Cross-Asset, Cross-Border Algorithmic Trading

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Cross-Asset, Cross-Border

Algorithmic Trading

Apama Track

Dan Hubscher, Principal Product Marketing Manager, Progress Apama Dan Hubscher, Principal Product Marketing Manager, Progress Apama

Progress Exchange Brasil 2009 Progress Exchange Brasil 2009

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Apama Background

Progress Software (NASDAQ: PRGS)

Apama Complex Event Processing

Platform

Apama Complex Event Processing

Platform

Focus on Capital Markets

• Algorithmic Trading _Other

• Algorithmic Trading • Risk Management • Market Making • Best Execution EQ FI Other • Best Execution

Multiple Asset Classes

120+

Global Customers Including

F&O FX

120+

Global Customers Including

Regulators, Exchanges, Banks

and Buy Side institutions

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The Capital Markets

Trading Community Today

Global rise of the alternative venues

• Market fragmentation

• Price/speed competition

• Regulatory drivers – RegNMS, MiFID, etc.

Volume & volatility

Technology arms race

• Increasing market data

• The need for speed

Automated trading evolution

Broker algorithms Proprietary algorithms

Smart Order Routing

News-driven Algorithms Broker algorithms Proprietary algorithms

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Cross-Asset Algorithmic Trading

– What & Why

Automated trading

When to trade

• Objective: seek alpha

How to trade

• Objective: best execution

Multi-Asset Trading Multi-Asset Trading

• Single platform

• Multiple asset classes

• Independent strategies Cross-Asset Trading

• Single platform

• Multi-asset strategies

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Complex Event Processing

Static Data Processing:

“How many orders were placed for a stock?” placed for a stock?”

1 2 3 4 5 6 7 8 9

time

1 2 3 4 5 6 7 8 9

Complex Event Processing:

“When 3 orders are placed for the same stock “When 3 orders are placed for the same stock within any 5 second window, stop any further

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4 Frontiers of

Algorithmic Trading Competition

Rapid customization customization Algorithmic Trading Speed/latency advantage

Cross-geography Trading advantage

geography

Cross-asset class

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Algorithmic Trading Rule – Equities Example

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% My Basket moves up by 0.5% ALL WITHIN

any 2 minute time period

THEN My Basket THEN BUY MSFT SELL HPQ MSFT Moving Average

•

multiple data streams

•

temporal sequencing

NASDAQ

NYSE

•

complex event sequences

•

real-time constraints

•

automated actions

•

temporal sequencing

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Apama Experience In Foreign Exchange

Key FX Use Cases

Aggregation Pricing

Algorithmic Trading Auto-Hedging &

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Algorithmic Trading Rule

– Foreign Exchange Example

!"# !" $$ % & $$ !" % & !"' !" !" % & !" # $ " !" ( ) *+ , + !"% !" !" & ' + ' & ( !" -% .-( ) *+ , + ' & ( *. $' !"

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Use Cases - Algorithmic Trading in FX

Proprietary trading

• Monitor for opportunities

• Statistical arbitrage over time

• Statistical arbitrage between currencies

Hedge or order implementation

• Minimize market impact

• Manage risk exposure

( ) *+ , !" -% .-( ) *+ , !"

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Fixed Income Custom “Rules-based”

Mean Reversion Algorithm

WHEN 10yr:5yr VWAP Spread < Lower Band

THEN

BUY 10yr:5yr VWAP Spread

WHEN

10yr:5yr VWAP Spread > Profit Line OR

10yr:5yr VWAP Spread < Stop Line

THEN THEN SELL Position Spread Mean Lower Band Lower Band

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Real-time Algorithmic Pricing – Fixed Income

MTS Rules-based Algorithms MTS Inter-dealer market BrokerTec Aggregated View Algorithms BT eS Trader parameters Real-time Pricing eSpeed View factors Skewing factors Real-time Pricing Engine Client Tiering positions Target positions In-house bond-pricing analytics Market Client history Inventory analytics interest rates Market factors, e.g. interest rates Client history

RFQ

Traditional Bond Pricing Engine (?)

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Futures – Spread Trading Example

Apama Spreader hosted by FFastFill

Hosted, integrated solution

Manual and automated spread trading

Multi-leg, multi instrument, multi-exchange models

Links to external modeling tools, charting packages and news feeds Managed legging risk

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Futures – Automated Execution Example

Apama AutoEx for CQG Integrated Client

Hosted, integrated solution

Apama automatic order execution

Apama tools to adjust execution strategies on the fly

CQG network of collocated low-latency Hosted Exchange Gateways Comprehensive end-to-end performance from signal generation to Comprehensive end-to-end performance from signal generation to execution

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Commodities: PTRM for Energy Markets

Programmatic Trading and Risk Management

Programmatic Trading

• Limit orders / Guard algorithms

• Spreads (statistical arbitrage)

- Calendar - crack - location - spark/dark • Smart Order Routing

• Automation loss of control??

