Tax-loss harvesting

Tax-loss harvesting replacement finder workflow

Review harvestable losses, wash-sale warnings, and factor-matched replacement basket research without treating the result as tax advice.

Review saved lots, then compare replacement baskets by factor exposure and tracking error.

Start with one question

Explore the results

What the workflow connects

  • Household Tax Opportunities for lot-level loss and gain diagnostics.
  • Wash-sale warnings and snapshot staleness checks before interpreting candidates.
  • Match Factor Exposure for replacement-basket research using named factor models.

Why replacement research needs boundaries

A factor-matched basket can help compare exposure drift, but it does not determine whether a replacement is substantially identical or tax-safe. That legal and filing question remains outside the product.

Review the flagged lots, replacement candidates, and remaining exposure differences in the results.

Inputs to inspect before relying on the output

  • Snapshot date, account ownership, cost basis, and wash-sale lookback context.
  • The target fund, candidate ETF universe, factor model, and estimation window.
  • Whether the proposed replacement research should be stress-tested in a tax-aware backtest.

Current boundary

ArthaPilot surfaces tax-lot diagnostics and exposure-matching research. It does not recommend trades, determine tax treatment, or certify replacement securities for wash-sale purposes.

FAQ

Does this tell me which replacement avoids wash-sale rules?
No. It can surface wash-sale warnings and factor/exposure differences, but it does not determine whether a replacement security is substantially identical.
Why pair tax opportunities with Match Factor Exposure?
Tax-loss harvesting creates an implementation question: if a lot is a candidate, what exposure drift might a replacement introduce? Factor matching makes that research explicit.

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