a-team group: super feed performance and efficiency

8/9/2019 A-Team Group: Super Feed Performance and Efficiency

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A f a

A-Ta Goup

Researched and written by:

PerformAnce And efficiency:How a Managed Services Approach

Can Ease Your Market Data HeadacheOctober 2009


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PErforMAnCE AnD EffiCiEnCY

itoduto

Market inrastructure is evolving at a pace that even the most technology-savvy nancial institutionsnd challenging. New execution venues are popping up everywhere ragmenting liquidity andcreating cross-dependencies between primary and derivative marketplaces. The move to astmarkets and trading automation is cutting response times and increasing data volumes. Marketshave shown a 70% increase in volume over the last year alone (see chart below).

Update latencies o less than 10microseconds are now possible even commonplace. Market datarates in excess o 20 billion updatemessages per day are on the nearhorizon. With a universe o more

than 250 real-time markets tradingin excess o 40 million instrumentsand derivatives, developing anddelivering a market data systemor todays markets is, at best,problematic.

Never beore have nancial institutions aced a more pressing need or fexible data acquisitionsolutions. And the requirement applies across the board: From the largest tier 1, bulge bracketrms, to the pluckiest speciality execution rm, rms o all shapes and sizes are seeing themarket data management requirement leap to the top o their priority lists.

And the timing couldnt be worse.

An industry brieing prepAred byA-TEAM GroUP or nYSE TECHnoloGiES 2

OPRA & Consolidated Equities 5 Second Peak Rates showing three-old

increase over past two years and 70% over the last year.

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The need to lower latency is at an all-time high. More than three-quarters o organizationsconcerned with market connectivity are driven to remove undue latency while lowering totalcost o ownership (TCO) and removing complexity rom their market data inrastructure (seebar graph).

Current market conditionsmean ewer sta areavailable or deployingcrucial systems. Marketdata acquisition hasalways involved anarduous orchestration opeople, technology, legal,administration and timing.The changing demands

o internal clients andongoing regulatorychange are makingmatters more urgent.

The breadth o market coverage necessary, meanwhile, is adding to the overall complexitywhile the business demands more inormation in a timely ashion, and the data is being put tomore uses. Nearly every trading house is contending with complex requirements or algorithmictrading and market data redistribution, as well as statistical arbitrage, portolio evaluation, riskavoidance, or data collection or compliance and verication.

Many rms are nding their existing solutions are not up to the challenge and cannot be

modied cost eectively or within a reasonable timerame. Most have observed that within ave year window they will need to re-architect their data centres. More and more are ndingthat a resh solution is the only way to meet latency objectives eciently.

Microseconds o delay can adversely aect trading decisions, and the latency requirementrom the business side places huge pressures on system perormance. But establishing andmaintaining network connections to multiple markets alone can rack up signicant costs.Bandwidth requirements reach into the multiple hundred megabit range or major markets.Update rates are approaching two million messages per second. All o which costs in terms odirect network inrastructure, computing power, and the human resource required to support it.

The total cost o ownership (TCO) o a locally deployed ticker plant, and the market datainrastructure to which it delivers data, is a complicated calculation. It depends heavily on anorganizations size and existing inrastructure, data and perormance requirements, and physicallocation. TCO also includes lost opportunity through lengthy time-to-market, the ully burdenedcost o sta necessary to develop, integrate, test, and deploy new solutions and enhancementsto the ticker plant, in addition to hardware maintenance and replacement strategies.

A growing rm, where time to market is critical, will want to invest in inrastructure thatcan easily expand and adapt to fuid conditions. Larger organizations, with market datainrastructure already in place, are scrutinizing the rising costs or development andmaintenance o existing systems. Many nd themselves with higher-than-optimal latency withno ability to improve the perormance o internal systems; in-house solutions that have grownwith the company haphazardly are oten overly complex and exhibit reliability issues.

For organizations large or small, conservative or aggressive, traditional or agile, an outsourced,managed or hosted solution may be worth considering or reasons o perormance, cost controland operational eciency. A hosted third-party ticker plant, with interaces to all major venues,can oer similar levels o perormance to an in-house platorm at a compelling price point.