Real-time risk assessment

• Limit management “Risk Firewall”

• Stop-loss & Algo “Auto-hedging”

• “Smart Risk” for trade performance

• “Concentration Risk Heat Map”

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Commodities: PTRM for Energy Markets

Asset Optimization via Asset-backed Trading

Internal Market Crossing

• Asset topology modelling for integrated utilities

• Asset-backed trading across the value chain

• Supply-demand matching

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Modeling Trading Strategies

Event Modeler Monitor Spread Orders Placed Orders Filled Orders Timed Out

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Real-time, Event-based

Platform for Building Applications

Business & IT Tools - Apama Workbench

Graphical Development

Dashboard Builder Code-based Development Graphical Development _{Event Modeler} _{Alpha-seeking & execution rules:} Equities Foreign Exchange Fixed Income Fixed Income Futures Commodities Cross-asset ...and more… Inputs Market data ...and more… Actions/Output Orders Market data Orders Any event Orders Derived data Dashboard interaction

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Cross-Asset Statistical Arbitrage

CEP easily enables cross-asset capabilities in the same platform

• Opening up a range of advanced opportunities

Algorithmic Trader BM&F Cross-Asset StatArb Algorithm Engine Trader Customized rules Bovespa Algorithm

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Algorithmic Trading Rule

- Cross-Asset Statistical Arbitrage Example

When there is a discrepancy between the actual and expected delta one-to-one price of cash and future of a US Treasury delta one-to-one price of cash and future of a US Treasury

Then automatically buy one and sell the other with the best price available across eSpeed and BrokerTec

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Cross-Asset Auto-Hedging

Many firms are taking positions in derivatives to hedge positions • US Treasuries against CBOT futures

• EuroGovvies against Eurex futures

• Equities against futures

Algorithms can automatically re-hedge these positions as the underlying Algorithms can automatically re-hedge these positions as the underlying factors cross specified thresholds

eSpeed Algorithmic BrokerTec eSpeed Auto-hedging Algorithmic Engine Trader Customized rules CBOT Auto-hedging Algorithm Eurex

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Cross-Asset Algorithmic Trading

Sample Customer Projects

Rapid customization

Options against futures

Cash treasuries against treasury futures

Algorithmic Trading Speed/latency advantage Cross-geography

Cash treasuries against treasury futures FX spot against FX futures

Cross-asset class

Cross-border listed equities with a spot FX leg

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4 Frontiers of

Algorithmic Trading Competition

Rapid customization customization Algorithmic Trading Speed/latency advantage

Cross-geography Trading advantage

geography

Cross-asset class

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Apama Connectivity

Broad range of proven adapters

• Market data, liquidity venues, bank portals

• Continuing expanding list

Adapter framework offers cross-asset support

• Low latency normalization of disparate formats

Integration Adapter Framework

Adapter Adapter

Adapter

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Apama Connectivity

Market Data Reuters Activ Financial

Dow Jones Elementized News Feed KOSPI (Korean Composite Stock Price Index)

Nexa Tickstream

Direct Foreign Exchange Markets EBS Spot Ai

Hotspot FX Currenex FXall Accelor Lava FX – Spot FX

Direct Fixed Income Markets ICAP Brokertec

BGC (eSpeed)

Tick Databases Nexa Tickstream

Wombat

Lime Brokerage (Citrius)

Equities Markets

Market Data

Market Data sources (listed above)

Lava FX – Spot FX Reuters Dealing 3000 BGC

Direct Futures & Options Markets Euronext.Liffe

Intercontinental Exchange (ICE)

Tick Databases

Vhayu/Reuters Tick Capture Engine KX Systems kdb+

EMS/OMS/FIX Gateways Transact Tools

Aegis Gateway (Athena Trader) Market Data sources (listed above)

Bovespa

Other direct connectivity 2

Order Execution

FIX 4.0 – 4.4 Bovespa

Intercontinental Exchange (ICE)

Chicago Mercantile Exchange (CME/NYMEX)

Eurex ELX BM&F

Direct Bank Connectivity

Aegis Gateway (Athena Trader) Ulbridge (Odisys)

GL Trade Cameron

Trading Technologies (TT) Pro Nexa Fastpath

IRESS CQG Bovespa

EMS/OMS/FIX Gateways (listed right) Direct Bank/Broker Connectivity (listed below)

Other direct connectivity 3

Analytics MATLAB

Direct Bank Connectivity Barclays

Deutsche Bank Autobahn UBS Goldman Sachs ITG Penson Brokerbox CQG FlexTrade Fidessa Infrastructure Adapters JMS JDBC MATLAB

Quantlib (select functions)

Intel Math Library (select functions) CQG Penson Brokerbox Lime Brokerage Morgan Stanely JDBC ODBC Sonic Tibco Rendezvous Tibco Talarian Sonic

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Markets Served

London Stockholm Amsterdam New York Boston London Chicago West Coast Mexico City Toronto Hong Kong Tokyo Middle East India China Bologna Seoul Amsterdam Eastern Europe & Russia Paris Madrid Hong Kong Singapore India Sao Paolo Sydney

Currently South Africa Melbourne

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Trading in the Cloud

Exchange collocation – enables competition in: • Cross-geography

• Speed/latency

Rapid customization

• Speed/latency

Software-as-a-Service • Quick time to market

Algorithmic Trading Speed/latency advantage Cross-geography

• Quick time to market

• Minimal investment Hosted • Easy access Cross-asset class • Easy access

• Optional connectivity to any other trading venues and market data sources Apama Examples

Apama Examples

• CQG – Automated execution for commodity & FX futures

• BGC – Algorithmic trading for Fixed Income cash & futures

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Real-time, Event-driven Model

Event Modeler

Any business update is an event Any business update is an event Asset neutral Monitor Risk Market agnostic Broad connectivity Orders Placed Broad connectivity

Leverage trader’s market knowledge

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Conclusions

Attract new business

• Compete across borders and asset classes Seek alpha, best execution, manage risk

• Customize leveraging market knowledge Markets are continually evolving

• First Mover Advantage Customization is now KING

• Create intellectual property for competitive differentiation

• Custom “rules-based” trading is critical

Trading firms look to Apama for a platform

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THANK YOU

Q&A SESSION CONTACT US

Dan Hubscher

Principal Product Marketing Manager, Progress Apama Progress Apama E-mail: [email protected] E-mail: [email protected] Web: www.progress.com/apama Blog: http://apama.typepad.com/ Blog: http://apama.typepad.com/