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position-sizer

tradermonty/claude-trading-skills

Calculate optimal share counts for long stock trades using risk-based position sizing methods.

What is position-sizer?

Position Sizer computes the number of shares to buy for a long stock trade based on account size, entry/stop prices, and risk tolerance. Use it when determining position size, applying Kelly Criterion, scaling for volatility (ATR), or checking portfolio concentration limits.

  • Calculate shares using Fixed Fractional (risk % of account), ATR-based (volatility-adjusted stops), or Kelly Criterion methods
  • Apply portfolio constraints: max position % and max sector % to prevent over-concentration
  • Support both whole shares (default) and fractional shares with configurable precision
  • Generate detailed JSON and Markdown reports with risk breakdown, stop-loss prices, and binding constraints
  • Compare multiple sizing scenarios side-by-side (e.g., 0.5%, 1.0%, 1.5% risk levels)
  • Floor share counts to respect risk and concentration budgets without rounding up

How to install position-sizer

npx skills add https://github.com/tradermonty/claude-trading-skills --skill position-sizer
Prerequisites
  • Python 3.9+ with standard library only
  • No API keys or external dependencies required
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How to use position-sizer

  1. 1.Gather trade parameters: account size, entry price, stop price, and risk percentage (or ATR/Kelly inputs)
  2. 2.Run the position_sizer.py script with your parameters (e.g., --account-size 100000 --entry 155 --stop 148.50 --risk-pct 1.0)
  3. 3.Optionally add portfolio constraints (--max-position-pct, --max-sector-pct, --current-sector-exposure) if applicable
  4. 4.Review the JSON and Markdown reports in the reports/ directory for share count, position value, dollar risk, and any binding constraints
  5. 5.Apply the final recommended share count to your trade entry; monitor the stop-loss price and portfolio heat (total open risk)

Use cases

Good for
  • Determine how many shares to buy given a $100k account, $155 entry, $148.50 stop, and 1% risk target
  • Size a position using ATR volatility: entry $155, ATR $3.20, 2.0x multiplier for dynamic stop placement
  • Calculate Kelly Criterion allocation from historical win rate (55%), average win ($2.50), and average loss ($1.00)
  • Check if a position fits portfolio limits: max 10% per position, max 30% per sector, current sector exposure 22%
  • Size fractional shares for a $1,000 account or high-priced stock to deploy defined risk without whole-share rounding loss
Who it's for
  • Swing traders and position traders managing risk per trade
  • Small-account traders using fractional shares to maximize capital deployment
  • Portfolio managers enforcing concentration limits across positions and sectors
  • Traders using Kelly Criterion or ATR-based volatility scaling for position sizing
  • Anyone building systematic trading workflows with defined risk rules

position-sizer FAQ

What is the difference between Fixed Fractional, ATR-based, and Kelly Criterion sizing?

Fixed Fractional risks a fixed percentage of account equity per trade (default 1%). ATR-based uses volatility (Average True Range) to set dynamic stop distances, scaling position size inversely with volatility. Kelly Criterion calculates mathematically optimal risk allocation from historical win/loss statistics; half Kelly is recommended in practice.

Should I use whole shares or fractional shares?

Use whole shares by default for standard workflows. Use fractional shares (--fractional flag) only when your broker supports them for the security and order type, and when whole-share rounding would significantly under-deploy your risk budget (common in small accounts or high-priced stocks).

What does 'binding constraint' mean in the output?

A binding constraint is the tightest limit that reduces your position size below the unconstrained calculation. For example, if max position % is 10% and max sector % is 30%, whichever results in fewer shares is the binding constraint. The report identifies which one applies.

Can I compare multiple sizing methods at once?

Yes. Run multiple scenarios with different parameters (e.g., --risk-pct 0.5, 1.0, 1.5 for Fixed Fractional, or --atr-multiplier 1.5, 2.0, 3.0 for ATR-based) and present a comparison table showing shares, position value, and dollar risk for each.

What is the '1% rule' and why does it matter?

The 1% rule recommends risking no more than 1% of account equity per trade; never exceed 2% without exceptional reason. This ensures you can survive losing streaks and compound gains over time. Position sizing enforces this discipline by calculating shares that respect your risk budget.

Full instructions (SKILL.md)

Source of truth, from tradermonty/claude-trading-skills.


name: position-sizer description: Calculate risk-based position sizes for long stock trades. Use when user asks about position sizing, how many shares to buy, risk per trade, Kelly criterion, ATR-based sizing, fractional-share sizing, or portfolio risk allocation. Supports stop-loss distance calculation, volatility scaling, and sector concentration checks.

Position Sizer

Overview

Calculate the optimal number of shares to buy for a long stock trade based on risk management principles. Supports three sizing methods:

  • Fixed Fractional: Risk a fixed percentage of account equity per trade (default: 1%)
  • ATR-Based: Use Average True Range to set volatility-adjusted stop distances
  • Kelly Criterion: Calculate mathematically optimal risk allocation from historical win/loss statistics

All methods apply portfolio constraints (max position %, max sector %) and output a final recommended share count with full risk breakdown. The default output is whole shares. Use --fractional only when the user's broker supports fractional shares for the security and order type.