Graph showing overall initiatives and individual priority. E.g. 62%

indicated reducing latency is critical while 38% selected it as

their most critical (source: NYSE Technologies).


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This white paper provides an analysis o the challenges acing market data technologistseverywhere. It looks at the platorm requirement, outlines total cost o ownershipconsiderations, and discusses the relative merits o a managed or hosted service approachlike NYSE Technologies SuperFeedTM.

evaluatg th StuatoMany considerations actor into the choice o market data inrastructure, and how to choosethe mix o outsourced solution, in-house development, proximity hosting and direct marketaccess. Over time, industry preerences have swung rom one extreme to another, based ontechnology limitations, economic conditions, and the capabilities and attitudes o staand management.

In todays economic environment, many market participants are rantically trying to identiy

their strengths and capitalize on them. Improvements in technology are removing capacitylimitations, making the optimum solution a unction o an organizations commitment andappetite or tackling new challenges.

More than ever beore, market data technologists ace real inrastructure choices permittingmore sophisticated collection, processing, and distribution o their data. But that doesntnecessarily make their task any easier.

Large rms engaging in a broad range o activities may nd they have a wide variety o needsor the same core data. Some require high throughput o data rom primary markets perhapsor statistical analyses, real-time risk calculation or algorithmic trading. Other departments mayneed a dierent cross-section o inormation with a more relaxed latency requirement.

Traditionally, high-perormance solutions or market data have oten entailed costly custom-built data acquisition sotware to satisy throughput and latency proles. This approachtypically involves signicant investment that only the largest rms can bear. But, the vastmajority o rms are seeking to minimize the hassle and burden on accountable resources anin-house solution can entail. The commitment in capital costs, sta and other resources toown and manage a low-latency, high perormance collection and processing system isnon-trivial.

Direct market access (DMA) involves streaming data with a minimal touch philosophy thatensures time-sensitive delivery to a rms trading engines. Larger rms consider this an axiomo competitiveness and utilizeDMA in operations centres

located physically near theirprimary markets. Smallerrms, hoping to remainnimble but competitive,may be less willing or able,however, to invest the timeand inrastructure to take ulladvantage o DMA ontheir own.

With market data quotevolumes on the rise, tackling

DMA or all relevant sourcesis a challengemost arenot readyto address.



Shows Fidessa Fragmentation Index (FFI) average or major indices. An index over 2

indicates a stock no longer has a primary venue. (Source: Fidessa Fragmentation Index

(http://ragmentation.fdessa.com)). Note: Figures are compiled rom order book trades

only. Totals only include stocks contained within the major indices.


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Recent statistics show, especially within Europe, that ragmentation has led to the necessity toconnect to our or more markets or each major group o instruments (see table and graph).

In-house DMA systems require allocated space and budget or data centres in multiplelocations. With this come power and capacity considerations, with tick boxes or uture growth,network and physical security, and connectivity to markets o interest.

Research estimates the total lietime cost o rack equipment at about $150,000 per unit, orabout $4,000 a month in a data centre. With rms looking to cut costs wherever they can, datacentre space must be utilised eectively. Firms must consistently right-size their data centres an ongoing expensive and rustrating experience best let to specialists.

Notwithstanding whether a truly ultra-low-latency requirement exists, any consumer o marketdata aces a signicant contract administration task. Direct and consolidated data eedsrequire contracts with source market venues, as well as any redistributors. Consumers needto satisy usage tracking, entitlements and reporting clauses used by suppliers or pricing. Forrms where a signicant number o market eeds are brought in-house, this can be a time-consuming, resource-intensive burden.

More broadly, business continuity planning is a critical consideration o any operationallyhealthy organization and ault tolerance is a mainstay element o any modern marketdata operation. Data systems with fexible architectures can provide local redundancy orgeographically diverse hot backup scenarios. But all is or naught i secondary systems arenot compatible with primary systems on which the organization bases its operations.

