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Fixed Income Trading: New venues

A simple question came up recently in a conversation – how many new Fixed Income trading venues are there?  I could not think of anywhere th...

Wednesday, 13 May 2015

The market data product that the global financial services industry really wants....

On a number of projects I have had to work with numerous datasets.  As an example, for a client with a global trading business the requirement included:
 
Bloomberg codes for FIX trading of futures
RIC codes for FIX trading of equities
ISIN codes for FIX trading of some participation notes
ISIN codes for FIX trading of some Fixed Income instruments
CUSIP codes for FIX trading of some Fixed Income instruments
Synthetic instrument codes for some money market instruments
Positions were managed for some instruments using Sedol codes and for others ISINs.  And for money market instruments, synthetic identifiers.  A real mish-mash...
 
Some good collateral material can be found at the LSE and specifically ISIN/SEDOL/MIC/Country of Register linkages-HSBC - See image below
 
There is a good background piece on the ISIN vs Bloomberg Open Symbology initiative here.
 
The challenge is that when seeking to ensure that risk positions are managed correctly, there is usually a requirement for a cross reference table, such that there is a mapping
 
Bloomberg ==RIC ==Sedol+MIC==ISIN+MIC (and so on for every different symbology)
ISIN/SEDOL/MIC/Country of Register linkages-HSBC
For electronic trading this would be incredibly useful.  Especially if a vendor could offer an event driven feed of data such that futures and options expiry data changes were notified in a sensible way.
 
London is full of smart folks trying to offer the next big thing within fintech.  This data proposal is nowhere near as glamorous and would be a nightmare to negotiate - imagine trying to get Reuters and Bloomberg to play nicely together...
 
But think of the efficiency gains to everyone in the industry.  Not "yet another identifier scheme" but a grand business utility to organise and rationalise the existing data symbology.
 

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