Set up, debug, and validate paper trading systems with simulated fills.
npx skills add https://github.com/trudumb/hyper_make --skill paper-trading
Please help me install this Agent Skill. Skill: paper-trading Source: https://github.com/trudumb/hyper_make/tree/main/.claude/skills/workflows/paper-trading Command: npx skills add https://github.com/trudumb/hyper_make --skill paper-trading
The paper trading workflow enables setting up, debugging, and validating trading strategies by using simulated fills against real market data, allowing testing without risking capital.
Start the paper trading workflow to initialize the simulation and validate strategy performance against real market data.
High-intent search queries and answers about installing and using this skill.
Paper trading uses simulated fills against real-time mid-price data to test trading strategies without risking capital. It enables local development and backtesting to verify strategy logic and risk controls before going live.
Setting up paper trading for backtesting requires initializing a deterministic FillSimulator to process real market data, managing calibration through a CalibrationController, and tracking local PnL to validate strategy robustness.
Calibration in simulated trading adjusts estimator accuracy using a CalibrationController to manage kappa confidence and calibration gamma. It ensures simulated fills remain realistic and strategy robustness is accurately validated.
Yes, paper trading is designed to debug and validate trading strategies by applying simulated fills to real market data. This allows you to verify strategy logic and risk controls locally before live deployment.
Yes, a deterministic FillSimulator is required to accurately simulate fills against real-time mid-price handling. This determinism ensures reliable backtesting, outcome tracking, and consistent strategy validation.
Backtesting with simulated fills depends on accurate calibration of kappa confidence and gamma to avoid unrealistic execution. Without proper calibration, tracked local PnL may not reflect true live market conditions or execution risk.
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