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Published byBeverley Newman Modified over 8 years ago
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MiFID impact on Market Data Business – Services and Solutions offered by DBAG FESE Convention June, 8th, 2006 Dr. Holger Wohlenberg Managing Director Market Data & Analytics Deutsche Börse AG
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1 The MiFID Monster ….. Under MiFID, exchanges will lose significant revenues in terms of market data, print fees for off- exchange trades and trade fees. The total annual lost revenues will be over €300 million annually, suggests the analysis. „An introduction to MiFID“, Celent White Paper 2005 Loss of concentration rule Market data fragmentation Market fragmentation Internalization Intermediation Implementation cost
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2 Value Proposition Attracted participants: Expertise: Leverage procedural skills (eg., billing, auditing) Service Level: Utilize available add-ons (eg., analysis tools) Leverage: Benefit from co-marketing/sales with related HQ content Fairness: Equalize dissemination to vendors Scale: Connect to data from multiple sources via one format/conn. UserVendor ( ) ( ) IF/SIMTF Risk/Flexibility/Speed: Lower invest – lead times via outsourcing Latency/Throughput: Leverage of fast/high volume techn. (CEF) ( ) ( ) Reach: Instant access to 360+ vendors worldwide Connectivity: Use existing interfaces/connections ( ) ( ) ( ) …DBAG‘s position…
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3 … DBAG’s offer – the MiFID Toolbox MTF Data Dissemination Counterparty Data Cleansing Analytics and Statistics Data Warehouse Solutions Transaction Reporting Post-Trade Transparency Pre-Trade Transparency Module Target clientsServices SI‘s All IF‘s including SI‘s MTF‘s All IF‘s including SI‘s, MTF‘s OTC quote dissemination via CEF Additional Data Warehouse Services OTC trade publication via CEF incl. value-add services Optional post-trade services e.g. trade matching clearing and settlement, additional Data Warehouse Services Complete market data business outsourcing service Dissemination, Marketing & Sales, Contracts + Billing Transaction Reporting (currently § 9 WpHG) OTC Data Storage Ex-post proof of Best Execution Data Drilling E.g. on- and off-exchange Member Rankings Provide cost-efficient data cleansing for increased demand of reliable counterparty data
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