Cost Density Net Rr Calculator

cost-density-net-rr-calculator

計算交易成本對風險報酬比的非線性衰減影響。將固定佣金與點差整合為「成本密度」指標，揭示停損大小與策略效率的雙曲線關係，識別「獲利事件視界」閾值。

majiayu000/claude-skill-registry·0installs663starsProductivity & Planning

SKILL.md

Full skill instructions

<essential_principles> 成本密度模型核心原則

1. 核心公式

所有計算基於以下關係：

Cost Density = (c/V + s)           # 成本密度（pips 等效）
x = Cost Density / P               # 負載係數
RR_net = (RR_g - x) / (1 + x)      # 淨風險報酬比
WR_min = (1 + x) / (1 + RR_g)      # 最低勝率
P_critical = CostDensity × (RR_g + 2) / RR_g  # 效率減半點

2. 參數定義

參數	定義	單位
RR_g	毛風險報酬比（目標/停損）	無單位
P	停損大小	pips/points
c	來回佣金（每手）	帳戶貨幣
s	來回點差	pips/points
V	每 pip 價值（每手）	帳戶貨幣/pip
R	固定風險（可選，會抵消）	帳戶貨幣

3. 關鍵洞察

雙曲線衰減: P → 0 時，x → ∞，RR_net → -1
R 無關性: RR_net 不依賴固定風險 R
剪刀效應: 短時間框架同時增加成本負擔與降低訊號品質

4. 單位一致性規則

P 和 s 必須使用相同基準（都是 pips 或都是 points）
c 必須是 round-turn（來回）佣金
V 必須是每 pip 每手的價值 </essential_principles>

<intake> **您想要執行什麼操作？**

Compute - 計算單一參數組合的成本密度與效率指標
Sweep - 掃描停損範圍，生成 RR_net/WR_min 曲線表
Analyze - 解讀結果，提供策略建議

等待回應後再繼續。 </intake>

<routing> | Response | Workflow | Description | |--------------------------------------|----------------------|----------------------| | 1, "compute", "calculate", "single" | workflows/compute.md | 單次計算成本密度指標 | | 2, "sweep", "grid", "curve", "range" | workflows/sweep.md | 網格掃描與閾值搜尋 | | 3, "analyze", "interpret", "explain" | workflows/analyze.md | 結果解讀與策略建議 |

讀取工作流程後，請完全遵循其步驟。 </routing>

<reference_index> 參考文件 (references/)

文件	內容
formulas.md	完整公式推導與數學證明
theory.md	市場微結構理論背景與文獻
</reference_index>

<workflows_index>

Workflow	Purpose
compute.md	單次計算成本密度與效率指標
sweep.md	網格掃描與閾值搜尋
analyze.md	結果解讀與策略建議
</workflows_index>

<templates_index>

Template	Purpose
output-schema.yaml	輸出 JSON schema
input-schema.yaml	輸入參數 schema
</templates_index>

<scripts_index>

Script	Purpose
cost_density.py	Python 計算實作
cost_density.ts	TypeScript 計算實作
</scripts_index>

<quick_start> 快速計算（XAU/USD 範例）：

輸入：

{
  "RR_g": 3.0,
  "c": 7.0,
  "s": 1.5,
  "V": 10.0,
  "P": 20
}

計算：

cost_density = 7.0/10.0 + 1.5  # = 2.2 pips
x = 2.2 / 20                    # = 0.11
RR_net = (3.0 - 0.11) / (1 + 0.11)  # = 2.60
WR_min = (1 + 0.11) / (1 + 3.0)     # = 27.7%
P_critical = 2.2 * (3.0 + 2) / 3.0  # = 3.67 pips

輸出：

{
  "cost_density": 2.2,
  "x": 0.11,
  "RR_net": 2.60,
  "WR_min": 0.277,
  "P_critical": 3.67,
  "Loss_RR": 0.133
}

</quick_start>

<success_criteria> Skill 成功執行時：

輸入參數通過驗證（單位一致性）
正確計算 cost_density、x、RR_net、WR_min
識別是否處於高摩擦區（P < P_critical）
輸出符合 outputs_schema
提供 zh-TW 解釋說明 </success_criteria>

Install skill

Copy and run in your terminal

npx -y skills add https://github.com/majiayu000/claude-skill-registry --skill cost-density-net-rr-calculator

View on GitHub

skills/data/cost-density-net-rr-calculator/SKILL.md

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