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TaxLot Rebalancer: Tax-Aware Rebalancing Execution Service

A human-powered rebalancing service where certified financial technicians (not advisors) receive a client's portfolio snapshot, calculate optimal rebalancing trades while modeling tax consequences across all holdings and cost basis lots, then execute the trades via the client's brokerage API or provide a detailed trade ticket for manual execution. The service handles wash-sale detection, long-term vs. short-term gain optimization, and state tax implications—all within 48 hours.

SERVICE

29 weeks • 70% confidence

Value Proposition

Eliminates the 4–6 hours of manual calculation and spreadsheet error per rebalancing event; recovers 1–3% in tax efficiency annually through lot-selection optimization and wash-sale avoidance; executes in 48 hours vs. weeks of procrastination; costs 1/10th of a financial advisor retainer ($150–300 vs. $3k–10k annually) while beating generic robo-advisors that ignore custom tax strategies.

Target Audience

Self-directed investors with $250k–$5M portfolios who rebalance 2–4 times yearly and hold positions across multiple accounts (taxable + retirement); primarily ages 35–65 with high income and tax sensitivity.

Key Features

  • Tax-lot-level cost basis import from brokerage (API or CSV upload)
  • Multi-account aggregation with tax-loss harvesting opportunity detection
  • Wash-sale rule modeling across 30-day windows
  • And more, with full implementation detail...

Tech Stack

Brokerage APIs: Schwab PortfolioCenter, Fidelity NetBenefits, E*TRADE, Interactive Brokers Backend: Python (pandas for tax-lot calculations), PostgreSQL for client data Frontend: React for client portal & technician dashboard Tax calculation library: custom-built (no off-the-shelf library handles multi-account, multi-state optimization)
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Original Problem

Portfolio rebalancing requires manual calculation and execution, causing tax inefficiency and missed optimization opportunities

Individual investors with equal-weighted portfolios struggle to efficiently rebalance their holdings because manual calculation of drift percentages, tax implications, and optimal trade execution is time-consuming and error-prone. Current solutions either require expensive financial advisors or force investors to use generic robo-advisors that don't accommodate custom portfolio strategies. This results in suboptimal rebalancing decisions, unexpected tax bills, and portfolio drift that erodes returns.

Score: 47.7%

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