Global X - U.S. 500 ETF (GXLC) 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.

Global X - U.S. 500 ETF (GXLC) operates in the Financial Services sector, specifically the Asset Management - Global industry, with a market capitalization near $4.5M, listed on AMEX, carrying a beta of 1.01 to the broader market. The Global X U. Led by Sandy Lu, public since 2025-09-23.

Snapshot as of May 29, 2026.

Spot Price
$91.12
ATM IV
18.4%
IV Skew 25Δ
0.039

As of May 29, 2026, Global X - U.S. 500 ETF (GXLC) at $91.12 has an ATM IV of 18.4%, implying a 30-day one-standard-deviation range of approximately ±$4.81. The 25-delta skew is +0.039: upside tail priced richer than downside, biasing probability mass above spot. 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 GXLC probability analysis Data Feeds Strategy Selection

Strategy selection on Global X - U.S. 500 ETF 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 18.4% 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 GXLC probability distribution

The probability cone above is the option-market-implied distribution of where Global X - U.S. 500 ETF 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 18.4% and spot at $91.12, the 1σ band is approximately ±6.3% over a 30-day horizon.

GXLC 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 GXLC 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 GXLC probability analysis questions

What is the GXLC 30-day expected price range?
As of May 29, 2026, with GXLC at $91.12 and ATM IV at 18.4%, the implied 30-day one-standard-deviation range is approximately ±$4.81, or about $86.31 to $95.93.
What does GXLC risk-neutral density tell us?
Risk-neutral density is the probability distribution of future GXLC 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 GXLC 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.