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Portfolio allocation

The portfolio manager decides how much weight to give each symbol, using a constraint solver (Google OR-Tools) rather than ad-hoc rules. It maximises total expected score subject to hard constraints.

make allocate
# or
uv run python main.py allocate --scanner volume --symbols NVDA,META,TSLA,AMD \
    --capital 100000 --max-positions 5 --max-weight 0.25

Requires the optional extra:

make install-portfolio    # or: uv sync --extra portfolio

What it solves​

Each scanned symbol becomes a candidate with a score (here, its trailing return — a transparent, swappable factor) and a price. The solver chooses weights to maximise the score-weighted allocation subject to:

  • invest at most 100% of capital,
  • hold at most --max-positions names,
  • cap any single name at --max-weight.

Example output:

SYMBOL     WEIGHT       DOLLARS    SHARES
NVDA        25.0%     25,000.00       190
META        25.0%     25,000.00        51
TSLA        20.0%     20,000.00        80

Choosing the factor​

The CLI scores by trailing return, but the allocator accepts any score. Swap in momentum, inverse volatility, a model's expected return, or signal strength — see Portfolio (engineering) for the model and how to change the scoring factor.