Cboe: Options Exchange Monopoly and AI-Driven Retail Trading Growth

Executive Summary

Cboe Global Markets operates the largest options exchange in the United States, processing more than 40% of all U.S. listed options volume. With $4.9 billion in total net revenue for fiscal 2024 and operating margins exceeding 50%, Cboe is a concentrated, high-margin infrastructure business built on two pillars: monopoly-like market structure in key options products and a data and analytics business that monetizes the information generated by its markets.

AI's impact on Cboe is predominantly positive, at least in the near-to-medium term. AI-powered retail trading tools are democratizing options trading, expanding the addressable user base for Cboe's products. AI-driven quantitative strategies increase volume in Cboe's markets. And AI's ability to process the complexity of options pricing — previously a barrier to mass-market participation — is making options accessible to millions of retail investors who previously would not have traded them. We assign a Margin Pressure Score of 2/10 — firmly protected, with AI as a net tailwind.

Business Through an AI Lens

Cboe's business has three revenue-generating components: exchange services (transaction fees from options, equities, and futures trading), data and access solutions (market data subscriptions, colocation, and connectivity), and global FX (currency trading platform revenues). The exchange services business is the dominant contributor and is inextricably linked to Cboe's proprietary products — particularly VIX derivatives and SPXW (S&P 500 index) options.

AI's impact on options markets is best understood through the lens of volume drivers. Options trading volume increases when: (1) retail investors use options for speculation, income generation (covered calls, cash-secured puts), or portfolio protection; (2) institutional investors hedge portfolios using index options; and (3) quantitative and algorithmic strategies trade options to capture volatility premiums or statistical arbitrage opportunities. AI is accelerating all three categories.

Retail options trading has grown explosively, driven in part by AI-powered investment apps (Robinhood, Webull, tastytrade) that make options mechanics accessible to non-professionals. The 0DTE (zero days to expiration) options phenomenon — daily options on SPX that expire the same day they are traded — has created a massive new trading category that Cboe hosts. 0DTE options now account for approximately 40-50% of total SPX options volume, a direct product of algorithmic and retail AI trading tools that can process same-day options mechanics.

Revenue Exposure

Cboe's revenue concentration in proprietary index options creates both strength and risk. SPX options and VIX derivatives are exclusively listed on Cboe — they cannot be traded on any other exchange. This exclusivity generates significant pricing power and volume concentration.

The options segment is the most valuable and the most AI-influenced. SPX options (including 0DTE) generate the majority of Cboe's options revenue. AI trading tools make SPX options more accessible to retail investors, expanding the potential trading population. Quantitative funds use AI-powered volatility models to trade VIX futures, adding institutional volume to Cboe's derivatives markets.

Data and access solutions is the second most AI-relevant segment. Cboe's Livevol data business provides options analytics and market data to traders, institutional investors, and academic researchers. As AI trading proliferates, demand for high-quality options market data (implied volatility surfaces, term structure data, skew analytics) grows. AI model training on options market data creates incremental demand that Cboe can monetize at premium prices.

The only meaningful revenue risk scenario involves regulatory action on payment for order flow (PFOF) — the practice by which retail brokers sell order flow to market makers, who then trade options on Cboe's platform. If PFOF is significantly restricted (as has been discussed periodically by the SEC), retail options volume could decline as market maker economics deteriorate. This is a regulatory risk, not an AI risk, but it is worth monitoring.

Cost Exposure

Cboe's cost structure is predominantly fixed: technology infrastructure, regulatory compliance, personnel, and depreciation account for the majority of operating expenses. Variable costs (costs that scale with volume) are minimal — the marginal cost of processing an additional options trade is nearly zero once infrastructure is in place.

AI presents cost opportunities in market surveillance, regulatory reporting, and technology operations. Cboe's rule enforcement division monitors billions of options transactions for manipulation, layering, and front-running. AI-powered surveillance systems can improve detection quality while reducing the personnel cost of manual review. This is a direct operating expense reduction opportunity.

Data operations costs are also amenable to AI efficiency. Cboe processes and distributes vast quantities of market data in real time. AI-driven data quality monitoring, anomaly detection, and distribution optimization can reduce operational costs in this area while improving the reliability and completeness of data products.

The most significant cost risk is technology investment required to maintain competitive infrastructure. As AI trading strategies increase the speed and volume of order flow, Cboe must continuously invest in low-latency infrastructure to maintain the sub-millisecond execution times that algorithmic traders require. This is a necessary competitive investment, not an AI-induced cost increase, but it represents a real capital expenditure requirement.

