position-sizer

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Position Sizer

仓位计算器

Overview

概述

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.

基于风险管理原则，计算多头股票交易的最优购买股数。支持三种仓位计算方法：

固定比例法：每笔交易承担账户净资产的固定比例风险（默认：1%）
基于ATR的方法：使用Average True Range（ATR）设置经波动率调整的止损距离
Kelly Criterion：根据历史盈亏统计数据计算数学上最优的风险分配

所有方法均应用投资组合约束条件（最大仓位占比、最大行业占比），并输出最终推荐的股数及完整的风险明细。

When to Use

适用场景

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 wants to check if a position fits within portfolio concentration limits

用户询问“我应该买多少股？”
用户希望为特定交易策略计算仓位规模
用户提及每笔交易风险、止损仓位设置或投资组合分配
用户询问Kelly Criterion或基于ATR的仓位计算
用户希望检查某一仓位是否符合投资组合集中度限制

Prerequisites

前提条件

No API keys required
Python 3.9+ with standard library only

无需API密钥
仅需Python 3.9+及标准库

Workflow

工作流程

Step 1: Gather Trade Parameters

步骤1：收集交易参数

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

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.

向用户收集以下信息：

必填项：账户规模（总净资产）
模式A（固定比例法）：入场价格、止损价格、风险比例（默认1%）
模式B（基于ATR的方法）：入场价格、ATR值、ATR乘数（默认2.0倍）、风险比例
模式C（Kelly Criterion）：胜率、平均盈利、平均亏损；可选提供入场和止损价格以计算股数
可选约束条件：账户最大仓位占比、行业最大占比、当前行业持仓占比

如果用户提供股票代码但未指定具体价格，可使用可用工具查询当前价格，并基于技术分析建议入场/止损价位。

Step 2: Execute Position Sizer Script

步骤2：执行仓位计算器脚本

Run the position sizing calculation:

bash

undefined

运行仓位计算脚本：

bash

undefined

Fixed Fractional (most common)

固定比例法（最常用）

python3 skills/position-sizer/scripts/position_sizer.py
--account-size 100000
--entry 155
--stop 148.50
--risk-pct 1.0
--output-dir reports/

ATR-Based

基于ATR的方法

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)

Kelly Criterion（预算模式 - 无需入场价）

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)

Kelly Criterion（股数模式 - 含入场/止损价）

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/

undefined

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/

undefined

Step 3: Load Methodology Reference

步骤3：查阅方法参考文档

Read

references/sizing_methodologies.md

to provide context on the chosen method, risk guidelines, and portfolio constraint best practices.

阅读

references/sizing_methodologies.md

，了解所选方法的背景、风险准则及投资组合约束的最佳实践。

Step 4: Calculate Multiple Scenarios

步骤4：计算多种场景

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

如果用户未指定单一方法，可运行多种场景进行比较：

固定比例法：0.5%、1.0%和1.5%风险比例
基于ATR的方法：1.5倍、2.0倍和3.0倍乘数
展示对比表格，包含每种场景的股数、仓位价值及美元风险

Step 5: Apply Portfolio Constraints and Determine Final Size

步骤5：应用投资组合约束并确定最终仓位

Add constraints if the user has portfolio context:

bash

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.

若用户提供投资组合相关信息，添加约束条件：

bash

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/

解释哪项约束条件生效，以及为何限制了仓位规模。

Step 6: Generate Position Report

步骤6：生成仓位报告

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)

呈现最终推荐内容，包括：

使用的方法及理由
准确的股数和仓位价值
美元风险及占账户的比例
止损价格
任何生效的约束条件
风险管理提醒（投资组合风险热度、止损纪律）

Output Format

输出格式

JSON Report

JSON报告

json

{
  "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
}

json

{
  "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

Markdown报告

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

会与JSON报告自动生成。包含：

参数摘要
当前使用方法的计算细节
约束条件分析（如有）
最终推荐的股数、价值及风险

报告将保存至

reports/

目录，文件名为

position_sizer_YYYY-MM-DD_HHMMSS.json

及

.md

。

Resources

资源

```
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)

```
references/sizing_methodologies.md
```
：固定比例法、基于ATR的方法和Kelly Criterion的综合指南，包含示例、对比表格及风险管理原则
```
scripts/position_sizer.py
```
主计算脚本（CLI界面）

Key Principles

核心原则

Survival first: Position sizing is about surviving losing streaks, not maximizing winners
The 1% rule: Default to 1% risk per trade; never exceed 2% without exceptional reason
Round down: Always round shares down to whole numbers (never round up)
Strictest constraint wins: When multiple limits apply, the tightest one determines final size
Half Kelly: Never use full Kelly in practice; half Kelly captures 75% of growth with far less risk
Portfolio heat: Total open risk should not exceed 6-8% of account equity
Asymmetry of losses: A 50% loss requires a 100% gain to recover; size accordingly

生存优先：仓位规模的核心是挺过亏损期，而非最大化盈利
1%规则默认每笔交易承担1%的风险；无特殊理由绝不超过2%
向下取整：股数始终向下取整为整数（绝不向上取整）
最严格约束优先：当存在多个限制条件时，最严格的条件决定最终仓位规模
半凯利准则：实际操作中绝不使用全凯利准则；半凯利准则可在风险远更低的情况下获取75%的增长收益
投资组合风险热度：总未平仓风险不应超过账户净资产的6-8%
亏损不对称性：50%的亏损需要100%的收益才能回本；据此合理设置仓位规模