anti-gambling-trader-tw
New用統計學判斷你的交易是優勢還是賭博 — 支援台股/美股/加密貨幣,自動計算勝率盈虧比期望值、做顯著性檢定與樣本外驗證,並能產生個人交易程式專案
Summary
This skill helps traders evaluate whether their trading strategy has a statistical edge or is simply gambling.
- It supports Taiwanese stocks, US stocks, and cryptocurrencies, automatically calculating win rate, risk-reward ratio, expected value, performing significance tests, and out-of-sample validation, and can generate a personal trading program project.
Install & Usage
mkdir -p .claude/skillsAdd the configuration to .claude/skills/anti-gambling-trader-tw.md
/anti-gambling-trader-twUse Cases
Usage Examples
/anti-gambling-trader-tw analyze my trade log for TSLA from 2023
Run a significance test on my crypto futures trades from the last 6 months
/anti-gambling-trader-tw generate trading bot project from my validated strategy
Security Audits
Frequently Asked Questions
What is anti-gambling-trader-tw?
This skill helps traders evaluate whether their trading strategy has a statistical edge or is simply gambling. It supports Taiwanese stocks, US stocks, and cryptocurrencies, automatically calculating win rate, risk-reward ratio, expected value, performing significance tests, and out-of-sample validation, and can generate a personal trading program project.
How to install anti-gambling-trader-tw?
To install anti-gambling-trader-tw: create the skills directory (mkdir -p .claude/skills), then add the config to .claude/skills/anti-gambling-trader-tw.md. Finally, /anti-gambling-trader-tw in Claude Code.
What is anti-gambling-trader-tw best for?
anti-gambling-trader-tw is a other categorized under General. Created by mars-tw.
What can I use anti-gambling-trader-tw for?
anti-gambling-trader-tw is useful for: Analyze your trading history to determine if your strategy has a statistically significant edge over random chance.; Calculate key metrics like win rate, risk-reward ratio, and expected value for your stock or crypto trades.; Perform hypothesis testing to see if your trading results are significantly different from a 50/50 coin flip.; Validate your trading strategy on out-of-sample data to check for overfitting.; Generate a Python trading bot project based on your validated strategy parameters.; Compare the performance of multiple trading strategies using statistical significance tests..