SGDJ and SILJ represent targeted vehicles for investors seeking exposure to junior precious metals miners, a volatile segment sensitive to commodity cycles, interest rates, and macroeconomic conditions. Rather than competing directly, these ETFs provide differentiated strategies within the same thematic universe: one centered on gold and the other on silver. This comparison highlights structural distinctions that can help investors align allocations with specific commodity views or risk tolerances amid evolving market environments.
The Sprott Junior Gold Miners ETF (SGDJ) is a passive exchange-traded fund that seeks to replicate the performance of the Solactive Junior Gold Miners Custom Factors Index before fees and expenses. It holds approximately 30 equity securities focused on small- and mid-cap gold mining companies, primarily in North America and Australia. The top holdings typically account for around 45% of assets, with concentrations in established junior producers and developers. The fund maintains full exposure to the materials sector and charges a net expense ratio of 0.50%. As a non-diversified, index-tracking vehicle issued by Sprott, SGDJ emphasizes cost efficiency and precise replication of its custom factors-based benchmark through periodic rebalancing aligned with index methodology.
The Amplify Junior Silver Miners ETF (SILJ) is a passive exchange-traded fund designed to track the Nasdaq Junior Silver Miners Index before fees and expenses. It comprises 54 to 70 holdings of small- and mid-cap companies engaged in silver mining, exploration, and development globally. Top holdings represent roughly 55% of assets, spread across pure-play silver producers and explorers. The ETF allocates nearly all assets to the materials sector and carries a net expense ratio of 0.69%. Issued by Amplify, SILJ operates as a non-diversified index fund with rebalancing conducted according to its underlying index rules to maintain targeted exposure.
The junior precious metals mining sector remains influenced by gold and silver price trajectories, driven by inflation expectations, central bank policies, geopolitical tensions, and industrial demand for silver in solar and electronics applications. Capital flows into mining equities often accelerate during periods of monetary easing or heightened uncertainty, while regulatory developments around permitting and environmental standards can affect project timelines. Both ETFs operate in a high-beta environment where operational leverage at mining companies amplifies commodity moves, exposing investors to company-specific execution risks alongside broader macro shifts. Recent market cycles have underscored the sector's sensitivity to real interest rates and currency fluctuations.
In recent market cycles, SGDJ has delivered exposure tied closely to gold price movements, benefiting from its concentrated holdings and lower expense drag that can enhance net returns during favorable periods. SILJ has provided broader participation across the silver complex, potentially capturing upside from industrial demand but also facing greater dispersion among holdings. Relative positioning reflects commodity divergences: gold-focused SGDJ may exhibit steadier trend consistency in certain environments, while SILJ's larger number of holdings supports diversification within silver juniors. Volatility differences stem from the underlying metals' distinct drivers, with both ETFs remaining sensitive to sector rotation and earnings cycles at top holdings rather than isolated events.
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Based on observable structural factors, Tickeron’s AI would currently assign a modest edge to SGDJ due to its lower expense ratio, more concentrated yet targeted gold exposure, and potentially tighter tracking efficiency. SILJ offers compelling breadth in the silver segment and strong liquidity, which could favor it under scenarios of silver outperformance. The probabilistic assessment favors SGDJ for cost-conscious investors seeking gold-centric positioning, while both remain viable depending on individual commodity outlooks and risk parameters.
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| SGDJ | SILJ | SGDJ / SILJ | |
| Gain YTD | 20.409 | 15.396 | 133% |
| Net Assets | 377M | 4.22B | 9% |
| Total Expense Ratio | 0.50 | 0.69 | 72% |
| Turnover | 76.00 | 47.00 | 162% |
| Yield | 9.55 | 2.30 | 415% |
| Fund Existence | 11 years | 14 years | - |
| SGDJ | SILJ | |
|---|---|---|
| RSI ODDS (%) | 3 days ago 90% | 3 days ago 90% |
| Stochastic ODDS (%) | 3 days ago 85% | 3 days ago 90% |
| Momentum ODDS (%) | 3 days ago 84% | 3 days ago 87% |
| MACD ODDS (%) | 3 days ago 90% | 4 days ago 90% |
| TrendWeek ODDS (%) | 3 days ago 90% | 3 days ago 90% |
| TrendMonth ODDS (%) | 3 days ago 90% | 3 days ago 90% |
| Advances ODDS (%) | 3 days ago 90% | 3 days ago 90% |
| Declines ODDS (%) | 26 days ago 86% | 26 days ago 89% |
| BollingerBands ODDS (%) | 3 days ago 86% | 3 days ago 90% |
| Aroon ODDS (%) | 3 days ago 90% | 3 days ago 89% |
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A.I.dvisor indicates that over the last year, SGDJ has been closely correlated with SA. These tickers have moved in lockstep 86% of the time. This A.I.-generated data suggests there is a high statistical probability that if SGDJ jumps, then SA could also see price increases.
| Ticker / NAME | Correlation To SGDJ | 1D Price Change % | ||
|---|---|---|---|---|
| SGDJ | 100% | +2.20% | ||
| SA - SGDJ | 86% Closely correlated | -9.35% | ||
| EQX - SGDJ | 85% Closely correlated | +5.05% | ||
| SKE - SGDJ | 84% Closely correlated | +0.11% | ||
| DRD - SGDJ | 84% Closely correlated | +4.03% | ||
| CDE - SGDJ | 83% Closely correlated | -0.66% | ||
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A.I.dvisor indicates that over the last year, SILJ has been closely correlated with PAAS. These tickers have moved in lockstep 93% of the time. This A.I.-generated data suggests there is a high statistical probability that if SILJ jumps, then PAAS could also see price increases.
| Ticker / NAME | Correlation To SILJ | 1D Price Change % | ||
|---|---|---|---|---|
| SILJ | 100% | +0.95% | ||
| PAAS - SILJ | 93% Closely correlated | +2.21% | ||
| CDE - SILJ | 91% Closely correlated | -0.66% | ||
| WPM - SILJ | 91% Closely correlated | +5.01% | ||
| SKE - SILJ | 88% Closely correlated | +0.11% | ||
| OR - SILJ | 87% Closely correlated | +2.27% | ||
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