FIBV Data Vending Workshop

Michael Atkin, FISDTaipei13-14 September 2001

FISD: A Global Market Data Business Forum

Neutral trade association for organizations in the market data industry

140 organizational members around the worldMembers are responsible for their own strategic

and commercial interests within FISD Staff acts as a neutral facilitator of the

discussion and manager of the consensus agenda that emerges as a result

FISD Executive Committee

Exchanges (Chicago Board of Trade, Chicago Mercantile Exchange, Deutsche Boerse AG, Euronext, London Stock Exchange, Nasdaq Stock Market, New York Mercantile Exchange, New York

Stock Exchange, Toronto Stock Exchange) Vendors (Bloomberg Financial, Bridge Information, Financial

Times, FININFO SA, Primark Corp., Reuters, S&P Comstock, Telekurs Financial, Thomson Financial)

User Firms (Charles Schwab, Credit Suisse First Boston, Fidelity Investments, JP Morgan Chase, Lehman Brothers Inc., Merrill Lynch, Morgan Stanley & Co., UK Information Provider User Group, Wellington Management Co., LLP)

Tomorrow’s Data Environment

The new “age of efficiency and automation” is upon us

Standards: what you don’t know can hurt youFour Core Areas

Straight Through Processing Data Quality and Consistency Market Data Administration Intellectual property rights

Straight Through Processing

The automated processing of securities transactions from trade inception to settlement

The back office moves forwardSecurity identification in automated

environments (symbology) Links between instruments and corporate action

information Logic of symbol construction Coordinated global exchange symbology

Data Quality

MDDL (XML for market data)Data Volumes

Quote mitigation strategies Static data outside of trading hours

Data Flags Required for accurate processing Cancellations, corrections, halts, market status, etc.

Transparency of price types

Network reliability

Market Data Administration

Bring contracts up to dateTransparent, consistent and rational market

data business policiesBusiness models that promote e-commerceBusiness process automation

Product/customer identification standards Billing data element standards

Simplification of processes

Market Data Definition Language

What is MDDL?

XML-based interchange format on the fields needed to describe Financial instruments Corporate events Market-related indicators

Mission of MDDL Promote data interoperability Standard definition of terms and common use of fields Extensible!

Core MDDL Question

Why would vendors who have built a core business around proprietary data formats want to shift to an open format standard? User demand Enhance product functionality Straight through processing

Why Do We Need MDDL?

Application efficiency (user demand) Integrate data from multiple sources Shift resources from “data formats” to “data quality

Product functionality (data relationships) Standard data models Common data directory for multiple classes Data linkages

Straight through processing ISO 15022, BEI, ISIN, message standard is XML

MDDL Requirements

Support multiple vendors Common vendor interface Common request format

(ISIN, ticker, instrument type)

Accommodate vendor and exchange specific fields

Support entitlement and permissioning requirements

Standardize data field names

Provide a mechanism for validation and data quality

Facilitate security identification for STP

Common request/response interface

Transparency, Disclosure and Exchange Obligations

Overview of Developments in the United States

Market Data Regulation

What’s going on? Securities and Exchange Commission Advisory

Committee on Market Information House Financial Services Subcommittee Database protection

Environmental Factors Demutalization/for-profit exchanges Online trading/retail investor access Decimalization and capacity issues

U.S. Market Structure

SEC ObjectivesExchange Act and 1975 Amendments

Section 11A (establishment of National Market System)

Transactions Reporting Rule Quote Rule Display Rule

Issues Being Addressed

The definition of transparency NBBO (best quotation and last sale) Data beyond mandatory minimum

Consolidated data streamCost of market data and revenue sharingAccess to data (terms and conditions)Data ownershipCapacity and quote mitigation

Advisory Committee Recommendations

Transparency Fundamental component of NMS Counterbalance to fragmentation

Does existing systems provide sufficient transparency? Merits of display rule Provision of data outside the display rule Availability of factors of production

Recommendations

Consolidation Single versus competing consolidators Systemic risks

Plan Administration Transparency of fees, contractual terms, business

requirements and administrative procedures Rationale of business policies Automation of business processes

Recommendations

Fees and Revenues No change to statutory standard NYSE withdraw from CTA SEC oversight

Capacity NBBO for options No penny increments More aggressive quote mitigation strategies

Recommendations

Data Ownership Not part of “Seligman Committee” Competition and vendor display rule Regulatory structure inhibits competition

