I went along to the Risk USA event yesterday and caught a good panel in the afternoon called “Garbage in, garbage out” Servicing the data supply and analytic needs for risk management.
In particular, one of the speakers, Frank R. Brown, described some work he had done as a consultant at one financial institution on tracking and rebalancing an index product. To do this, Frank had to integrate the constituent instrument symbology of the:
- Index Provider
- Real-Time Data Provider
- Rebalancing Software
- In-house Trading System
On top of this, corporate events might result in changes to symbology that not all providers would be up to date on, with various lags before all had caught up with the corporate action (rebalancing software often late, custodian often not changing symbol at all). He mentioned that he did all of this symbology management manually in Excel.
Of his time, he said he spent:
- 65% on managing the symbology and dealing with data issues
- 20% managing the various vendor APIs in Excel to update the data
- 15% on tracking and rebalancing
To sum up, he said that a productive work level of 15 cents in the dollar wasn’t good value for the client and yet the issue continues on and on. I don’t think that his example was particularly earth shattering in terms of newness, but it put in a very simple and pragmatic context the importance of doing some of the simple things right and the benefits of a more automated approach to data management, even before you delve into the data quality/validity issues of the market data itself.
Just to end on an entertaining note, then back to the title of the talk on “Garbage-in, garbage-out…” the panel moderator (Domenic Iannaccone of Sybase) put forward a good quote he had heard:
“If everyone used the same garbage at least that would be a step forward!”
Transparency and consistency can take many forms, but I didn’t know it needed to apply to incorrect data too!…