ETF Comparison: SCHX vs SCHA
ETF 說明
SCHX - Schwab U.S. Large-Cap ETF
The Schwab U.S. Large-Cap ETF tracks the Dow Jones U.S. Large-Cap Total Stock Market Index, providing broad exposure to large-cap stocks in the American market. The fund holds a diversified portfolio of over 750 securities, including well-known companies such as ExxonMobil, Apple, IBM, and GE. With a low expense ratio, this ETF is an excellent choice for investors seeking cost-effective, long-term exposure to the U.S. large-cap market.
SCHA - Schwab U.S. Small-Cap ETF
The Schwab U.S. Small-Cap ETF (SCHA) tracks the Dow Jones U.S. Small-Cap Total Stock Market Total Return Index, providing diversified exposure to small-cap companies in the U.S. equity market. The fund's broad focus on both value and growth securities aims to capture the growth potential of small-cap firms while mitigating volatility. With a low expense ratio and a large number of holdings, SCHA offers a cost-effective way to add small-cap exposure to a portfolio.
比較表
| SCHX | SCHA | |
|---|---|---|
| 基金名稱 | Schwab U.S. Large-Cap ETF | Schwab U.S. Small-Cap ETF |
| Fund Provider | Charles Schwab | Charles Schwab |
| Index | Dow Jones U.S. Large-Cap Total Stock Market Index | Dow Jones U.S. Small-Cap Total Stock Market Total Return Index |
| Asset Class | Equity | Equity |
| Listing | US-listed | US-listed |
| Expense Ratio | 0.03% | 0.04% |
| Inception Date | 2009-11-03 | 2009-11-03 |
| Number Of Holdings | 751 | 1727 |
| Region | United States | United States |
| Investment Style | Blend | Blend |
| Market Cap | Large-Cap | Small-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。