Global X Gold Explorers ETF (GOEX) and Global X Silver Miners ETF (SIL) represent specialized vehicles for investors seeking equity exposure to precious metals without direct ownership of physical commodities. These ETFs do not compete head-to-head as substitutes but instead offer differentiated strategies within the mining and exploration universe. GOEX targets companies engaged in gold deposit identification and development, while SIL focuses on silver producers. In the current environment of fluctuating interest rates, evolving industrial silver demand, and gold’s role as a hedge, the pair allows investors to fine-tune exposure between exploration risk and established mining operations. The comparison highlights structural nuances that influence risk, diversification, and thematic alignment.
Global X Gold Explorers ETF (GOEX) is a passive, equity-based exchange-traded fund designed to track the Solactive Global Gold Explorers & Developers Total Return Index. The fund invests primarily in companies involved in gold exploration and development activities worldwide. It typically holds approximately 51 securities, providing diversified access across small- and mid-cap explorers. Sector allocation centers almost exclusively on basic materials, specifically precious metals. The expense ratio stands at 0.65%. As a thematic, market-capitalization-weighted passive vehicle, GOEX rebalances periodically in line with the underlying index methodology. Distinguishing features include its focus on earlier-stage companies, which can amplify sensitivity to discovery news and gold price movements compared with more mature mining operations.
Global X Silver Miners ETF (SIL) is a passive, equity-based exchange-traded fund that seeks to replicate the performance of the Solactive Global Silver Miners Total Return Index. The strategy targets companies actively engaged in silver mining and related operations. The fund typically maintains around 39 holdings, resulting in a more concentrated portfolio than many broad equity ETFs. Allocation is overwhelmingly to the basic materials sector, with silver miners as the core exposure. The expense ratio is 0.65%. SIL employs standard index-based rebalancing and offers investors a pure-play vehicle for silver equity exposure. Key structural characteristics include greater weighting toward established producers, which may provide relatively more stable cash flows but still carries significant commodity and operational risks.
The precious metals mining sector operates at the intersection of monetary demand for gold as a store of value and industrial applications for silver, particularly in solar energy, electronics, and electric vehicles. Macro drivers include interest rate expectations, inflation trends, and geopolitical uncertainty, all of which influence capital flows into the space. Regulatory developments around mining permits and environmental standards can affect project timelines for explorers and producers alike. Silver benefits from dual demand dynamics, while gold exploration remains more sensitive to price rallies that justify higher-risk drilling programs. Sector risks encompass commodity price volatility, rising operating costs, and jurisdiction-specific political factors. These elements shape the broader environment in which both ETFs operate, creating opportunities and challenges tied to commodity cycles rather than single-quarter events.
In recent market cycles, both ETFs have demonstrated sensitivity to precious metals price movements and sector rotation patterns. GOEX’s emphasis on explorers can lead to amplified upside during gold price surges driven by discovery announcements or macroeconomic hedging demand, though it may also experience sharper drawdowns in risk-off periods. SIL’s positioning toward established silver miners tends to reflect a blend of monetary and industrial silver demand, potentially offering somewhat different volatility characteristics during periods of strong solar or electronics sector growth. Relative positioning highlights GOEX’s higher-beta profile to gold price changes versus SIL’s exposure to silver’s industrial component. Over broader timeframes, differences in holdings concentration and company stage contribute to distinct risk-adjusted return profiles, with neither fund intended for short-term trading but rather for thematic allocation within diversified portfolios.
Tickeron’s AI Screener is an AI-powered stock and ETF discovery tool that helps traders and investors filter the market based on technical patterns, fundamentals, trends, volatility, and AI-driven signals. Users can scan thousands of stocks and ETFs using customizable filters such as industry, market capitalization, technical indicators, price patterns, and performance metrics. The screener helps identify trade ideas, trending stocks, breakout candidates, and market opportunities more efficiently than manual screening. Investors seeking data-driven insights into funds like Global X Gold Explorers ETF (GOEX) or Global X Silver Miners ETF (SIL) may find the platform useful for refining their research process.
Based on observable structural factors including identical expense ratios, diversification breadth, and liquidity profiles, Tickeron’s AI would currently assign a modest probabilistic edge to Global X Silver Miners ETF (SIL) due to its larger scale, established miner focus, and potentially more balanced exposure to both monetary and industrial silver demand. Global X Gold Explorers ETF (GOEX) remains a compelling alternative for investors prioritizing exploration upside within the gold theme. Selection ultimately depends on individual risk tolerance and portfolio objectives.
The information on this webpage is provided for general informational and educational purposes only and is not intended as investment advice, a recommendation to purchase or sell any security, or an offer or solicitation related to investments. It does not consider your personal financial situation, goals, or risk profile, and all investing carries inherent risks, including the possibility of losing your entire investment. For more details, please review our full disclaimer.
| GOEX | SIL | GOEX / SIL | |
| Gain YTD | 19.499 | 19.357 | 101% |
| Net Assets | 145M | 5.43B | 3% |
| Total Expense Ratio | 0.65 | 0.65 | 100% |
| Turnover | 27.01 | 27.57 | 98% |
| Yield | 2.57 | 1.38 | 187% |
| Fund Existence | 16 years | 16 years | - |
| GOEX | SIL | |
|---|---|---|
| RSI ODDS (%) | 3 days ago 90% | 3 days ago 90% |
| Stochastic ODDS (%) | 3 days ago 88% | 3 days ago 89% |
| Momentum ODDS (%) | 3 days ago 85% | 3 days ago 90% |
| MACD ODDS (%) | 4 days ago 90% | 4 days ago 90% |
| TrendWeek ODDS (%) | 3 days ago 90% | 3 days ago 90% |
| TrendMonth ODDS (%) | 3 days ago 89% | 3 days ago 90% |
| Advances ODDS (%) | 3 days ago 89% | 3 days ago 90% |
| Declines ODDS (%) | 26 days ago 85% | 26 days ago 87% |
| BollingerBands ODDS (%) | 3 days ago 87% | 3 days ago 89% |
| Aroon ODDS (%) | 3 days ago 89% | 3 days ago 89% |
A.I.dvisor indicates that over the last year, GOEX has been closely correlated with EQX. These tickers have moved in lockstep 85% of the time. This A.I.-generated data suggests there is a high statistical probability that if GOEX jumps, then EQX could also see price increases.
| Ticker / NAME | Correlation To GOEX | 1D Price Change % | ||
|---|---|---|---|---|
| GOEX | 100% | +3.11% | ||
| EQX - GOEX | 85% Closely correlated | +5.05% | ||
| AGI - GOEX | 84% Closely correlated | +3.19% | ||
| DRD - GOEX | 82% Closely correlated | +4.03% | ||
| SKE - GOEX | 81% Closely correlated | +0.11% | ||
| CDE - GOEX | 80% Closely correlated | -0.66% | ||
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A.I.dvisor indicates that over the last year, SIL has been closely correlated with PAAS. These tickers have moved in lockstep 95% of the time. This A.I.-generated data suggests there is a high statistical probability that if SIL jumps, then PAAS could also see price increases.
| Ticker / NAME | Correlation To SIL | 1D Price Change % | ||
|---|---|---|---|---|
| SIL | 100% | +2.14% | ||
| PAAS - SIL | 95% Closely correlated | +2.21% | ||
| WPM - SIL | 94% Closely correlated | +5.01% | ||
| CDE - SIL | 91% Closely correlated | -0.66% | ||
| OR - SIL | 89% Closely correlated | +2.27% | ||
| VZLA - SIL | 82% Closely correlated | +2.33% | ||
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