When to Use

  • User asks "how many shares should I buy?"
  • User wants to calculate position size for a specific trade setup
  • User mentions risk per trade, stop-loss sizing, or portfolio allocation
  • User asks about Kelly Criterion or ATR-based position sizing
  • User has a small account where whole-share rounding would under-deploy a defined risk budget
  • User wants to check if a position fits within portfolio concentration limits

Prerequisites

  • No API keys required
  • Python 3.9+ with standard library only

Workflow

Step 1: Gather Trade Parameters

Collect from the user:

  • Required: Account size (total equity)
  • Mode A (Fixed Fractional): Entry price, stop price, risk percentage (default 1%)
  • Mode B (ATR-Based): Entry price, ATR value, ATR multiplier (default 2.0x), risk percentage
  • Mode C (Kelly Criterion): Win rate, average win, average loss; optionally entry and stop for share calculation
  • Optional constraints: Max position % of account, max sector %, current sector exposure
  • Optional share mode: Whole shares by default, or fractional shares with --fractional --share-precision N when supported by the broker

If the user provides a stock ticker but not specific prices, use available tools to look up the current price and suggest entry/stop levels based on technical analysis.

Step 2: Execute Position Sizer Script

Run the position sizing calculation:

# Fixed Fractional (most common)
python3 skills/position-sizer/scripts/position_sizer.py \
  --account-size 100000 \
  --entry 155 \
  --stop 148.50 \
  --risk-pct 1.0 \
  --output-dir reports/

# Fractional shares for small accounts or high-priced stocks
python3 skills/position-sizer/scripts/position_sizer.py \
  --account-size 1000 \
  --entry 155 \
  --stop 148.50 \
  --risk-pct 1.0 \
  --fractional \
  --share-precision 4 \
  --output-dir reports/

# ATR-Based
python3 skills/position-sizer/scripts/position_sizer.py \
  --account-size 100000 \
  --entry 155 \
  --atr 3.20 \
  --atr-multiplier 2.0 \
  --risk-pct 1.0 \
  --output-dir reports/

# Kelly Criterion (budget mode - no entry)
python3 skills/position-sizer/scripts/position_sizer.py \
  --account-size 100000 \
  --win-rate 0.55 \
  --avg-win 2.5 \
  --avg-loss 1.0 \
  --output-dir reports/

# Kelly Criterion (shares mode - with entry/stop)
python3 skills/position-sizer/scripts/position_sizer.py \
  --account-size 100000 \
  --entry 155 \
  --stop 148.50 \
  --win-rate 0.55 \
  --avg-win 2.5 \
  --avg-loss 1.0 \
  --output-dir reports/

Step 3: Load Methodology Reference

Read references/sizing_methodologies.md to provide context on the chosen method, risk guidelines, and portfolio constraint best practices.

Step 4: Calculate Multiple Scenarios

If the user has not specified a single method, run multiple scenarios for comparison:

  • Fixed Fractional at 0.5%, 1.0%, and 1.5% risk
  • ATR-based at 1.5x, 2.0x, and 3.0x multipliers
  • Present a comparison table showing shares, position value, and dollar risk for each

Step 5: Apply Portfolio Constraints and Determine Final Size

Add constraints if the user has portfolio context:

python3 skills/position-sizer/scripts/position_sizer.py \
  --account-size 100000 \
  --entry 155 \
  --stop 148.50 \
  --risk-pct 1.0 \
  --max-position-pct 10 \
  --max-sector-pct 30 \
  --current-sector-exposure 22 \
  --output-dir reports/

Explain which constraint is binding and why it limits the position.

Step 6: Generate Position Report

Present the final recommendation including:

  • Method used and rationale
  • Exact share count and position value
  • Dollar risk and percentage of account
  • Stop-loss price
  • Any binding constraints
  • Risk management reminders (portfolio heat, loss-cutting discipline)
  • Small-account reminders: fractional shares do not remove broker minimums, spread/slippage, commissions/fees, margin limits, borrow availability, or day-trading controls

Output Format

JSON Report

{
  "schema_version": "1.0",
  "mode": "shares",
  "parameters": {
    "entry_price": 155.0,
    "account_size": 100000,
    "stop_price": 148.50,
    "risk_pct": 1.0
  },
  "calculations": {
    "fixed_fractional": {
      "method": "fixed_fractional",
      "shares": 153,
      "risk_per_share": 6.50,
      "dollar_risk": 1000.0,
      "stop_price": 148.50
    },
    "atr_based": null,
    "kelly": null
  },
  "constraints_applied": [],
  "final_recommended_shares": 153,
  "final_position_value": 23715.0,
  "final_risk_dollars": 994.50,
  "final_risk_pct": 0.99,
  "binding_constraint": null
}

Markdown Report

Generated automatically alongside the JSON report. Contains:

  • Parameters summary
  • Calculation details for the active method
  • Constraints analysis (if any)
  • Final recommendation with shares, value, and risk

Reports are saved to reports/ with filenames position_sizer_YYYY-MM-DD_HHMMSS.json and .md.

Resources

  • references/sizing_methodologies.md: Comprehensive guide to Fixed Fractional, ATR-based, and Kelly Criterion methods with examples, comparison table, and risk management principles
  • scripts/position_sizer.py: Main calculation script (CLI interface)

Key Principles

  1. Survival first: Position sizing is about surviving losing streaks, not maximizing winners
  2. The 1% rule: Default to 1% risk per trade; never exceed 2% without exceptional reason
  3. Default to whole shares: Existing workflows remain integer-share by default
  4. Floor, never round up: Whole-share mode floors to an integer; fractional mode floors to the requested precision so risk and concentration budgets are not exceeded
  5. Strictest constraint wins: When multiple limits apply, the tightest one determines final size
  6. Half Kelly: Never use full Kelly in practice; half Kelly captures 75% of growth with far less risk
  7. Portfolio heat: Total open risk should not exceed 6-8% of account equity
  8. Intraday rules are broker-specific: FINRA replaced the old pattern-day-trader day-count and $25,000 minimum-equity requirements with intraday margin standards effective 2026-06-04, with broker phase-in allowed through 2027-10-20. Check the broker's current rules before repeated same-day trading in a margin account.
  9. Asymmetry of losses: A 50% loss requires a 100% gain to recover; size accordingly