etf hidden cost comparator

    1

    Analyze ETFs beyond the expense ratio to uncover hidden costs like tracking error, spreads, and tax leakage.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLI+17 more

    See it in action

    You say

    Compare VTI and ITOT for a 5-year buy and hold strategy. Focus on all-in costs.

    Your agent does

    | Metric | VTI | ITOT | |---|---|---| | TER | 0.03% | 0.03% | | Tracking Error | 0.01% | 0.02% | | Median Spread | 0.01% | 0.02% | | Volume | ~$1.5B/day | ~$500M/day | Conclusion: Both are top-tier. VTI has a slight edge in liquidity and tracking precision, but the 0.01% difference is negligible for most retail portfolios.

    What you get

    Identify the lowest total cost of ownership between similar index funds.Quantify the impact of bid-ask spreads on short-term trading costs.Evaluate the risks of synthetic vs physical replication methods.Estimate dividend leakage for international vs US-domiciled funds.

    About this skill

    The problem

    Headline expense ratios (TER) rarely tell the full story of what an ETF actually costs you. Hidden factors like tracking error, wide bid-ask spreads, and dividend leakage can silently erode your returns, making a "cheap" fund more expensive than its competitors.

    What it does

    • Analyzes 7 critical cost dimensions including TER, tracking error, and bid-ask spreads.
    • Evaluates structural risks such as physical versus synthetic replication methods.
    • Estimates dividend leakage based on fund domicile and distribution policies.
    • Generates a normalized comparison table to visualize all-in costs.
    • Calculates total cost of ownership estimates based on holding periods.

    Why this beats prompting it yourself

    Generic prompts often miss technical nuances like annualized spread costs or the counterparty risk of synthetic replication. This skill enforces a structured forensic audit that accounts for slippage and tax efficiency, ensuring you don't overlook technical drag that simple GPT prompts ignore.

    Use cases

    • Compare two ETFs tracking the same index to find the most efficient vehicle.
    • Evaluate if switching funds is worth the trade costs and tax implications.
    • Audit a portfolio for synthetic replication or low-liquidity risks.
    • Assess the impact of dividend withholding taxes on international holdings.

    Known limitations

    Calculations depend on the availability of recent prospectus and exchange data. Tracking error is backward-looking and spreads can spike during periods of high market volatility.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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