Quant Lab · Primary: R · Secondary: Python

Backtests, Risk &
Systematic Research.

Frameworks and strategy research built for real decision-making. Each project is cost-aware, regime-tested, and designed for replication.

Primary: R Secondary: Python
01Active
Backtest Risk R
In Progress

ORB Backtest Framework

Reusable backtesting engine with transaction costs, position sizing, and performance diagnostics. Foundational framework for future strategy research.

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02Pipeline
SimulationPortfolioPython/R
Planned

Monte Carlo Portfolio Simulator

Thousands of portfolio paths — drawdown probability, terminal wealth ranges, and risk-of-ruin under different allocation rules. Horizon and sequence-of-returns stress testing.

After ORB
IndicatorsRegimesPython/R
Planned

EMA Strategy Across Volatility Regimes

Do simple momentum indicators behave differently in low vs high volatility? Fixed rules, compared across regimes, with cost and turnover diagnostics.

After Monte Carlo