By Peter Simpson, OneTick Product Owner
The market data ecosystem continues to evolve in response to RTS 24, U.S. SIP reform, and evolutions towards 24 x 7 trading, requiring firms to stay agile, innovative, and forward-thinking to leverage these changes effectively.
As regulators around the world continue to evolve market data infrastructure, one of the most significant ongoing changes for the U.S. is the reform of the Securities Information Processor (SIP) driven by SEC Rule Changes which started in 2025.
The upcoming changes to the U.S. SIP are designed to address issues of latency, granularity, and coverage and provide a more comprehensive and timely view of market activity. These reforms will likely include higher-frequency data feeds, faster data dissemination, and better alignment with the needs of both institutional and retail traders.
From a quantitative perspective, U.S. SIP reform represents a significant opportunity to gain access to richer, more granular datasets. For quants developing high-frequency trading strategies, this could mean more accurate real-time data for backtesting and decision-making. For market structure researchers, the increased granularity and faster data dissemination will allow for more precise modeling of market liquidity, price discovery, and execution dynamics.
However, this new landscape will also introduce challenges, particularly around latency and data integration. These faster and more frequent data feeds will require firms to adapt their systems to handle larger volumes of data in real-time, without compromising performance. For quants, this may mean investing in more sophisticated infrastructure and algorithms to ensure that strategies can react to market conditions without delays.
Here’s what’s happening - beginning with the odd‑lot activation around April 27, 2026 and no later than the first business day of May 2026, the SIPs will disseminate top‑of‑book odd‑lot quotations priced at or better than the NBBO, including the best odd‑lot bid and offer across all Participants (the “BOLO”) and the best odd‑lot bid and offer from each individual Participant. This represents a fundamental change to the consolidated tape: odd‑lot quotes have never been part of core data, so the tape has historically understated true market depth, particularly in high‑priced, highly liquid names.
Odd‑lot quotes will be carried on the existing SIP channels alongside round‑lot quotes, and vendors must adapt to new fields and behaviors, which requires data subscribers to update their message parsing and processing logic ahead of the hot‑cut release. Given the high volume of odd‑lot activity relative to round lots in modern markets, overall quote message rates are expected to rise materially, driving higher demands on data storage, real‑time feed processing capacity, and historical replay infrastructure for backtesting and analytics.
For trade‑surveillance teams, the challenge is compounded: odd‑lot quotes are not protected under Regulation NMS and do not affect the NBBO, so surveillance models will need to be explicitly updated to handle a new category of quote data that is visible but non-protected, and to correctly attribute trading behavior relative to a more granular view of the order book.
Beyond U.S. equities, structural changes are accelerating across derivatives and international markets.
In the U.S., NYSE Arca has received SEC approval for a 22-hour weekday schedule targeting late 2026. Nasdaq is also proposing a near-24×5 model on a similar timeline, with approval granted for NMS stocks and ETPs to trade 23 hours a day, five days a week.
Clearing and SIP infrastructure are tracking the same roadmap: the SIP Operating Committees have submitted a Plan Amendment targeting 8:00 p.m. Sunday through 8:00 p.m. Friday operations, with a December 2026 launch pending SEC approval.
Internationally, in 2025 LSEG was reported to be exploring 24-hour trading. HKEX has outlined a path toward near-24-hour derivatives trading with announcements just this week, and CME Group has announced 24/7 trading for cryptocurrency futures and options beginning in May 2026.
Each of these developments carries direct implications for how data is captured, stored, and analyzed: evolving session boundaries, shifting liquidity profiles outside traditional core hours, and the need to re-engineer surveillance and analytics pipelines to support continuous or near-continuous data flows across time zones.
For quants and data engineers, the implication is straightforward: surveillance models, storage architectures, and analytics pipelines built around discrete daily sessions will need to be rethought for a market that no longer has a predictable open and close.
Originally planned for November 2025, minimum tick sizes will be assigned in tiers based on each stock’s time‑weighted average quoted spread under the revised Regulation NMS framework, with the most liquid securities moving from $0.01 increments to finer steps such as $0.005. Tick‑size classifications are recalibrated twice a year, using three‑month evaluation windows, so assignments can shift as underlying liquidity and spreads evolve.
Regulatory and industry estimates suggest on the order of 1,700 securities will transition to smaller tick sizes, representing a disproportionate share of overall trading volume, which materially increases the number of quote and trade messages generated in the most active names and, in turn, the volume of tick data that must be stored, processed, and replayed for analytics and backtesting.
The SEC has issued an exemptive order deferring compliance with the amended tick‑size rules from the first business day of November 2025 to the first business day of November 2026, effectively pushing implementation into late 2026 to allow additional time for industry readiness, capacity planning for data‑storage and infrastructure upgrades, and coordination with related market‑structure reforms.
For quantitative strategies and market‑surveillance teams, the change is structurally significant: smaller ticks are expected to tighten spreads, alter queue‑priority and microstructure dynamics, and increase market‑data volumes, requiring both careful recalibration of execution logic and historical backtesting assumptions and enhancements to surveillance models, storage architectures, and real‑time monitoring pipelines so they can scale to higher message rates and more granular pricing without loss of coverage or performance.
As the regulatory and market infrastructure landscape evolves, maintaining the integrity of backtesting and research reproducibility becomes increasingly important. The introduction of RTS 24 and U.S. SIP reform brings both opportunities for improved research accuracy and challenges around data management.
Precise, time-sequenced order records enable more accurate backtesting, allowing quants to simulate strategies in a market environment that reflects the true sequence of events. This increased fidelity can lead to more reliable performance metrics and, ultimately, better-informed trading decisions. However, the complexity of managing large volumes of high-frequency data can introduce new risks—particularly around data quality and consistency.
Data quality checks present an ever growing concern because the standards are consistently evolving… Examples below:
For backtesting to remain reliable in this new environment, quants must ensure that their data pipelines are robust, well-tested, and able to handle the new demands placed on them. This includes having mechanisms in place to verify the accuracy and integrity of the data at each stage of the backtesting process, from initial data collection to final model evaluation.
As the regulatory standards around market data continue to evolve, so too must the systems and processes that support market research and trading. RTS 24 and U.S. SIP reform are just the beginning of a broader trend towards more granular, real-time, and transparent data across global markets.
For quants, data engineers, and market participants, the key to staying ahead of the curve will be embracing these changes and adapting to the new realities of market data. By developing the right infrastructure, refining data models, and investing in the tools needed to handle higher-frequency data, firms can turn these regulatory challenges into opportunities for innovation and growth.
In the coming years, we expect to see even more transformative changes to the way market data is captured, processed, and distributed. For those who are able to adapt quickly and leverage the power of these new data streams, the potential rewards are immense.
The future of market data is here—are you ready to embrace it?
Schedule a call with the OneTick team today.
Best wishes,
Peter SImpson
Learn more at onetick.com or request a private demo here.