ETF Comparison: FNCL vs IXG
ETF 說明
FNCL - Fidelity MSCI Financials Index ETF
The Fidelity MSCI Financials Index ETF (FNCL) provides exposure to the U.S. financial sector, offering a diversified portfolio of large-cap, mid-cap, and small-cap companies. This ETF is suitable for investors seeking to implement a tactical tilt or sector rotation strategy, and is competitively priced compared to its peers.
IXG - iShares Global Financials ETF
The iShares Global Financials ETF provides exposure to a broad range of financial companies globally, including banks, insurance companies, and other financial institutions. The fund tracks the S&P Global 1200 / Financials index, which is a market-capitalization-weighted index of large-cap financial stocks from developed markets. The ETF offers a convenient way to gain exposure to the global financial sector, making it suitable for investors seeking to diversify their portfolios or implement a sector rotation strategy.
比較表
| FNCL | IXG | |
|---|---|---|
| 基金名稱 | Fidelity MSCI Financials Index ETF | iShares Global Financials ETF |
| Fund Provider | Fidelity | BlackRock |
| Index | MSCI USA IMI Financials 25/50 Index | S&P Global 1200 / Financials -SEC |
| Asset Class | Equity | Equity |
| Listing | US-listed | US-listed |
| Expense Ratio | 0.08% | 0.42% |
| Inception Date | 2013-10-21 | 2001-11-12 |
| Number Of Holdings | 402 | 210 |
| Currency | USD | USD |
| Region | United States | Developed Markets |
| Investment Style | Blend | Blend |
| Market Cap | Large-Cap | Large-Cap |
| Sector | Financials | Financials |
| Sector Detail | Banks & Insurance | Banks & Insurance |
| Leveraged | Non-leveraged | Non-leveraged |
回測選項
摘要
關鍵指標
績效指標
風險指標
詳細報酬
績效分析
績效分析透過累積報酬、年底（EoY）報酬及 Sharpe 比率、Sortino 比率等風險調整指標，評估歷史資料以衡量投資策略報酬。這有助於投資人在不同市場條件下評估絕對和相對績效。
累積報酬
年底報酬表
年底報酬
風險分析
風險分析是指對可能導致資本損失的潛在負面事件進行評估。進行風險分析有助於決定是否應進行投資。這是透過回撤、波動率和 Beta 等風險指標來完成的，這些指標反映了利益相關者對投資策略一致性的信心。
回撤
回撤表
Monte Carlo 模擬
Monte Carlo 模擬是一種統計方法，透過從歷史資產價格資料中隨機抽樣產生大量潛在結果，用以預測投資組合報酬。它協助投資人評估各種市場條件下投資組合的潛在風險和報酬。模擬考慮初始投資，並可選擇性地模擬現金流情境，如固定投入、固定提款或比例提款。
重要提示：透過 Monte Carlo 模擬產生的預測純屬假設性質，不保證未來報酬。投資決策應考量多種因素，過去表現不代表未來結果。