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I will backtest your trading strategy in python with risk analysis
Python for Quant Finance, Backtesting, Market Data and FX
I build Python tools for financial market data, strategy backtesting, portfolio risk analysis and FX pricing. My work combines quantitative finance, time-series analysis and machine learning with clea...
About this Gig
Test your trading rules with a reproducible Python backtest and a clear explanation of performance and risk.
I will implement one fully specified, rule-based strategy for one asset using your supplied daily OHLCV data, up to 10000 rows. All packages include agreed transaction costs, explicit signal timing, an equity curve, drawdown, trade log, performance metrics, Python source and setup notes.
STANDARD adds a benchmark and chronological train/test split. PREMIUM adds up to 10 parameter combinations and a sensitivity summary; selection uses the training sample and the test sample stays separate.
Please provide entry/exit rules, position sizing, capital, fees, slippage and the sample period. Revisions: Basic 1; Standard and Premium 2, within the agreed rules.
Research and evaluation only: historical results do not guarantee future returns. Live trading, broker APIs, Pine Script, high-frequency data, strategy discovery and ML model development require a separate quote. English or French documentation.
FAQ
Will you create a profitable trading strategy?
I implement and evaluate your specified rules. Profitability, returns and win rates are not guaranteed. The deliverable is documented research code and a report, not investment advice or a live execution system.
What data and rules should I provide?
Provide daily OHLCV data, asset and sample dates, entry and exit rules, sizing, initial capital, trading costs and slippage assumptions. Message me first for intraday data, complex instruments, additional assets or ambiguous rules.
