ETF Comparison Analyzer
يستخدم المستثمرون الأفراد والمستشارون الماليون هذا الموجه عند الاختيار بين صندوقَي مؤشر أو أكثر يبدو أنها تغطي نفس شريحة السوق. يكشف الفروق الجوهرية في التكلفة وجودة التتبع والتركيز والسيولة التي تخفيها المواد التسويقية.
الأوامر
You are an ETF analyst helping a [INVESTOR PROFILE] evaluate and compare exchange-traded funds. I want to compare the following ETFs: [ETF TICKERS]. My primary investment goal is [INVESTMENT GOAL] with a [TIME HORIZON] time horizon. For each ETF provided, research or use the data below to analyze the following dimensions: ETF Data: [ETF DATA — expense ratios, AUM, inception date, benchmark index, sector weights, holdings] 1. **Cost Analysis** Compare expense ratios across all ETFs. Calculate the cumulative cost drag over [TIME HORIZON] on a $[INVESTMENT AMOUNT] investment assuming 7% annual gross return. Flag any hidden costs — bid-ask spreads, securities lending income offset, or tax inefficiency. 2. **Tracking Quality** Assess benchmark tracking error over the most recent three-year period. Note the tracking difference (annual return versus index) as distinct from tracking error (volatility of that gap). Identify which ETF has been most faithful to its benchmark. 3. **Portfolio Concentration and Overlap** List the top-ten holdings of each ETF and calculate overlap percentage between funds. Flag any ETFs where the top-ten holdings represent more than 40% of total assets. Identify concentration risk at the single-stock or single-sector level. 4. **Sector and Geographic Exposure** Build a side-by-side sector allocation table. For international ETFs, include regional breakdown. Note any significant tilt toward cyclical sectors, defensive sectors, or factor exposures (value, growth, momentum, quality). 5. **Liquidity Assessment** Compare average daily trading volume and AUM. Flag any ETF with AUM below $500 million as a potential liquidity or closure risk. Assess bid-ask spreads as a transaction cost for the expected trade size. 6. **Historical Performance Context** Present annualized total returns for one, three, and five-year periods alongside the stated benchmark. Note performance gaps and any periods of significant underperformance. Remind the reader that past performance is not a guarantee of future results. 7. **Best-Fit Recommendation** Based on all dimensions above, recommend the single best ETF for [INVESTOR PROFILE] pursuing [INVESTMENT GOAL]. Justify the choice in three sentences covering cost, quality, and fit. Flag if a two-ETF combination would better serve the investor's goal. Format the core analysis as comparison tables where possible. Write the recommendation section in plain prose.
متغيرات الأمر
استبدل كل عنصر نائب بمعلوماتك الخاصة:
[INVESTOR PROFILE][ETF TICKERS][INVESTMENT GOAL][TIME HORIZON][ETF DATA — expense ratios, AUM, inception date, benchmark index, sector weights, holdings][INVESTMENT AMOUNT]ما ستحصل عليه
حسابات مقارنة للتكلفة التراكمية على أفق الاستثمار وتحليل خطأ التتبع وفجوة التتبع وتحليل تداخل المحتويات مع إشارات التركيز وجدول تخصيص القطاعات وتقييم السيولة وملخص الأداء التاريخي وتوصية بأفضل صندوق مع المبرر.
💡 نصيحة خبير
كرر هذه المقارنة سنويًا — تخفض شركات إدارة صناديق المؤشرات نسب المصاريف دوريًا أو تغير منهجيات المؤشرات. قد يكون الصندوق الأمثل قبل ثلاث سنوات قد تجاوزه منافس أرخص يتتبع مؤشرًا مطابقًا.
أدوات الذكاء الاصطناعي المتوافقة
Claude
Ideal for structured comparison tables and nuanced best-fit reasoning. Paste ETF fact sheet data or holdings lists directly. Claude handles up to five or six ETFs simultaneously and produces well-organized comparison output.
ChatGPT
GPT-4o with browsing can fetch current expense ratios and holdings for major ETFs. Use Data Analysis to run the cost-drag calculation and produce formatted tables. Works best when you provide tickers and ask it to pull its own data.
Perplexity
Best for sourcing current ETF data before running the comparison. Ask Perplexity for the latest expense ratio, AUM, top holdings, and sector weights for each ticker, then feed those figures to Claude or ChatGPT for the structured analysis.
Gemini
Useful when ETF data is stored in a Google Sheet. Gemini can reference the sheet and run the comparison in context. Its built-in Search grounding helps verify AUM and performance data for lesser-known ETFs.