historical gold and silver seasonality with interactive charts, monthly price trends, and year-by-year comparisons
Compare how gold and silver monthly average prices changed across the calendar year.
Silver · 2006–2025 · 20 observations per calendar month
Gold & silver seasonality
Silver · Average monthly change (%)
Changes between monthly average prices, in USD. Historical patterns are not forecasts or monthly closing-price returns.
Enable JavaScript for the interactive chart. The statistics and tables below remain available.
2026 is shown separately below and excluded from the complete-year baseline.
Monthly statistics Average, median & positive cases
| Month | Average | Median | Positive cases | Lowest | Highest |
|---|---|---|---|---|---|
| January | +2.42% | +2.38% | 14 / 20 (70%) | −4.18% | +11.19% |
| February | +3.33% | +4.46% | 13 / 20 (65%) | −10.17% | +18.58% |
| March | +0.81% | −0.54% | 9 / 20 (45%) | −16.76% | +16.23% |
| April | +2.22% | +0.61% | 12 / 20 (60%) | −11.81% | +21.15% |
| May | −0.69% | −1.32% | 9 / 20 (45%) | −12.65% | +12.00% |
| June | −0.62% | 0.00% | 9 / 20 (45%) | −19.40% | +9.76% |
| July | +0.68% | −0.43% | 10 / 20 (50%) | −11.57% | +16.38% |
| August | +1.94% | +1.77% | 11 / 20 (55%) | −18.89% | +31.07% |
| September | +1.21% | −0.85% | 9 / 20 (45%) | −15.07% | +16.67% |
| October | −0.32% | −1.02% | 9 / 20 (45%) | −16.23% | +15.42% |
| November | +1.09% | +0.09% | 10 / 20 (50%) | −8.23% | +13.25% |
| December | +1.01% | −0.77% | 9 / 20 (45%) | −8.46% | +23.61% |
Positive cases count changes strictly above zero. Flat months remain in the denominator. Counts describe this historical sample, not future probabilities.
Year-by-year monthly changes Explore the heatmap
Scroll sideways to see all months. Select a cell to inspect that calendar month.
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
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2026 so far Separate from the baseline
Published months of the incomplete year. Missing months are not estimated. These observations are excluded from all baseline statistics.
| Month | Latest year | Baseline average | Baseline median |
|---|---|---|---|
| January | +47.83% | +2.42% | +2.38% |
| February | −11.07% | +3.33% | +4.46% |
| March | −4.88% | +0.81% | −0.54% |
| April | −2.57% | +2.22% | +0.61% |
| May | +2.77% | −0.69% | −1.32% |
| June | −14.49% | −0.62% | 0.00% |
| July | −11.84% | +0.68% | −0.43% |
| August | +11.22% | +1.94% | +1.77% |
| September | −1.22% | +1.21% | −0.85% |
| October | −11.76% | −0.32% | −1.02% |
| November | Not published | +1.09% | +0.09% |
| December | Not published | +1.01% | −0.77% |
Methodology, sources & limitations
Observation basis. Nominal USD per troy ounce, monthly averages from the World Bank Pink Sheet. Analysis starts January 1971; December 1970 is retained solely to calculate January 1971’s change. No daily prices, live quotes or monthly closing prices are mixed into this series.
Monthly change. 100 × (this month’s average ÷ previous month’s average − 1). January is compared with the previous December. These are changes in monthly averages, not executable investment returns. Early source rounding can produce flat months and affect small changes.
Comparable years. The baseline uses the latest 10, 20 or all complete January–December years with twelve calculable changes. Every calendar month uses the same years. The newest incomplete year is shown separately. A period ending in September therefore does not add extra January–September observations to the baseline.
Statistics. Average is the arithmetic mean; median is the middle sorted observation (the mean of the two middle observations for an even sample). Positive cases are the count of changes above zero divided by all observations, including flat months. A tolerance of 0.0000000001 percentage points treats numerical rounding noise as zero. Highest/lowest cards rank the selected average or median and disclose ties. Extremes and positive counts are descriptive sample statistics, not forecasts or calibrated probabilities. Outliers, source revisions and the selected period can change the pattern.
Source definitions. Gold is described as a spot average of daily rates from June 2025, previously the London afternoon fixing average. Silver is described as London afternoon fixing for 99.9%-refined silver, with Handy & Harman before July 1976. This source-method change is retained in the historical series.
