iShares Silver Trust (SLV) 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.

iShares Silver Trust (SLV) operates in the Financial Services sector, specifically the Asset Management industry, with a market capitalization near $36.95B, listed on AMEX, carrying a beta of 0.98 to the broader market. The iShares Silver Trust (the 'Trust') seeks to reflect generally the performance of the price of silver. public since 2006-04-28.

Snapshot as of May 29, 2026.

Spot Price
$68.38
ATM IV
43.8%
IV Rank
24.8%
IV Percentile
50.4%
HV 20-Day
56.4%
IV Skew 25Δ
-0.034

As of May 29, 2026, iShares Silver Trust (SLV) at $68.38 has an ATM IV of 43.8%, implying a 30-day one-standard-deviation range of approximately ±$8.59. IV rank is 24.8% (subdued, distribution priced tighter than usual). IV percentile is 50.4%. The 25-delta skew is -0.034: downside tail priced richer than upside, biasing probability mass below 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 SLV probability analysis Data Feeds Strategy Selection

Strategy selection on iShares Silver Trust 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 43.8% 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 SLV probability distribution

The probability cone above is the option-market-implied distribution of where iShares Silver Trust 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 43.8% and spot at $68.38, the 1σ band is approximately ±15.1% over a 30-day horizon. Recent realized HV-20 of 56.4% runs 12.6 vol points above current implied, an inverted regime where premium buyers are underpaying.

SLV 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. SLV's put-skewed 25-delta surface (-0.034) means downside risk-neutral probabilities are higher than upside - the empirical bias is well-documented. 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 SLV 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. With SLV IV rank at 24.8%, the chain is pricing tighter tails than recent realized history; buyers get cheaper optionality but need a real catalyst to monetize. 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 →

SLV implied volatility by strike, top contracts ranked by IV in the nightly options scanSLV Implied Volatility Skew (Top Contracts)44%46%48%50%$70$72$74$76$78$80Strike ($)Implied Volatility
Chart aggregates top-ranked contracts by strike from the institutional-grade nightly options scan. Sparse coverage on long-tail tickers reflects the scan's S&P 500/400/600 + ETF focus.

SLV highest implied-volatility contracts

TypeStrikeExpirationVolumeOIIVBidAsk
CALL$69.00Jun 5, 202647.2K3.7K43.1%$1.34$1.38
CALL$80.00Jun 18, 202626.3K101.0K50.9%$0.40$0.41
CALL$72.50Jun 3, 20264.1K23142.6%$0.20$0.23
PUT$64.00Jul 2, 20261.7K10143.8%$1.66$1.73
CALL$70.00Jun 18, 20262.6K112.4K43.9%$2.13$2.15

Top 5 contracts from the institutional-grade nightly options scan; ranked by iv within the broader S&P 500/400/600 + ETF universe.

Frequently asked SLV probability analysis questions

What is the SLV 30-day expected price range?
As of May 29, 2026, with SLV at $68.38 and ATM IV at 43.8%, the implied 30-day one-standard-deviation range is approximately ±$8.59, or about $59.79 to $76.97. IV rank is subdued, so the priced distribution is tighter than the 1-year typical width.
What does SLV risk-neutral density tell us?
Risk-neutral density is the probability distribution of future SLV 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 SLV 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.