We are so proud to introduce dxFeed ZeroDTE, a new quantitative analytics solution designed to bring greater transparency and precision to the rapidly growing market for zero-days-to-expiration (0DTE) options.
Developed by dxFeed’s AI & Quant Research team, the solution transforms live SPX and XSP options data into comprehensive pricing and risk analytics, enabling brokers, trading platforms, and analytics providers to give traders a clearer understanding of potential outcomes before entering a trade.
The introduction comes as 0DTE options continue to reshape US derivatives markets. According to Cboe, same-day contracts accounted for approximately 65%* of SPX options trading volume in Q3 2026, averaging a record 3.2 million contracts daily. Yet the analytical tools available to traders have not always kept pace with this growth, particularly when it comes to understanding the risks behind complex, multi-leg strategies — a challenge previously highlighted by Jon Light, Senior Director of Product Management, Devexperts.
Beyond Probability of Profit: Understanding the Full Risk
While conventional trading interfaces typically display strikes, premiums, and margin requirements, ZeroDTE reveals the market-implied probabilities behind each strategy, including the likelihood of retaining the full premium, experiencing a partial loss, or reaching the maximum possible loss.
Unlike traditional probability calculations based on a single implied volatility estimate or delta, the solution analyzes the entire live options chain, incorporating the volatility smile and distribution tails to deliver a consistent view of market-implied outcomes.
Through a single API integration, platforms can provide traders with:
- Market-implied probabilities of different profit and loss outcomes.
- Fair value comparisons against displayed market prices.
- Maximum profit, maximum loss, and break-even levels for individual strategies.
- Market-implied distribution of today’s close, derived from live options data.
- Strategies defined in units of the day’s priced move, so the same structure can be compared across days and market conditions .
Supporting popular structures including iron condors, butterflies, straddles, strangles, and vertical spreads, the service brings sophisticated quantitative analytics directly into the trading experience.
“Retail platforms are good at showing a probability of profit, and most will show the maximum loss as well. What they don’t show is how likely that loss is,” said Anton Antonov, Head of AI & Quant Research at dxFeed. “ZeroDTE puts the odds next to the worst case: the chance of keeping the credit, of a partial loss and of the maximum loss, read from the whole option chain rather than a single volatility number. Rather than predicting where the market will go, we give traders the tools to understand what current options prices imply, evaluate different strategies consistently, and make more informed decisions.”
Expanding dxFeed’s Intelligent Market Data Ecosystem
ZeroDTE marks another milestone in dxFeed’s evolution from market data delivery toward advanced analytics, quantitative research, and intelligent financial technology.
The solution joins dxFeed’s growing portfolio of innovative technologies, including SummerFox, its award-winning AI-powered market intelligence solution; Grenadier, an AI-based market data anomaly detection technology; and dxScript, an AI-assisted scripting environment for custom market analytics and indicators.
Together, these solutions reinforce dxFeed’s commitment to transforming high-quality financial data into accessible, actionable intelligence for the global trading community.
The new analytics capabilities have already been integrated into DXcharts, demonstrating how advanced options risk metrics can be incorporated directly into trading and charting interfaces.
For a deeper look at the technical capabilities, key features, and practical applications of ZeroDTE, explore our in-depth article.
*All figures are market-implied from current option prices and are not a forecast or a recommendation
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