Moat Test

Cboe's moat is deep and multidimensional. The most important component is its proprietary product moat: VIX, the S&P 500 Volatility Index, is a Cboe trademark, and VIX futures and options can only be traded on Cboe. Similarly, SPXW options are exclusively listed on Cboe. These proprietary products generate transaction fees that competing exchanges simply cannot replicate — they would need to create competing volatility index products and convince market participants to migrate liquidity, which is extraordinarily difficult given network effects in options markets.

The liquidity network effect in options is even more powerful than in equities or futures. Options markets have thousands of contracts (different strikes and expirations) for each underlying, and liquidity in each contract is limited. Fragmentation across multiple exchanges reduces liquidity quality disproportionately. This is why options volume concentrates on a single exchange for each underlying — and Cboe has maintained dominant share in SPX and VIX products for decades.

The data moat is a secondary but growing competitive advantage. Cboe's historical options data — spanning decades of volatility surface observations, term structure dynamics, and skew behavior — is a unique data set with increasing value as AI model training for options strategies requires long historical time series.

Timeline Scenarios

1-3 Years (Near Term)

Near-term dynamics are strongly favorable for Cboe. The 0DTE options boom continues as AI-powered retail trading platforms make daily options trading accessible. VIX futures and options volumes remain robust as AI hedge funds and macro traders use volatility derivatives to manage AI-driven market uncertainty. Data revenues grow as AI trading firms and quantitative researchers pay premium prices for Cboe's historical and real-time market data. Revenue growth of 7-10% annually with stable-to-expanding margins.

3-7 Years (Medium Term)

Medium-term, Cboe's growth is driven by international expansion and new product development. The company has expanded into European equity options (EuroCCP acquisition) and is developing new index options products tied to AI-relevant benchmarks. AI-powered portfolio construction tools generate new hedging demand for index options as institutional investors manage AI-driven portfolio risk. PFOF regulatory risk is the most significant medium-term uncertainty.

7+ Years (Long Term)

Long-term, Cboe's options franchise should benefit from continued financialization of the economy — more assets, more investment vehicles, more hedging needs. AI's role in making options accessible to new market participants is a secular tailwind. The introduction of options on AI-related products (volatility indices for AI sector stocks, AI-specific risk management derivatives) represents a potential new revenue category. Cboe's role as the global volatility marketplace is durable.

Bull Case

In the bull case, AI-driven retail and institutional options trading volume grows at 10-12% annually, with 0DTE and weekly options becoming increasingly standard tools for retail portfolio management. Cboe successfully expands internationally, capturing meaningful share of European index options volume. Data revenues grow at 15% annually as AI trading firms pay premium prices for proprietary market data. Operating margins expand above 55% on the favorable revenue mix. The stock sustains a premium multiple reflecting its exchange monopoly economics.

Bear Case

In the bear case, the SEC implements significant restrictions on PFOF and associated retail options payment flows, reducing retail options volume by 20-25%. A prolonged low-volatility market environment reduces demand for VIX-related derivatives. International expansion in European options markets disappoints, failing to replicate the U.S. proprietary product model. Revenue growth decelerates to 2-3% annually with slight margin compression. This bear case is driven primarily by regulatory risk rather than AI-driven competition.

Verdict: AI Margin Pressure Score 2/10

Cboe earns a 2/10 — tied with CME Group as the most protected company in this batch. The proprietary product moat (VIX, SPX options) creates a revenue base that AI cannot disintermediate — these products can only be traded on Cboe by regulatory design and liquidity network effect. AI is a direct tailwind to Cboe's volume: AI trading tools expand retail options participation, AI quantitative strategies increase institutional volume, and AI model training creates incremental demand for Cboe's historical market data. The primary risk is regulatory (PFOF), not AI-driven.

Takeaways for Investors

• Cboe's proprietary product moat (VIX, SPX options) is the foundation of its competitive position — these products can only be traded on Cboe, creating a regulatory and liquidity-based moat that AI cannot disrupt.
• AI is a direct positive catalyst for Cboe's volume: AI-powered retail trading platforms are democratizing options trading and the 0DTE options boom (40-50% of SPX volume) is a direct product of AI-accessible trading tools.
• Data and access solutions revenue (~$900M) is growing as AI trading firms create incremental demand for high-quality options market data for model training and live trading analytics.
• The primary risk is regulatory (PFOF restriction), not AI-driven — investors should monitor SEC options market structure reform proceedings as the most important near-term variable.
• Cboe's international expansion into European index options represents the most significant medium-term growth opportunity, with AI-powered trading platforms potentially accelerating retail options adoption in European markets.
• The combination of exchange monopoly economics, AI-driven volume tailwinds, and growing data revenue creates one of the most AI-resilient business models among S&P 500 financial companies.