Market Data ♥ Market Volatility

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On this Valentine’s Day, MayStreet turned to our first love – market data – to put January’s market volatility into context.

Here at MayStreet, we live and breathe market data. Our team monitors and analyzes hundreds of feeds globally each day and has been particularly intrigued by the message traffic trends we observed on both OPRA (the consolidated U.S. listed options quote and trade feed) and the U.S. Equity SIPs (the consolidated US equities quote and trade feeds – CTS, CQS, UTDF and UQDF) during the period of intense volatility at the end of January.

As you may recall, a lot happened during the week of January 24. There was the stunning market rally on Monday, with the Dow closing in the green after being down more than 1,000 points earlier in the day. Tuesday saw big selloffs in advance of Wednesday’s Fed meeting, Thursday brought the Bureau of Economic Analysis’ Q4 2021 GDP report and Q4 corporate earnings were announced throughout the week. All of that led to a VIX that closed significantly above normal – between 32.8 and 38.9 – each day of the week (for context, anything above 20 is seen as “high”). 

Here’s how OPRA and the U.S. Equity SIPs responded:


As market data practitioners are well aware, OPRA is the big kahuna of message volume – no other feed even comes close. Earlier this year, OPRA reported that December 2021 represented a new all-time high for peak transactions per day – 128.5 billion, on average, for the month. Given the extreme volatility of the week of January 24, we compared our observed OPRA message traffic (measured in bytes) for the week to December 2021’s peak volume day, Dec 2. 

The results were eye opening, to say the least: 

December 2021 was not just OPRA’s high-water mark for the year in terms of message volume, it also represented the all-time peak (which is even more surprising given that December has historically been considered a slow month). Yet compared to 2021’s peak day of December 2, the week of January 24’s message volumes were even higher. Monday represented the week’s peak – and unsurprisingly, the VIX also reached its high for the week that day – and even the week’s lightest day was still slightly higher than December 2. 

U.S. Equity SIPs

The impact of the week’s market volatility was even more pronounced in the U.S. Equity SIPs. 

The Equity SIPs’ peak message volume day (also measured in bytes) in December 2021 was December 3 (rather than December 2 for OPRA). As you can see, the Equity SIP feeds showed even higher increases in message volumes as compared to the Equity SIPs’ December peak.

Additionally, like OPRA, the Equity SIPs peaked the same day the VIX did – January 24 – with message volume that was 45% greater than the December 3 peak.


Comparing the entirety of January 2022 to December 2021, there was a 24% increase in the U.S. Equity SIPs’ message volume versus a 10% increase for OPRA. But since OPRA dwarfs the U.S. Equity SIPs in terms of message volume (by a factor of approximately 20x), the OPRA increases are a much bigger deal given the real compute and bandwidth resource drain it represents.

Despite both OPRA and the U.S. Equity SIP feeds peaking on the same day, we neither observed nor heard of any issues across the industry on that day, which is even more impressive when you consider that a pre-market power outage required OPRA to broadcast from its remote data center throughout the day. Kudos to both OPRA and the U.S. Equity SIPs for managing to withstand significant message loads without issue. As we move forward, it is also a reminder that all market data infrastructure – from the exchanges’ all the way down to participants’ – must be designed to handle simultaneous peaks, which are increasing in frequency and intensity. 

MayStreet ♥ Market Data

As always, we’re curious to compare notes on best practices with others in the market data trenches. Drop us a note at or message us on social, even if it’s just to tell us you love market data as much as we do. To keep up with everything we are doing, follow us on LinkedIn.