Overall, a daunting array o variables actor into a orthright comparison o an organizationscurrent capabilities against its needs. For this reason, some rms opt to seek out a hybrid,or even ully external, solution that gives them the perormance prole they need at a capitalexpenditure and maintenance burden they can aord (see Demonstrable Benets o HostedSolutions sidebar overlea).

Although responsiveness to market conditions is oten the overriding constraint, in-housedevelopment is no longer a oregone conclusion especially with current ocus on spend oranything that doesnt turn a direct prot. Adding perormance proles and increased demandon datasets only complicates the analysis.

PrimaryAlternative

Venues

Index Venue Share Chi-X TurquoiseNASDAQ

OMX BATS Others

AEX Amsterdam 69.94% 15.78% 4.64% 0.70% 4.46% 4.33%

BEL 20 Brussels 60.79% 14.04% 3.10% 0.51% 3.33% 17.98%

CAC 40 Paris 67.21% 15.31% 5.25% 1.05% 4.20% 6.34%

DAX Xetra 74.68% 17.00% 3.72% 0.49% 3.12% 0.03%

FTSE 100 London 62.74% 21.84% 6.37% 1.21% 7.82%

FTSE 250 London 71.39% 18.13% 5.71% 0.35% 4.41%

IBEX 35 Madrid 99.36% 0.50% 0.05% 0.04%

FTSE MIB Milan 88.84% 6.80% 1.01% 0.08% 3.18% 0.04%

PSI 20 Lisbon 97.74% 0.72% 1.43% 0.04% 0.05%

SMI SWX 79.96% 11.83% 5.58% 0.75% 1.87%

OMX C20 Copenhagen 87.31% 10.78% 1.32% 0.24% 0.32% 0.01%

OMX H25 Helsinki 79.02% 12.34% 5.31% 0.74% 0.85% 1.55%

OMX S30 Stockholm 78.60% 13.68% 3.83% 0.43% 1.14% 2.23%

OSLO OBX Oslo 93.42% 3.33% 0.61% 0.04% 0.19% 2.41%

Liquidity ragmentation or major indices in Europe showing that 6

or more venues should be hit to fll orders. (source: Fidessa).


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establshg a r o

copasoSo how does a market data operations proessional make the rightdecision about meeting this considerable and complex set o currentand uture requirements?

Its important to consider the starting point beore making decisionsabout what direction to take. Its highly likely that anyone currentlyexamining how to optimize their rms market data inrastructure isntconsidering a green-eld development: every rm today has someorm o market data inrastructure in place.

That points to two choices o project imperative: either you arereplacing an existing platorm thats costly or cumbersome tomaintain; or you are seeking to upgrade to something aster and moreecient. In either case, a clean break is probably a more direct wayto achieve project goals.

Entrenched inrastructure may dene an organizations currentcapabilities but it doesnt necessarily satisy the wants and needso the entire enterprise. Whats required is an approach thatencompasses the rms requirements in a timely and aordablemanner while remaining agile or uture demands.

Total cost o ownership (TCO) or internal platorms is dicult tocalculate within an organization due to overlapping responsibilitiesand conusing priorities. True allocation o costs is necessary toperorm a air comparison a near impossibility or any organizationthat has its own development and operations sta because manyreal costs are hidden in shared resources or covered by corporateoverhead.

But how does TCO actor into the decision? And what are the bestpractices or uture-proong an organization?

An internally constructed and managed market data platorm canyield explicit benets in terms o fexibility and time to market or

new nancial instruments, markets and data sets. But internaleorts may be hampered by any number o uncontrollable actors:contravening development team priorities, resource allocation delaysand questions about the suitability or purpose o the end-result, tomention just a ew.

As such, or some market players, there are compelling arguments oroutsourcing the entire data acquisition suite and backbone platormto a capable third party, even beore the potential perormancebenets and management streamlining.

Latency and control are the two most requently voiced objections

to arming out market data acquisition and processing, even i theunction is not a core capability o most market data consumers.

But those objections can be short-circuited by a third-party,

Demonstrable Benefts o

Hosted Solutions

A mid-sized, New York basedbuy side rm had a very commonproblem a legacy inrastructurebuilt over time that requiredexcessive resources to manage,maintain, and expand. The goal:reduce costs and simpliy theacquisition o market data.

