXML (XML, Tag/Value envelope)
• Example Message:
• 8=FIX.4.19=6135=A49=INVMGR56=BRKR34=152=20000426-
12:05:0698=0108=3010=157


What is a FIX Engine ?

• Session protocol implementation
• Messages and behavior

• Supports application messages
• Behavior is application-specific

• Eases trading counterparty connectivity

• “The nice thing about standards…”
• Many variations


QuickFix/J Open Source Project
• Spin off of the QuickFIX C++ project
• Native C++
• Java via JNI

• QuickFix/J motivators
• Interesting domain
• Integration/deployment issues w/JNI
• Free FIX engine for Java clients
• No existing OSS Java FIX engines
• Unhappy with existing vendors ( Price, Support )
• Unhappy with “homebrew” engines

• History
• Discussed on QF lists and wiki
• November 2004 : QFJ work started in by Steve BATE
• Help from Smart Trade on the port
• Mid-July 2005 : 1.0.0 beta released
• December 2008 : Smart Trade Technologies takes over the project lead
• February 2009 : 1.4 released

• http://www.quickfixj.org

QuickFix/J Elements

• FIX metadata (XML)
• Parser, Pretty Printing, Validation

• Generation of Message-related code
• Uses Java, XSLT, and XML metadata
• Java message and field definitions (FIX 4.0 – 5.0, Serializable )
• Message Cracker (type safe dispatcher)

• Application
• Interface implemented by users
• Several callbacks (Session creation, Logon/Logoff, Message sent/recvd).

• Session
• Implements FIX protocol
• Data dictionary
• Message Factory
• Message Store (file, JDBC, BDB)
• Session Log (file, JDBC, console)
• Settings (file)


QuickFix/J Elements

• Connection management
• Socket Initiator (usually buy side)
• Socket Acceptor (usually sell side)
• Single or multithreaded
• NIO using MINA
• Alternate implementations possible

• Acceptance Testing tools
• declarative test definitions derived from FIX spec,
• JUnit based

• Unit testing tools
• fills coverage gaps in acceptance testing
• JUnit based

• Cruise Control
• Continous integration support
• Builds product and executes tests

• Example applications and code samples


QuickFix/J Benefits
• Covers the full FIX connectivity scope
• Supports FIX versions 4.0 - 4.4, 5.0/FIXT1.1
• Scheduling of session connections
• Failover and High Availability

• Open Source
• Free! It costs nothing and has a very liberal open source license.
• Full source code available (also at no cost).

• Native Java
• Runs on any hardware and operating system supported by 1.4+ Java SE or
compatible VM.
• Supports embedded SSL with Java 5+
• Provides standard JMX MBeans for FIX engine management
• Easy to embed in existing Java applications

• Highly Customizable
• Support for protocol customizations (new messages, fields, constraints).
• Session state storage plugins: JDBC, File, SleepyCat/JE, In memory
• Logging plugins: JDBC, File, SFL4J (supports JDK1.4 logging, Log4J, Commons
Logging), Console, Composite


QuickFix/J inside the Smart
Trade LMS


Liquidity Connect Architecture

• Connecting N world to P world

• Enterprise Integration Patterns implementation
• Not yet CAML ☺
• Router / Translator / Interceptor Chains

• Connector
• Abstract the API to connect to a specific world
• Manages life cycle of the connection ( ready, down, stale.. )
• Receives and transmits message to an interceptor chain

• Interceptor chain
• Unidirectional
• Pass messages along different components
• Connector is always at the start and the end of a chain
• One to many relationship : 1 connector -> N connector

• Bridge
• Assembly of connectors and interceptor chains
• Spring based definition


Liquidity Connect Architecture
• A –B Bridge

• A – BC Bridge


STTP Connector

• Connecting Smart Trade LMS world to P world

• Using the Smart Trade STConnect API

• Normalizing data into the Smart Trade canonical model
• Translator interceptors


QuickFIX/J Connector

• Connecting Smart Trade LMS world to FIX world

• Using QuickFix/J Fix engine and libraries

• Normalizing data into the FIX canonical model
• Translator interceptors to manage versions
• Support Custom fields


QuickFix/J and ST LMS


ESPER CEP


Esper Open Source Project

• Mission
• CEP a natural and easy task of your application
• Open platform to create competitive differentiators and maximize
reuse

• ...and therefore
• Lightweight and embeddable into any Java technology process
• Open source
• Low latency and high throughput

• Project background
• 3 years of development, 100% Java
• NEsper for .NET/C#, same semantics

• Dual licensing Enterprise/OEM/Open Source model
• Open source for open source use (GPL license)
• Commercial for redistribution by ISVs
• Services & support (dev, 8x5, 24x7)

• http://esper.codehaus.org


Esper Products Offering

• ESPER
• ESP/CEP with expressive Event Processing Language
• Continuous queries, aggregation, joins, causality and missing events,
joins to historical data, output flow control...
• Standalone or Embedded

• ESPER HA
• Out-of-heap storage, complete resiliency to disk, or local in-memory
caching
• Clustering and hot backup capabilities for event and streams state

• ESPER ENTERPRISE EDITION
• Esper Studio: Operational console for runtime management, real-
time event stream views and ad-hoc queries
• EsperJMX: Runtime management and monitoring over standard JMX
connectors
• EsperJDBC: JDBC compliant client and server endpoints for
interoperability

• NESPER
• ESPER for C#/.NET


Esper Key Benefits

• ESPER Integrated ESP and CEP and expressive EPL language

• Rapid development, test and reuse of existing code
• Java libs, other open source fwk, Eclipse IDE etc.

