Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
Stock Strategy Backtester Clean
Backtest stock trading strategies on historical OHLCV data and report win rate, return, CAGR, drawdown, Sharpe ratio, and trade logs. Use when evaluating or...
skill openclawclawhub Free
Backtest stock trading strategies on historical OHLCV data and report win rate, return, CAGR, drawdown, Sharpe ratio, and trade logs. Use when evaluating or...
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, agents/openai.yaml, references/backtest-metrics.md, scripts/backtest_strategy.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.1
Provenance
- Publisher
- taylen
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Version Notice
Use this clean slug if your environment pins to stock-strategy-backtester-clean.
Overview
Run repeatable, long-only stock strategy backtests from daily OHLCV CSV files. Use bundled scripts to generate consistent metrics and trade-level output, then summarize with investor-friendly conclusions.
Quick Start
Prepare a CSV with at least Date and Close columns. Run a baseline backtest: python scripts/backtest_strategy.py \ --csv /path/to/prices.csv \ --strategy sma-crossover \ --fast-window 20 \ --slow-window 60 Export artifacts for review: python scripts/backtest_strategy.py \ --csv /path/to/prices.csv \ --strategy rsi-reversion \ --rsi-period 14 \ --rsi-entry 30 \ --rsi-exit 55 \ --commission-bps 5 \ --slippage-bps 2
Workflow
Validate data Ensure Date is parseable and sorted ascending. Ensure Open/High/Low/Close are numeric; missing Open/High/Low falls back to Close. Pick strategy logic sma-crossover: trend-following with fast/slow moving averages. rsi-reversion: buy oversold and exit on momentum recovery. breakout: enter on highs breakout and exit on lows breakdown. Set realistic assumptions Always set --commission-bps and --slippage-bps. Avoid reporting cost-free backtests as production-ready. Compare variants Change one parameter block at a time. Compare on the same date range and same cost model. Produce final summary Report: total_return_pct, cagr_pct, win_rate_pct, max_drawdown_pct, sharpe_ratio, profit_factor, and trade count. Use trade CSV to explain where alpha is coming from.
Supported Commands
Baseline SMA strategy: python scripts/backtest_strategy.py \ --csv /path/to/prices.csv \ --strategy sma-crossover \ --fast-window 10 \ --slow-window 50 Breakout strategy: python scripts/backtest_strategy.py \ --csv /path/to/prices.csv \ --strategy breakout \ --lookback 20 JSON-only output (for automation pipelines): python scripts/backtest_strategy.py \ --csv /path/to/prices.csv \ --strategy rsi-reversion \ --quiet
Output Contract
Script prints a JSON object to stdout with: strategy period metrics config trades
Analysis Guardrails
Use out-of-sample logic Prefer walk-forward validation over one-shot tuning. Avoid leakage Compute signals from bar t, execute at bar t+1 open. Report downside with upside Never present return without drawdown and trade count. Treat results as research Backtests are not guarantees and should not be framed as financial advice.
References
Metrics details: references/backtest-metrics.md
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts1 Config
- SKILL.md
- references/backtest-metrics.md
- scripts/backtest_strategy.py
- agents/openai.yaml