Total expense, or direct costs thatcould be identied, was over $2

million annually to acquire basicmarket data relating to equities,utures, and options. Customapplications were interaced tovendor supplied sotware orconsolidated and direct eedsusing ticker plants on two sites.

And this cost doesnt includethe sta involved in keeping thedepartment running a marketdata architect and manager, twoapplication engineers, two levelone support sta, an applicationdeveloper, a systems administrator,and a network engineer.

By implementing SuperFeedTM,a hosted, managed service romNYSE Technologies, the rm wasable to realize a 40% savings andstill meet the basic requirements:

Over $800,000 o direct costsavingsDirect eeds or minimum latency

on required venuesConsolidated eed or othersourcesConnection to primary hostedand disaster recovery sites

SuperFeedTM integration aordedadditional tangible benets thatcould not be assigned a cost value:

Perormance upgrade romlegacy middleware to latesttechnologyRepurposing o eight sta to core

business unctionsComplementary reduction in datacentre capacity requirements


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managed system that satises immediate requirements while providing a solid base systemrom which to expand.

The arguments or such a hybrid solution are compelling.

Today, an outsourced solution can oer similar perormance levels to and oten better than an in-house ticker plant. When co-located with a rms primary trading and investmentapplications latency concerns are alleviated. And it can be interaced to a proven marketdata platorm within the rms data centres, raising the possibility o use in concert with otherlocally sourced data.

Although TCO is a unction o a specic rm, an outsourced ticker plant rom a single providervirtually removes many hassles, leaving them instead to the supplier. These include datacentre capacity planning, data acquisition and normalization, venue connectivity and contractadministration, physical and network security exposure to multiple connection points, and

capital expenditures or hardware.

By purchasing a completesolution, a rm adds aull suite o capabilitiesover a single, commoditynetwork interace with littleoperational burden. Goneare the rustrations with

power upgrades at data centres, the intricacies o space allocation in a large organization,or the need to deal with the trade-o o replacing hardware with newer, aster units versusadding acility space.

No longer does exposure to multiple, unamiliar and remote network interaces cause concern.No longer must development and operations sta deal with updates and compatibility with allo the venues and data sources critical to the enterprise (see map below).

Whats let is a compelling reduction in resource commitment or any organization: A single,low-latency, high-throughput pipe or all required markets that can be provisioned and usedselectively which simplies so many aspects o market data acquisition and management.

With an outsourced solution,the business has a consistentand accurate view o itscosts or data acquisition

and systems, while providingnormalized data the entireorganization can use.

An outsourced ticker plantcan be used to consolidatehigh-speed data eeds, whileretaining compatibility with theexisting enterprise market dataplatorm. This can help reducetime to market or missioncritical applications by allowing

development sta to ocuson value-added unctionality.Market data acquisition is not and should not be acore strength o any

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Where do you locate and how do you keep up?

Outside primary exchanges there are up to 120 MTFs (69 in London alone),

90 regulated markets, and 60 dark poolsl (source: NYSE Technologies).


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nancial institution. Such data is a core requirement to be sure, but buy- and sell- side rms alikemake money on understanding the data and using it to their advantage not on collecting it.

Deployed in an optimal way,and combined thoughtullywith internal mission-criticalsystems, an outsourced,managed market dataenvironment can begin todeliver on the promises o high-speed delivery and comprehensive coverage, while diminishingthe overhead, in terms o both direct and indirect costs. (See A Case in Point box below).

