Built by an investor who
needed it to exist.
Who makes this
Harvest is built and maintained by Ryan O'Connor, a CFA charterholder and portfolio manager with more than a decade of experience managing fixed income, structured product, and multi-asset portfolios.
The tool started as a personal itch. Harvesting a loss on a single stock means answering one question well: what do I hold for the next 31 days that keeps my exposure without being the same security? Institutional desks answer it with factor models and licensed data. Individual investors mostly answer it with guesswork. There was no good standalone tool in between — so this is that tool.
How the numbers work
Enter a stock and the tool finds its industry-classification peers — companies in the same sub-industry — plus ETFs covering the same slice of the market. For each candidate it computes the Pearson correlation of daily closing-price returns against your holding over 1, 3, 5, and 10-year windows.
Methodology notes: price series are aligned trading-day by trading-day before returns are computed. A correlation cell is left blank when overlapping history covers less than 60% of its window, so a recently listed company never shows a mislabeled long-horizon figure. Data is end-of-day and unadjusted for intraday moves.
What this tool is not
It is not investment, tax, or legal advice, and it makes no recommendations. Correlation is a historical, descriptive statistic — it tells you how two securities have moved, not how they will. Whether any replacement avoids wash-sale treatment depends on your facts and circumstances; the "substantially identical" standard has no bright-line rule. Before acting on anything you find here, talk to your tax professional. That isn't boilerplate — it's how the person who built this would use it, too.
Questions or corrections
Spotted a misclassified ticker or a number that looks wrong? That feedback makes the tool better for everyone: rjoconnorlife@gmail.com
Harvest · Independent and unaffiliated with any broker, fund sponsor, or index provider. Classification groupings are editorial approximations for research convenience.
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