The sheer gravitational force of the market data plant is pulling the rest of the trading assembly line into its complex. Applications such as OMS's, CEP platforms, P&L blotters, portfolio risk analysis, TCA, quantitative modeling and compliance monitoring all have an ever increasing need to quickly and efficiently marry global market data to their siloed application data.
In the past, market datasets were small enough to allow them to be pulled in a reasonable amount of time to each of these trading applications independently, or if there was enough system downtime between successive business days, it did not matter if it took a few hours every night to pull the data. Now a few hours have grown into at times half a day to get, for example, all North American equity quote data.
The gravitational pull of the market data plant will continue to strengthen and force more and more trading applications to import some or all of their data and/or analytics into a market data platform such as that provided by Vhayu. For most of the applications previously mentioned, the growth rates of the siloed datasets pale in comparison with the growth rates of the market data universe. The only way that trading houses can hope to keep up with explosive market data volumes is to integrate the trading desk data silos into the market data plant.
More and more of Vhayu's equity customers are bringing their internal order flow into our market data platform for analysis on a historical basis. The next logical step is to do this on a real-time basis. On the fixed income side, Vhayu customers have imported bond reference data history, futures contract information and spot FX trades directly into the system. Prospective customers have approached Vhayu recently about how to integrate a historical bond (govies and corporate) ratings database into their platform, in order to do global bond portfolio re-balancing and risk assessment analysis.
As many of the competitive and collaborative players such as exchanges, broker/dealers, banks, hedge/pension/mutual funds, regulatory bodies and government banks face the ever increasing volumes of trade data, which of these entities will continue to resist the pull of the market data plant versus those who embrace it and adopt platforms such as Vhayu remains to be seen.
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