A Case in Point: Considering Total Cost o OwnershipHave you reviewed the ull scope o the cost o your ticker plant? Use this check list to identiy i you

have reviewed common, oten overlooked, expenses within your market data acquisition system:

Yes No

Latency and Access:

m m Latency, across all sourcesm m Latency rom primary marketsm m Direct market access sotware and provisioningm m Co-location and proximity hosting costs

Lost Opportunity and Product Availability:

m m Time to market or new or modied eaturesm m Control over sotware development resourcesm m

Development, integration, test, deployment resourcesHardware and Maintenance:

m m Capital outlaw or computers, O/S, racksm m Disposal costs or old equipmentm m Administration and maintenance costs or equipmentm m Connectivity costs and lead-time

Complexity and Security:

m m Number o nal mile communications circuitsm m Network security, operations, and maintenance costs

Facilities Management:

m m Wasted money on oversized data centresm m Cubic ootage within your data centre(s) or expansion

m m Electricity and cooling costsm m Facility continuity during power/hardware upgradesm m Capacity planning physical, electricity, computersm m Business continuity and disaster recovery planning

Administration and Auditing:

m m Reporting requirements or each sourcem m Contract ullment or each sourcem m Multiple use costs or each sourcem m Auditing and accounting resources

I you ticked Yes or most o the points then you are considering the range o commercial andstrategic issues necessary to ensure you have a well structured solution which meets your needs.

But thats only the what. Its then onto the how. Your consideration is then between in-houseor outsource, and i you outsource do you buy a solution to run in-house or lease a solution roma ull service provider. An outsourced solution bundles the costs or most expenses in an easilymanaged, single line item.

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SupfdTm o nySe Thologs

From avourable TCO to high data availability, rom outsourced operational resources tosystem redundancy, a hosted, managed service ready to deploy when you are built by atrusted, experienced partner could be how your organization can streamline its market datamanagement processes while optimizing perormance.

Flexible deploymentstrategies and manageablesolutions are theoundations on which NYSETechnologies has builtits Market Data PlatormV5 and the SuperFeedTM

ully managed, hostedticker plant. SuperFeedTMprovides latency proles

consistent with the most demanding perormance requirements, while delivering the breadtho data previously only seen in slower consolidated eeds. Installed in hosting acilitieswith excellent access to major markets, SuperFeedTM is packaged ready or mainstreamapplications.

Top-o-book data is delivered with sub-100 microsecond latency through the SuperFeedTM

plant, and even aster perormance as Market Data Platorm V5 eed handlers are deployed.High throughput is assured with the Secure Financial Transaction Inrastructure (SFTI)network which is architected to provide the astest point to point connections. Coupled withNYSE Technologies global leading data centre and co-location strategy, a range o highperormance solutions are available to meet all needs. Data is acquired or all major inregion venues with sub-millisecond timing and delivered to co-located clients in less than100 microseconds. This timing is obviously extended or continental European venues andout o region exchanges but NYSE Technologies continually assesses the most ecient andlowest latency network routes or acquiring and delivering exchange data.

SuperFeedTM delivers all o the NYSE Euronext markets, as well as other major venues inthe US and Europe through a single SFTI network connection. NYSE Technologies alsoprovides its SuperBook virtual order book aggregation via SuperFeedTM. The simpliedinterace, accessed through the mature MAMA application programming interace (API),provides streamlined procurement and acquisition o market data and related services toyour downstream products.

SuperFeedTM, poweredby NYSE Technologiesultra-low-latency DataFabric middleware, isa consolidated eeddelivering realtime marketdata content within aco-location acility or ultimate connectivity to global markets. The individual eed handlersused within SuperFeedTM are also available within Market Data Platorm V5, permitting avariety o congurations rom ully outsourced to hybrid scenarios integrated with yourinternal market data inrastructure.

For example, SuperFeedTM may be used initially to provide needed sources quickly or as aredundant eed, and then expanded as necessary utilizing the same network pipe.



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Likewise, as new markets are added to the hosted SuperFeedTM, they can be migrated to arms internal platorm when needed or increased data utilization.

Total cost o ownership (TCO) is brought into ocus with SuperFeedTM because marketdata interaces and management costs are brought together. By comparing the eatures oSuperFeedTM against legacy in-house installations, SuperFeedTM can show tremendouscost-benets in just the rst year while enjoying a lightweight management burden inongoing years.

NYSE Technologies can handle the upstream administration or all data delivered viaSuperFeedTM making it the single management interace to administer market data accessthroughout your organization. Whether to a single co-location acility or multiple datacentres or high-perormance computing, the SuperFeedTM consolidated eed is easy tomanage and easy to integrate.

