There are levels in any market chart that cause price to reverse, accelerate, or stall – levels that have nothing to do with traditional support and resistance drawn from price history. They come from the options market. Specifically, they come from the delta-hedging activity of market makers managing their exposure at high-open-interest strike prices. Fabio, co-founder of MentorQ, has built a platform to make these invisible levels visible to retail traders for the first time.
The concept is not new to institutional traders. Large hedge funds have been using options flow data to inform positioning decisions for decades. What has changed since COVID is the explosive growth in options activity – particularly short-dated options – that has made the options market a primary driver of intraday price behaviour across equities, indices, and futures. Traders who don’t look at options data are, as Fabio puts it, “driving at night with only their headlights” while institutional participants have a full view of the road ahead.
This episode covers the mechanics of how market maker hedging creates reaction zones, how MentorQ quantifies them into actionable levels, and what the backtested results look like across SPX and major stocks.
Watch the full episode below, then read on for the complete breakdown.
Why Options Volume Now Drives Underlying Markets
Before COVID, options were primarily an instrument for sophisticated institutional participants. The growth of commission-free trading platforms (Robinhood, eToro), the GameStop meme stock mania of 2021, and the explosion of zero-day-to-expiry (0DTE) options have fundamentally changed the landscape. Options volume has grown to a point where, in many instruments, it rivals or exceeds spot trading volume.
The consequence for price action traders is significant. When the options market is large relative to the underlying, the hedging activity of market makers can drive price moves independently of fundamentals or traditional chart patterns. The GameStop short squeeze was in part a gamma squeeze – as call buyers kept pushing the stock higher, market makers were forced to continuously buy stock to maintain delta neutrality, creating a self-reinforcing upward spiral that had nothing to do with the company’s fundamentals.
Understanding this mechanism is no longer optional for active traders. If you’re not monitoring where the options market has large open interest concentrations, you’re missing a major driver of price behaviour.
How Market Makers Create Hidden Reaction Zones
The mechanism is straightforward once you understand market maker economics. Unlike customers who take directional views, market makers are in the business of providing liquidity and capturing bid-ask spreads. They don’t want directional exposure. To neutralise it, they use delta hedging – continuously buying or selling the underlying asset to offset the directional risk of the options they’ve sold.
Here’s why this creates reaction zones: at strike prices with very large open interest, a small move in the underlying triggers large delta changes (because gamma is high near the strike). This forces significant market maker hedging activity. If the market is approaching a strike with massive call open interest, market makers who are short those calls must buy the underlying as it rises – which tends to support or accelerate the move. Conversely, when market makers are short puts at a particular strike, they sell the underlying as price falls toward that strike, creating support that doesn’t appear in any traditional technical analysis framework.
The Net Gamma Exposure Chart
MentorQ’s core tool is what Fabio calls the Net Gamma Exposure (GEX) chart. This plots, for a given underlying, the distribution of call gamma and put gamma across all strike prices. Green bars represent call Gamma exposure (strikes where market makers are short calls and must hedge by buying). Red bars represent put Gamma exposure (where they’re short puts and hedge by selling).
The peaks of these distributions – the strike prices with the highest total gamma exposure – define the reaction zones. These are the levels where market maker hedging activity will be most intense, and therefore where you’re most likely to see price stall, reverse, or experience a sharp directional move if the level breaks.
The four primary levels MentorQ defines are:
- Core Resistance: The strike with the highest call Gamma exposure. Acts as a ceiling where market maker delta hedging tends to slow or cap upward moves.
- Put Support: The strike with the highest put Gamma exposure below current price. Acts as a floor where market maker hedging activity tends to support or bounce price.
- Maximum Gamma level: Where total Gamma exposure across all strikes is highest – the most sensitive price level in the current options chain.
- Minimum level: The lower boundary of the expected daily range based on current options positioning.
The Backtested Evidence
Fabio presents backtested results for MentorQ’s One Day Expected Move indicator across SPX from 2019 to 2023. The results show:
- On 87% of trading days, the closing price of SPX stayed above the model’s minimum level.
- On 85% of trading days, it stayed below the maximum level.
Similar results were found when applied to high-options-volume stocks like Nvidia and Tesla, with success rates of approximately 86% for both the upper and lower bound conditions. MentorQ is working with a quantitative research firm to backtest the full dataset across all covered instruments.
These hit rates are not trading signals – they’re probabilistic constraints on the expected daily range. But they’re actionable: a trader entering a spread trade, an iron condor, or a directional trade who knows there’s an 85%+ probability that price will not exceed a specific level has meaningful statistical justification for their risk management levels.
How to Apply This as a Non-Options Trader
One of the most useful points Fabio makes is that you don’t need to trade options to benefit from options data. If you’re a futures trader, a stock trader, or an ETF trader, the reaction zones are relevant to your entries, exits, and profit targets.
Practical applications for non-options traders:
- Profit targets: If price is approaching core resistance with heavy call Gamma above, there’s high probability of a reversal or slowdown at that level. This is a natural profit target for long directional trades.
- Stop placement: If put support is clearly defined below current price, placing stops just below that level accounts for the market maker dynamics that will be defending it.
- Regime assessment: The overall balance of call vs. put Gamma tells you whether the options market is positioned bullishly or bearishly. A net call-heavy positioning environment has different mean-reversion characteristics than a net put-heavy one.
- Daily range estimation: The One Day Expected Move levels give you a statistically validated intraday range. Knowing whether you’re in a high-volatility or low-volatility day changes which strategies make sense to run.
The Swing Trading Model
At the time of recording, MentorQ was launching a five-to-twenty day swing trading model for traders who don’t want to monitor intraday. This model uses machine learning incorporating momentum, options data, gamma, and delta to forecast upper and lower price bands over the next five to twenty days, along with a “risk trigger” level where a volatility breakout is likely to originate.
The backtested success rates on this model were comparable to the intraday model, suggesting the options flow signal has predictive value across multiple timeframes.
Platform Access and Asset Coverage
MentorQ covers approximately 1,000 assets – the US stocks with the highest options activity, plus major index and commodity futures (including gold, copper, forex futures like AUD/USD). Data is available through Discord with a bot interface and has been integrated into TradingView, NinjaTrader, and MetaTrader as indicator overlays that plot the reaction zones directly on the chart. The platform URL is mentorq.com.
Get the show notes & transcript
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