Navigating the complex world of equity options data

In an exclusive Risk.net webinar, convened in collaboration with Cboe Global Markets, experts discussed the expanding world of equity options data, the rise of retail investment within it, and the technological challenges and opportunities associated with these factors

The equity options market has experienced unprecedented growth in recent years, primarily driven by the retail investor market.

The global Covid-19 pandemic-led lockdown – which shut offices, shops, schools and leisure activities – combined with a stock market in freefall and a world in crisis created a desire to hedge the unpredictable, as well as an apparent opportunity to ‘win big’ in the stock markets. Moreover, a growth in free-to-trade broker apps made trading available to a wider group of investors.

By any measure, growth has exploded, creating a vast amount of data, all of which needs processing, analysing and storing. This is happening in an unpredictable environment of rising interest rates, increasing inflation and higher market volatility.

In this Risk.net webinar panel session with Cboe, experts discussed the changing options landscape, focusing in particular on the rise of retail investment, associated data and risk management challenges, as well as managing large data quantities while maintaining quality.

Here are the key themes that emerged from the discussion.
 

Equity options beckon

The US Options Price Reporting Authority (OPRA) market has recorded an astronomical rise in option series in the past 10 years, reaching 1.6 million options on 6,000 underlying instruments compared with 500,000 a decade ago.¹   

Similarly, messages flowing through the OPRA feed have also witnessed a dramatic rise, from an estimated 10 million a day at their peak a decade ago to almost 40 million messages per second at peak today. Furthermore, 2021 witnessed a peak of around 9.4 million trades a day, and 2022’s peak reached 8.5 million trades a day, more than quadruple the amount a decade ago when peak trades were between 1.5 million and 2 million.¹

“[There is an] enormous amount of data flowing through these systems in the options markets. This puts a strain on everybody – from technology, where you must process all data, store it and get it through your networks, to the trading desks and the market-making groups, as well as the risk groups processing the data to perform their analyses,” said Gerald Hanweck, Cboe.

The intensity extends to the back office, he added, which is tasked with managing all the information from reference data around contracts to the large datasets that come in at the end of each day. Panel participants agreed that the associated data and technology challenges are colossal, as is the opportunity.
 

Data and technology: rising to the challenge

The technological demands for processing, storage and compute for an expanding options trading landscape cannot be underestimated. “The technical challenge is not small. We’re talking about 40Gb a second in bandwidth requirements, and roughly 40 million messages per second at peak flowing through these feeds,” Hanweck said.

Options trading is unique in that a lot of options either don’t quote or never trade. “There are many option quotes that are very wide or sit at zero bid and do not move all day, so there’s a lot of work in taking that data and analysing it, smoothing it out and [assigning] a theoretical value,” he added.

But technology has risen to the challenge, perhaps in part benefiting from a virtuous circle where the technology allows for more trading and the increased trading drives technology improvements. Today, real-time options analytics platforms can map historical data, and provide portfolio margin analytics and trading indicators derived from options data to benefit investors and exchanges alike. It has also become critical to ensure technology can scale up to match the rise in user demand.

Panellists noted how high-performance network cards have evolved, and memory and storage have increased, to match demand for more reliable and secure data. From a quant finance perspective, diverse tools are available to ensure data integrity is maintained, including new techniques for fitting option-pricing models to the observed data in real time.

Risk assessment is important and vital to provide investors with the information they require to make considered decisions, the panel noted, especially in very tight, illiquid markets when there are no prices coming through.
 

Retail influx and the data integrity imperative

Retail investor fervour and interest in the equity options market is clear and is here for the long term, and data integrity is vital to this group. Investors need quick access to reliable and accurate data at the right time to understand the relevant investment risk and reward, and how it could alter over time, the panel noted.

The proliferation of mobile apps for retail investment presents an additional technology challenge as providers must ensure information is available in this medium alongside the traditional web platform. The panel also highlighted how visual formats can help customers understand options more effectively.

Savvy investors are also applying higher-level analytics, including risk parameters, and must be confident of data quality to do this. Cutting-edge technology and data solutions that produce real-time implied volatilities and Greeks – delta, gamma, theta, vega and rho – on the global listed options markets are becoming key in this market.

Investors are now coming on board interested in option spreads, the panel noted, bringing platform service and education to the forefront. Providers are keen to ensure there is education tied into this, including that for new features or data services, as the demand for digestible data and analytics grows. “We never [release] a new feature, a new data service or data point if we can’t actually build some education around it, which, at the end of the day, drives that scalability,” said a panellist.
 

Artificial intelligence (AI)/machine learning and upholding data quality

Consuming high-volume market data feeds in real time does not mean sacrificing quality. Next-generation technology advancements in performance and storage are also being complemented with an evolution of AI, machine learning and statistical techniques to manage quantity and safeguard quality.

“[These techniques mean] we can fit option pricing models to the data in real time, to have a good picture of the theoretical price even if the market liquidity dries up, or if the options markets close but the underlying stocks are still moving,” said Hanweck.

“We are even seeing AI, neural network-type techniques enter the options world to improve data mining, as well as new techniques solving differential equations and option-pricing models with neural networks. This will continue to grow.”
 

Fixed income perspective

Acknowledging an economic climate in which interest rates worldwide are rising to combat inflation and bond prices are selling off, the panel turned to fixed income. While the market is still broadly focused on linear derivatives, there is the possibility that investors will begin embracing the defined downside and asymmetric upside they can achieve with options trading, the panel said, and rethink the traditional 60/40 portfolio.
 

In summary

The rise in retail investment in equity options was not just a Covid-19 lockdown distraction; it clearly is here to stay, even though options volatility, volume of data, and quotes and trades will increase over time. Retail investors have learnt that options have a permanent place in their investment and trading strategies.

The unparalleled growth in this market means that data integrity is more important than ever, and big data feeds in real time need not signal a compromise on quality. It is vital that exchanges help facilitate that next-generation technology hub to make markets more transparent.
 

Notes

^{1. Cboe Global Markets, September 2022}

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