Rapid solutions deployment and agile data acquisition systems underscore the simplicitygained by relying on a proven partner to handle the complex tasks o updating marketdata eeds, handling data centre resources, and conducting ongoing business continuityplanning. High-perormance and low-latency are key drivers in nding the best solutions oran organization committed to success in todays markets. NYSE Technologies SuperFeedTMaddresses these requirements with a cost-eective and direct solution.

SuperFeedTM provides a high-perormance, consolidated ticker plant service with high dataavailability and redundant operations to ease your market data headache.

For more inormation, visit www.nyxdata.com/supereed


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www.s.o/thologs

A business division o NYSE Euronext (NYX), NYSETechnologies is a leader in providing innovativesotware, market data products and data managementapplications, connectivity solutions, exchangetechnology, and transaction solutions or tradingrms, vendors and nancial markets around the world.Oering the most comprehensive suite o best-o-breed commercial technology solutions that alsoinclude advanced messaging platorms, co-locationsystems, ultra low-latency order routing capabilities anda one-o-a-kind hosted networked community, NYSETechnologies products attract and enable the reefow o liquidity or the global marketplace. With ocesacross the U.S., Europe and Asia, NYSE Technologiesadvanced integrated solutions or ully-deployed,hosted, managed or on-demand services has earnedthe trust to power the trading operations o hundreds oglobal nancial institutions and exchanges.

For additional inormation visit:www.nyse.com/technologies

Copyright 2009, NYSE Technologies, Inc. All rights reserved.

This document is provided or inormation purposes only and the

contents hereo are subject to change without notice. All perormance

inormation was determined in a controlled environment. Actual results

may vary. Perormance inormation is provided AS IS and no warranties

or guarantees are expressed or implied by NYSE Technologies

NYSE Technologies does not guarantee any cost savings or reductions.Results vary based upon each customers existing inrastructure and ees

This document is not warranted to be error-ree, nor subject to any other

warranties or conditions, whether expressed orally or implied

in law, including implied warranties and conditions o merchantability

or ftness or a particular purpose. We specifcally disclaim any liability

with respect to this document and no contractual obligations are ormed

either directly or indirectly by this document. This document may not be

reproduced or transmitted in any orm or by any means, electronic or

mechanical, or any purpose, without our prior written permission.

www.a-tagoup.o

A-Team Group, ounded in 2001, is a publishing, re-search and events group that provides the global com-munity o IT and data proessionals in nancial marketswith the business intelligence they need to excel in theirroles.

Were widely known or our ocused series o publica-tions, research and events across mission-critical unc-tions including high-perormance trading inrastructure,low-latency market data and connectivity, enterprise datamanagement, reerence data, market structure, risk andregulation and more.

A-Team Groups publishing division publishes a range oonline and in print news services including Risk & Regu-lation IT, Reerence Data Review, Market Data Insight,Electronic Trading and Low-Latency.com and A-TeamIQ magazine. Find out more at www.a-teamgroup.com/publishing.

A-Team Groups research division collates data, perormsanalysis and delivers results or internal product devel-opment and marketing, as well as publishing in-depthreports or external use, examples o which include:BusinessEntityIdentiers:TheCrucialFoundationfor

Accurate Risk ManagementOTCValuations-PricingAssetsinthePostCredit

Crunch WorldBuy-sideFirmsTakeaHardLookatDataPractices:

Derivatives Push the Data Management EnvelopeAreContributedBondPricestheHiddenGeminFixed

Income?FasterThanaSpeedingBulletLow-LatencyArchi-tectures and Building Blocks or Tomorrows TradingApplicationsBuyerPersona-TheInuenceBehindDataManage-mentDecisions,andmore

Find out more at www.a-teamgroup.com/research

For more inormation visit:

www.a-teamgroup.com


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A-Ta Goup

m al nyse tchl stM, la cac :

emal: [email protected]

W: www.yse.cm/techges

Te:

e: + 44 20 7987 5400

Amca: +1 (212) 510 3600

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a-team group: super feed performance and efficiency

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