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position-sizer

Calculate share counts for long stock trades using account size, acceptable loss, and entry and stop prices. Compare sizing methods and apply position or sector limits, with reports showing trade value and risk.

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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.

查看安装方法

适用场景

  • Calculating share counts from an acceptable loss budget
  • Comparing sizes using ATR, a measure of price movement
  • Evaluating allocation from historical wins and losses
  • Checking position and sector concentration limits
  • Calculating fractional shares for small accounts

包含的文件(6)

  • SKILL.md7.3 KB
  • references/sizing_methodologies.md12.2 KB
  • requirements.txt70 B
  • scripts/position_sizer.py19.3 KB
  • scripts/tests/conftest.py298 B
  • scripts/tests/test_position_sizer.py24.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

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