• Performant & lightweight
• Server-less if needed
• Possible use of Real-Time JVMs
• Multi-platform (Java / .Net, 32/64 bits, multiple OS support)

• Ease of integration in existing platforms or standards
• Spring Framework
• Enterprise Integration Technologies

• Management console, runtime management, standard based
(JMX)


ESPER inside the Smart Trade
LMS


Why integrating with ESPER CEP ?

• CEP are NOT Liquidity Management Systems…… They are
complementary

• Smart Trade
• “Smart Trade’s customers will be able to rely on a domain-specific
CEP for their SOR, crossing and aggregation strategies on top of
already existing programmable rules that our liquidity management
system produces and implements to ensure best execution for their
firm and clients. This clearly proves that CEP and liquidity
management are complementary technologies.”
David VINCENT – co-founder and CTO

• Esper Tech
• "The EsperTech and SmartTrade agreement combines and extends
our open-source roots to maximize fit for purpose and confidence
while minimizing costs for Reg NMS and MiFID best-execution
deployments. This once again confirms how our enterprise-ready and
open-source CEP makes sense in today’s world across all industries.”
Thomas BERNHARDT, founder and CEO

• OEM Agreement between Smart Trade Technologies and Esper
Tech signed in February 2009


ESPER Plugin
• Domain specific integration
• Creation of complex stream on the fly
• Manipulating a Domain Specific model

• Wrapping the ESPER 3.2 runtime into STContainers
• Rely on EPServiceProvider, EPStatement and the other friends
• Using Spring
• Extending the ESPER engine with specific behaviour ( ex : sorting )

• Wrapping the Smart Trade canonical model with Event
• Ex : MarketDataSnapshot => MarketDataSnapshotEvent
• Ex : NewOrderSingle => NewOrderSingleEvent
• Using model extensibility to add EPL return statement fields


Liquidity Aggregator’s ESPER Plugin

• Integration with the STConnect API
• Allows to interact remotely with the ESPER Engine
• Creating and consuming EPL queries from external process
• Chosing feed sources

• “Plumbing” Liquidity sources events to the ESPER engine
• Source of data
• Distribution End point


Examples of ST / EPL use
• Average Bid in the last 30 seconds window

select avg(price.value) as PriceAverage from
MarketDataSnapshotEvent(MDReqID.value=‘XXXX')[bidEntries].win:time(30 sec)

• Instant BestBid / BestOffer spread

select bestAggregatedOffer.price.value-bestAggregatedBid.price.value as Spread from
MarketDataSnapshotEvent(MDReqID.value=‘XXXX')

• Average BestBid / BestOffer spread in the last 30 seconds window

select avg(bestAggregatedOffer.price.value-bestAggregatedBid.price.value) as Spread from
MarketDataSnapshotEvent(MDReqID.value=‘XXXX').win:time(30 sec)

• VWAP
select average as VWAP from
MarketDataSnapshotEvent(MDReqID.value=‘XXXX')[bidEntries].win:stat:weighted_avg(price.value,
quantity.value)


Liquidity Orchestrator’s ESPER Plugin

• Generating complex events to be managed by the rules
• From aggregated or raw market data
• From order life cycle events ( Fills, Cancelation, unsollicitated messages )
• From external functional events ( Risk exposure,..) to technical events (
Latency, ..)

• Separating the events monitoring logic from the actions
• A clean Action / Reaction model
• A way to layer the rules coding


ESPER and ST LMS


Questions


Please contact

Europe United Kingdom
Tel : + 33 1 44 50 19 19 Tel.: +44 (0)20 3326 0522
Fax: + 33 4 42 97 62 52 Fax: +44 (0)20 7491 7976
hgozlan@smart-trade.net njames@smart-trade.net

North America
Tel.: +1 212 618 6383
Fax: +1 212 618 6309
mbailey@smart-trade.net

www.smart-trade.net

Climbing mount complexity, one event at a time

Recommended

Recommended

More Related Content

Similar to Climbing mount complexity, one event at a time

Similar to Climbing mount complexity, one event at a time (20)

More from Skills Matter

More from Skills Matter (20)

Recently uploaded

Recently uploaded (20)

Climbing mount complexity, one event at a time