FIBV Data Vending Workshop

1
FIBV Data Vending Workshop

• Michael Atkin, FISD
• Taipei
• 13-14 September 2001

2
FISD A Global Market Data Business Forum

• Neutral trade association for organizations in
  the market data industry
• 140 organizational members around the world
• Members 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

3
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, SP 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)

4
Tomorrows Data Environment

• The new age of efficiency and automation is
  upon us
• Standards what you dont know can hurt you
• Four Core Areas
• Straight Through Processing
• Data Quality and Consistency
• Market Data Administration
• Intellectual property rights

5
Straight Through Processing

• The automated processing of securities
  transactions from trade inception to settlement
• The back office moves forward
• Security identification in automated environments
  (symbology)
• Links between instruments and corporate action
  information
• Logic of symbol construction
• Coordinated global exchange symbology

6
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

7
Market Data Administration

• Bring contracts up to date
• Transparent, consistent and rational market data
  business policies
• Business models that promote e-commerce
• Business process automation
• Product/customer identification standards
• Billing data element standards
• Simplification of processes

8
Market Data Definition Language
9
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!

10
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

11
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

12
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

13
Transparency, Disclosure and Exchange Obligations

• Overview of Developments in the United States

14
Market Data Regulation

• Whats 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

15
U.S. Market Structure

• SEC Objectives
• Exchange Act and 1975 Amendments
• Section 11A (establishment of National Market
  System)
• Transactions Reporting Rule
• Quote Rule
• Display Rule

16
Issues Being Addressed

• The definition of transparency
• NBBO (best quotation and last sale)
• Data beyond mandatory minimum
• Consolidated data stream
• Cost of market data and revenue sharing
• Access to data (terms and conditions)
• Data ownership
• Capacity and quote mitigation

17
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

18
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

19
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

20
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

21
Tomorrows Standards Today

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

22
Simplify, Automate, Standardize

• New mantra for the global market data industry
• Standardization is good business
• Will 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)

23
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 T1
• Changing market conditions require a fast,
  efficient way to process transactions from
  point-of-trade to point-of-settlement

24
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

25
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

26
Data Distribution and MDDL

• The end of the era of proprietary formats?
• Standard data formats are useful for moving data
  between applications
• Standard 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)

27
Vocabulary Development

• Common taxonomy for market data
• MDDL Domains
• Instruments (equities, collective investment
  vehicles, debt, contracts, units)
• Indicators (indices, financial and exchange
  statistics, ratings, economic indicators)
• Corporate events (notifications, descriptive
  data, fundamentals

28
MDDL Descriptors/Glossary

• Identifiers
• Valuations (prices)
• Measures
• Statistics
• Dates and times
• Currencies
• Locations

• Holdings
• Loads and fees
• Industry classification
• Asset class
• Source
• Indicators
• Features

29
Technical Development

• Extensibility is the key
• Minimal structure defined
• XML schema and DTD supported
• Element based approach
• Concept of reference lists
• Property concept that inherits through hierarchy

30
MDDL Status

• Version 1.0 beta is now available
• Common equities, mutual funds and indices only
• 1.0 final at FISDs World Financial Information
  Conference (London)
• http//www.mddl.orghttpwww.fisd.net/mddl

31
Market Data Business Management

• Everything starts with the contract
• Market data business policies
• Exchange business practices
• Transparency of policies and consistency of
  interpretation
• Data usage (redistribution, indices, derived
  data)
• Business process automation

32
Contractual Issues

• Principal document governing what vendors,
  redistributors and subscribers can/cant 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

33
Problems with Contracts

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

34
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)

35
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)

36
Exchange Business Practices

• Billing and Reporting Requirements
• Subscriber 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)

37
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

38
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_at_siia.ne
  t (web) www.fisd.net