In 1993, one of the world’s largest exchange holding companies, CBOE, introduced the Volatility Index, which is now a key measure of near-term volatility in the market. Yesterday, it posted its largest-ever one-day rise as markets posted massive losses amidst spiking trading volumes.
Apart from the pain these events are causing for traders, investors, and those who dare to check their 401(K) balances, financial services firms that operate trading platforms have their own set of worries keeping them up at night: how can they manage the volume spikes accompanying these periods of high volatility?
Their trading platforms must be able to process trades while simultaneously processing analytic queries – handling billions of transactions per day while supporting thousands of analytic queries per second from hundreds of applications. They must be simultaneously massively scalable and bulletproof: able to accommodate unexpected levels of volatility without incident.
When market volatility and trading volumes spike unexpectedly like they are doing now, transaction and query volumes may exceed the planned system headroom. The resulting consequences, including dropped trades, downtime, or a systems failure, can be catastrophic, incurring financial losses and reputational damage of the firm.
InterSystems technology is powering trading platforms for some of the world’s largest investment banks – and has enabled them to withstand all major market corrections, including 2008 financial crisis, the 2010 “flash crash,” and the devaluation of China’s currency in 2015, and this week’s tsunami.
What makes a data platform stable and useful during these periods of high volatility is the ability to process transactions and analytics simultaneously – at scale – even when workloads spike unexpectedly. And it’s one of the hallmarks of InterSystems IRIS Data Platform. To learn more, please read our product literature.
Joe Lichtenberg is responsible for product and industry marketing for data platform software at InterSystems. Joe has decades of experience working with various data management, analytics, and cloud computing technology providers.
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