
Backtest Cost Sensitivity
io.github.tylerscomic-labv1.0.0更新於 Oct 2, 2026
Commission/slippage sensitivity sweep, breakeven cost finder, and lookahead-bias checklist.
概覽
透過掃描手續費與滑點假設來分析回測結果,找出策略的損益兩平成本並稽核前視偏差。
- 功能
- 它提供三個用來評估執行成本如何影響交易策略回測的工具。cost_sensitivity_sweep 針對回測結果掃描一系列手續費與滑點假設,並回報各項績效指標如何隨成本變化而下降。breakeven_cost_finder 找出策略優勢歸零的確切成本水準。lookahead_bias_checklist 針對跨 K 線邊界的資料洩漏、重繪指標和讀取未來 K 線等前視偏差模式提供結構化稽核。
- 適用情境
- 適用於在實盤前驗證演算法交易策略,尤其是當回測只依賴單一固定手續費或滑點假設時。它有助於判斷策略優勢能否在真實執行成本下存活,以及回測是否包含前視偏差。
- 執行需求
- 以遠端 streamable HTTP 端點方式執行;未宣告任何套件、環境變數、標頭或身分驗證。自架方式為透過 npm 安裝並執行 node server.js,需要 Node.js。託管方式據描述提供免費方案與付費 Pro 方案。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Backtest Cost Sensitivity,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"backtest-cost-sensitivity-mcp": {
"type": "http",
"url": "https://backtest-cost-sensitivity-mcp.mcpize.run/mcp"
}
}
}README
backtest-cost-sensitivity-mcp
[License: MIT] [Live on MCPize]
An MCP server that sweeps commission and slippage assumptions across a backtest to find the real breakeven cost per trade, plus a structured look-ahead-bias audit.
The problem this solves
Most backtests run with one fixed commission/slippage assumption, which hides how fragile a strategy's edge actually is to real-world execution costs. A strategy that's profitable at 0.5 ticks of slippage and dead at 1.5 ticks needs to know that before going live, not after.
Tools
cost_sensitivity_sweep
Sweeps a range of commission and slippage assumptions against backtest results and reports how performance metrics degrade across the range.
breakeven_cost_finder
Finds the exact commission/slippage level at which a strategy's edge goes to zero — the real cost ceiling, not a guess.
lookahead_bias_checklist
A structured audit for the specific look-ahead-bias patterns that inflate backtest performance (data leakage across bar boundaries, repainting indicators, future-bar reads).
Use it
Hosted (recommended): MCPize — free tier, paid Pro tier for higher limits.
Self-host:
Part of the AlgoForge suite
Prop-firm and quant-validation tools for algo traders: prop-rules-mcp, trade-journal-mcp, payout-calc-mcp, econ-calendar-mcp, montecarlo-validator-mcp, overfitting-audit-mcp, walkforward-validator-mcp, pinescript-audit-mcp, pinescript-mcp.
License
MIT
來源:README.md,提交 e25023c
工具
0版本歷史
1- v1.0.0最新Oct 2, 2026