ETF Comparison: SLYG vs PGF
ETF 說明
SLYG - SPDR S&P 600 Small Cap Growth ETF
The SPDR S&P 600 Small Cap Growth ETF (SLYG) tracks the S&P SmallCap 600 Growth Index, providing exposure to small-cap companies in the US equity market that exhibit growth characteristics. The fund offers a diversified portfolio of approximately 348 holdings, with a focus on growth securities and a market capitalization bias towards micro-caps. With a low expense ratio, SLYG can be a quality addition to portfolios seeking small-cap growth exposure.
PGF - Invesco Financial Preferred ETF
The Invesco Financial Preferred ETF (PGF) provides investors with exposure to preferred stocks in the financial sector, offering a unique combination of relatively stable income and lower volatility compared to common stocks. The fund's concentrated portfolio of 95 holdings is focused on the US financial sector, making it suitable for investors seeking to boost yields in their portfolio or reduce risk while maintaining some equity exposure.
比較表
| SLYG | PGF | |
|---|---|---|
| 基金名稱 | SPDR S&P 600 Small Cap Growth ETF | Invesco Financial Preferred ETF |
| Fund Provider | State Street | Invesco |
| Index | S&P SmallCap 600 Growth Index | ICE Bofa Exchange-Listed Fixed Rate Financial Preferred Securities |
| Asset Class | Equity | Equity |
| Listing | US-listed | US-listed |
| Expense Ratio | 0.15% | 0.56% |
| Inception Date | 2000-09-25 | 2006-12-01 |
| Number Of Holdings | 348 | 95 |
| Currency | USD | USD |
| Region | United States | United States |
| Investment Style | Growth | Blend |
| Market Cap | Micro-Cap | Micro-Cap |
| 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。