Research LabPreview

Turn market data
into better questions.

Build feature datasets, run supported research jobs, and compare reports inside the trading desktop. Keep your experiments close to the strategies they inform.

Get HyperionX See the workflow

HyperionX Research Lab dataset and quantitative research workspace — Inside the HyperionX desktop

Research Lab is Preview. Availability depends on your license, installed release, and research runtime.

BUILT INTO YOUR WORKFLOW

Give every strategy idea a research trail.

Shape your dataset

Choose an instrument, timeframe, historical range, and feature configuration. Review the generated columns and target labels before comparing results.

Run the experiment

Use the managed Python runtime for supported local research, or a cloud-assisted workflow when it is available and you have reviewed its data flow.

Compare and continue

Review reports and preserve the configuration behind each run. Take selected findings into strategy development and validation.

A CLEAR NEXT STEP

Make the experiment repeatable.

STEP 01
Define the dataset
Choose your market, range, features, and labels with the research question in mind.
STEP 02
Run and inspect
Verify the research runtime, start a supported job, and review the output and any omitted features.
STEP 03
Keep the evidence
Save your dataset configuration and reports, then test the resulting strategy idea through the validation workflow.

Set up your desktop

A LITTLE MORE CONTEXT

Good questions.
Clear answers.

Read the Research Lab documentation

Does all research stay on my computer?

Supported local jobs run through the managed Python environment. Cloud-assisted jobs have a separate data flow; review that workflow before sending a dataset.

Does a research result prove a live edge?

No. Results depend on data, labels, assumptions, and validation. Research output needs independent review and further testing.

BETTER TOGETHER

Backtesting & research