What is the Q 30-day expected price range?

As of May 29, 2026, with Q at $156.15 and ATM IV at 60.6%, the implied 30-day one-standard-deviation range is approximately ±$27.13, or about $129.02 to $183.28.

What does Q risk-neutral density tell us?

Risk-neutral density is the probability distribution of future Q price implied by listed option prices. Extracted via Breeden-Litzenberger (twice-differentiating the call price function with respect to strike), it represents the pricing kernel rather than the real-world probability of outcomes. Persistent skew or fat-tail features in the density reflect how the market is pricing tail risk.

How does Q ATM IV translate to a probability range?

ATM IV is annualized; multiplying by sqrt(t/365) scales it to the chosen tenor. Under lognormal assumptions, the resulting standard deviation defines the ±1σ band that contains roughly 68% of outcomes, ±2σ for 95%. Empirical equity returns have fatter tails than log-normal, so the implied tail probabilities under-state realized tail frequency in stressed regimes.

Qnity Electronics, Inc. (Q) Probability Analysis

Probability analysis extracts the risk-neutral probability distribution implied by option prices. It shows the market-implied likelihood of the underlying reaching various price levels by expiration.

Qnity Electronics, Inc. (Q) operates in the Technology sector, specifically the Semiconductors industry, with a market capitalization near $33.31B, listed on NYSE, employing roughly 10,000 people, carrying a beta of 1.68 to the broader market. Qnity Electronics, Inc. Led by Jon D. Kemp, public since 2025-10-27.

Snapshot as of May 29, 2026.

Spot Price: $156.15
ATM IV: 60.6%
IV Rank: 42.2%
IV Percentile: 78.2%
HV 20-Day: 58.1%
IV Skew 25Δ: 0.001

As of May 29, 2026, Qnity Electronics, Inc. (Q) at $156.15 has an ATM IV of 60.6%, implying a 30-day one-standard-deviation range of approximately ±$27.13. IV rank is 42.2% (near its 1-year median). IV percentile is 78.2%. The 25-delta skew is +0.001: roughly symmetric wings. Under lognormal assumptions roughly 68% of outcomes fall within ±1σ and 95% within ±2σ; risk-neutral probability analysis refines this by extracting the market-implied distribution directly from options prices, capturing the fat tails that real markets exhibit.

How Q probability analysis Data Feeds Strategy Selection

Strategy selection on Qnity Electronics, Inc. options does not derive from any single metric in isolation. The probability analysis view above sits inside a broader read: ATM IV currently sits at 60.6% and dealer gamma exposure is positive, so dealer hedging is mechanically mean-reverting. Combine the probability analysis data here with the volatility-skew surface, dealer-gamma exposure, max-pain level, and upcoming-events calendar to build a positioning thesis. Risk-defined structures (credit spreads, debit spreads, iron condors) are usually safer than naked positions while the regime is uncertain; the data on this page anchors the inputs but does not by itself constitute a trade thesis.

How to read the Q probability distribution

The probability cone above is the option-market-implied distribution of where Qnity Electronics, Inc. spot could end up at expiration. It's derived from the implied-volatility surface via a risk-neutral pricing transformation, not from historical realized returns. With ATM IV at 60.6% and spot at $156.15, the 1σ band is approximately ±20.9% over a 30-day horizon. Recent realized HV-20 of 58.1% runs 2.5 vol points below the current implied, suggesting the chain is pricing more dispersion than the underlying has been delivering.

Q risk-neutral vs real-world probabilities

The probabilities derived from option prices reflect the market's risk-adjusted view, not the realized statistical distribution. Risk-neutral probabilities include the equity risk premium and skew preferences priced into options, so they tend to overstate tail probability and understate upside drift relative to actually-realized outcomes. For probability-of-touch calculations and assignment-risk modeling, risk-neutral is the right benchmark. For position-sizing your own conviction, blend with realized-volatility-based statistics from the HV columns.

Trading the Q distribution

Probability-driven strategies aim to capture mispricings between the implied distribution and your own probability assessment. Premium-selling structures (credit spreads, iron condors, cash-secured puts) profit when the implied distribution overprices tail probability relative to realized; premium-buying (debit spreads, long calls/puts, long straddles) profits in the reverse. Always pair probability-driven strategy selection with a stop loss or wing-defined risk - the implied distribution is a snapshot, and regime shifts can invalidate it intraday.

Learn how risk-neutral density is reported and how to read the data →

Frequently asked Q probability analysis questions

What is the Q 30-day expected price range?: As of May 29, 2026, with Q at $156.15 and ATM IV at 60.6%, the implied 30-day one-standard-deviation range is approximately ±$27.13, or about $129.02 to $183.28.
What does Q risk-neutral density tell us?: Risk-neutral density is the probability distribution of future Q price implied by listed option prices. Extracted via Breeden-Litzenberger (twice-differentiating the call price function with respect to strike), it represents the pricing kernel rather than the real-world probability of outcomes. Persistent skew or fat-tail features in the density reflect how the market is pricing tail risk.
How does Q ATM IV translate to a probability range?: ATM IV is annualized; multiplying by sqrt(t/365) scales it to the chosen tenor. Under lognormal assumptions, the resulting standard deviation defines the ±1σ band that contains roughly 68% of outcomes, ±2σ for 95%. Empirical equity returns have fatter tails than log-normal, so the implied tail probabilities under-state realized tail frequency in stressed regimes.