Underlying providers. Gold: Bloomberg Finance L.P.; Kitco.com; IMF International Financial Statistics; London Bullion Market; Metals Week; Platts Metals Week; Shearson Lehman Brothers, Metal Market Weekly Review; Thomson Reuters Datastream; World Bank. Silver: American Metal Market; Australian Mineral Economics; Bloomberg Finance L.P.; London Bullion Market; Metals Week; Metals Statistics; Platts Metals Week; The Silver Institute; Thomson Reuters Datastream; World Bank.
Licence. The dataset catalogue lists CC BY 4.0, subject to World Bank Dataset Terms and applicable third-party exceptions. Source data are extracted into a reduced dataset; statistics and graphics are calculated by Silver Dominion. Preserve source, provider and licence attribution when reusing exports. No affiliation or endorsement by World Bank or its providers is implied.
Coverage and updates. Source publication: 2026-11-03. Snapshot retrieved: 2026-11-05. Latest observation: Oct 2026. Last successful source check: 2026-11-05 08:54 UTC. Shared server checks run daily through WordPress scheduled tasks. Source observations are normally released monthly. Failed or incomplete downloads retain the last verified history; visits do not trigger provider downloads.
Prices exclude inflation, currency changes, bullion premiums, taxes and transaction costs. A seasonal pattern alone does not establish the best time to buy or sell. The default statistics, tables and methodology are readable without JavaScript; interactive charts, filters and exports require JavaScript.
Understanding Gold and Silver Seasonal Patterns
Gold and silver seasonality shows how precious metals have historically performed during different months of the year. Some months have experienced stronger average returns, while others have shown weaker performance or more frequent declines.
Studying these patterns helps investors identify recurring trends, compare monthly performance, and better understand long-term price behavior.
However, seasonal tendencies can change over time and do not guarantee future returns.
How to Use the Gold & Silver Seasonality Explorer
The Gold & Silver Seasonality Explorer provides interactive charts, historical monthly returns, and year-by-year comparisons.
Investors can examine average and median monthly changes, compare gold and silver performance, and explore whether seasonal patterns have remained consistent across different periods.
Comparing multiple years also helps reveal whether unusually strong or weak market conditions have influenced historical averages.
Historical Data and Seasonal Market Trends
The explorer uses monthly average gold and silver prices from the World Bank, with historical data beginning in 1971. Monthly percentage changes are calculated using consecutive monthly averages rather than month-end closing prices.
Average and median returns help distinguish recurring tendencies from unusually large price movements.
Seasonal patterns can be influenced by interest rates, inflation, currency movements, industrial demand, and investor sentiment.
For additional market context, explore the Gold & Silver COT Positioning Tracker or examine historical declines with the Gold & Silver Crash Recovery Tool.
Historical seasonality provides useful context but should not be treated as a reliable prediction of future prices.
Frequently Asked Questions
What is gold and silver seasonality?
Gold and silver seasonality refers to recurring patterns in precious metals prices during different months of the year. Historical monthly returns can reveal periods of stronger or weaker performance, but these patterns do not guarantee future results.
What is the best month to buy gold?
There is no consistently reliable best month to buy gold. Historical seasonal charts can identify months with weaker average price changes, but results vary across different periods. Interest rates, inflation, and investment demand can outweigh seasonal patterns.
Does silver follow the same seasonal patterns as gold?
Gold and silver can share seasonal tendencies, but their patterns are not identical. Silver is more sensitive to industrial demand, while gold is influenced more strongly by monetary conditions and safe-haven investment flows.
Where does the gold and silver seasonality data come from?
The explorer uses historical monthly average prices from the World Bank Commodity Price Data (Pink Sheet), beginning in January 1971. Prices are expressed in nominal U.S. dollars per troy ounce.
How are monthly gold and silver returns calculated?
Monthly percentage changes compare each month’s average price with the previous month’s average. These figures are not month-end investment returns. Historical averages and medians are calculated from the available complete years.
What is the difference between average and median seasonality?
Average seasonality measures the arithmetic mean of historical monthly changes. Median seasonality represents the middle observation. Comparing both helps identify whether unusually large price movements have distorted historical averages.
Can gold and silver seasonality predict future prices?
No. Seasonal patterns provide historical context but cannot reliably predict future gold or silver prices. Interest rates, monetary policy, currencies, industrial demand, and geopolitical events can outweigh seasonal tendencies.