Solutions ยท Strategy Research
Prove it before you trade it.
Build, backtest and paper-trade strategies against pre-sourced market data, then move to live execution without rebuilding a single line of the logic.
Without it
A quant builds a strategy in a research notebook. It looks strong in backtest. A different team rebuilds it from scratch for production. Small differences in execution assumptions creep in. Live performance quietly diverges from what was tested.
With Jheel
The strategy object that ran in backtest is the same object that trades live. No second implementation to drift from the first. The model, its parameters, its logic: unchanged.
What it does
Everything between an idea and a live position
Full model library
From SMA, EMA and Bollinger Bands through statistical and machine-learning models.
Pre-sourced market data
Backtest against data that's already connected. No separate feed to license.
Realistic cost modeling
Transaction cost and slippage assumptions built into every backtest run.
Paper trading
Run the strategy against live markets before a dollar of capital moves.
Custom models via scripting
The same in-app scripting surface used across the platform defines your own models.
No reimplementation gap
The tested strategy is the trading strategy. Literally. Not in spirit.
How it connects