Focus of Congressional inquiry Database protection legislation Feist Case -- Is the exchange the creator or collector

of market data? This is just the opening salvo in a long battle

Tomorrow’s Standards Today

MDDL, Market Data Business Policy, Symbology and Business Process Automation

Simplify, Automate, Standardize

New mantra for the global market data industryStandardization is good businessWill the global financial industry work

cooperatively to implement standards? STP standards (i.e. BEI, ISO 15022 data dictionary, MIC,

security identification/ISIN+, counter party ID)

Data distribution (i.e. MDDL, XBRL, NewML, price types)

Billing and reporting (i.e. product identification, customer

identification, billing data elements)

STP Standards

Firms are in the midst of technology planning cycles for STP Growth in domestic and cross-border trading volumes More complex investment/risk management strategies Lower margins (save money through productivity and

efficiency gains)

Regulatory requirements for T+1

Changing market conditions require a fast, efficient way to process transactions from point-of-trade to point-of-settlement

Unique Security Identification

Accurate and timely security identification is one of the keys to STP Most front-offices identify securities by name or symbol

while back-offices use number Primary identifiers must be accurate, unique, available

and usable

Incompatible databases and the lack of data standards mean high error rates, valuation errors, exception-based processing, trades of the wrong security and trade failures

Will ISIN Survive STP?

ISIN is an issue identifier standard Creation of the ANNA Service Bureau Accuracy, maintenance, quality issues on track ISIN alone is not sufficient for unique identification

Place of official listing is essential for pricing and settlement of multiple listings (NOTE: source of the data is the stock exchanges, not the numbering agencies)

Register is important for security routing Place of trade is important for due diligence and

market compliance

Data Distribution and MDDL

The end of the era of proprietary formats?Standard data formats are useful for

moving data between applicationsStandard data definitions (taxonomy) are

useful for creating data relationships and promoting content transparency

Market data (MDDL) is a component of many other XML initiatives (news, business research, STP, clearing/settlement)

Vocabulary Development

Common taxonomy for market dataMDDL Domains

Instruments (equities, collective investment vehicles, debt, contracts, units)

Indicators (indices, financial and exchange statistics, ratings, economic indicators)

Corporate events (notifications, descriptive data, fundamentals

MDDL Descriptors/Glossary

IdentifiersValuations (prices)MeasuresStatisticsDates and timesCurrenciesLocations

HoldingsLoads and fees Industry classificationAsset classSource IndicatorsFeatures

Technical Development

Extensibility is the keyMinimal structure definedXML schema and DTD supportedElement based approachConcept of reference listsProperty concept that inherits through

hierarchy

MDDL Status

Version 1.0 beta is now availableCommon equities, mutual funds and

indices only1.0 final at FISD’s World Financial

Information Conference (London)http://www.mddl.org

http:www.fisd.net/mddl

Market Data Business Management

Everything starts with the contractMarket data business policies

Exchange business practices Transparency of policies and consistency of

interpretation Data usage (redistribution, indices, derived data)

Business process automation

Contractual Issues

Principal document governing what vendors, redistributors and subscribers can/can’t do with the data

(1) definition of market data (7) exchange fees

(2) content and supply (8) unit of count

(3) agreements (9) billing and payment

(4) rights to use (vendor) (10) reporting requirements

(5) rights to use (subscriber) (11) audit requirements

(6) system descriptions (12) other market data policies

Problems with Contracts

Practical implications Old contracts/new situations Conflicts of interpretation Complex communications chain Global lack of uniformity

Market Data Policy Project

Comprehensive database covering all obligations and requirements covered by exchange contracts Compliance with contractual obligations Clear real-world interpretations Policy comparison Business considerations (i.e. external

redistribution)

Exchange Business Practices

Prior Approval versus Vendor Discretion (business model for redistribution of data)

User Classification (used to determine the rights to use data and fee levels)

Unit of Count (how market data usage is counted, priced and applied in contracts)

Exchange Business Practices

Billing and Reporting RequirementsSubscriber Agreements (used to determine

liability and to recognize rights and restrictions on data usage)

Non-Real Time Data (policies governing the use of delayed data)

Derived Data (extent to which vendors/subscribers can create their own intellectual property from exchange market data and under what terms)

Business Process Automation

Simplification and automation of business processes is important to everyone and one of our most important administrative objectives

Three core goals Data definition standards Process simplification Data consistency

In the age of e-commerce -- we can do better

Now for the Sales Pitch

Join FISD and get involved in this debate

Attend the 5th World Financial Information Conference October 30 - November 2 in London

Michael Atkin (direct) 202.789.4450matkin@siia.net (web) www.fisd.net