Zephyrine — Quant Backtesting Researcher AI Skill
Instant download · 30-day money-back guarantee. Pay once, keep forever — no subscription. Refund policy
Turn a beautiful 2.1 Sharpe ratio into a bootstrap significance test, and find out if it's real edge or a coin flip wearing a chart.
- Hypotheses written down and frozen before any historical data gets pulled
- Python backtests (Backtrader, QuantConnect, vectorbt-style) built with realistic costs and slippage from the first run
- Walk-forward and cross-validation splitting to catch curve-fit results before they get trusted
- Statistical significance testing (bootstrap, t-test, permutation) so a good Sharpe ratio isn't mistaken for edge
Traders and researchers who want a systematic strategy idea rigorously validated in Python before risking capital on it.A senior Quant Backtesting Researcher bills $110+/hr, this is one file, yours forever.
Drop Zephyrine into Claude and get a Senior Quant Backtesting Researcher who treats every strategy idea as a hypothesis to be disproven, not a discovery to be celebrated.
Zephyrine covers hypothesis formation, Python backtesting with realistic costs, walk-forward and cross-validation, statistical significance testing, and multi-strategy portfolio correlation analysis.
What you get
- →Hypotheses written down and frozen before any historical data gets pulled
- →Python backtests (Backtrader, QuantConnect, vectorbt-style) built with realistic costs and slippage from the first run
- →Walk-forward and cross-validation splitting to catch curve-fit results before they get trusted
- →Statistical significance testing (bootstrap, t-test, permutation) so a good Sharpe ratio isn't mistaken for edge
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Zephyrine builds the answer. Includes a full worked example so you see exactly what you get.
# Zephyrine - Quant Backtesting Researcher You are Zephyrine, a Senior Quant Backtesting Researcher. Treat every strategy idea as a hypothesis to be disproven. ## How you work 1. Form the hypothesis before looking at returns 2. Build the backtest with realistic frictions from the start 3. Split the data before optimizing anything 4. Test whether the result could be noise, with a real significance test 5. Check the strategy in a portfolio context, then deliver a verdict, not just a chart A lucky draw is not edge until a significance test says otherwise.
Excerpt from the actual file you'll download.
Four steps. Any AI chat.
- 01Download the file
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
- 02Open your AI chat
Claude, ChatGPT, Gemini, Grok, or Copilot — whichever one you already use.
- 03Paste the file contents
Drop it into the system prompt, Project instructions, or custom instructions field.
- 04Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required. No subscription. Pay once, keep forever.
Works with every major AI chat.
Drop the file into your AI's system prompt, Project instructions, or custom instructions. No setup. No code. No vendor lock-in.
- Claude
- ChatGPT
- Gemini
- Grok
- Copilot
Works with any AI chat that accepts a system prompt or custom instructions.
Ready to specialise your AI?
One drop-in file. Pay once, keep forever — works with Claude & ChatGPT.