The experiment runs without relying on my laptop.
Forecast generation and post-close scoring are designed as remote, version-controlled workflows. The research process therefore depends on a defined schedule and committed code rather than on remembering to run a script manually.
Two automated jobs surround the market session.
Forecast runner
Retrieve the permitted pre-open information, create the target-date forecast, lock the observation and publish the public-safe result.
Scoring runner
Retrieve the realised Nasdaq Composite close, score the frozen forecast, update prospective records and publish the resulting evidence.
Automation is part of how the experiment is controlled.
A cloud workflow starts around the defined forecasting or scoring window.
The committed production scripts execute in a clean remote environment.
Guards stop the run when timing, data or output assumptions fail.
The new forecast or score is saved as a dated research artifact.
Only the public-safe derived output is copied to this website.
Reduce the amount of manual intervention.
Manual execution creates avoidable discretion: a forecast can be delayed, forgotten, or run under a different local environment. A remote workflow makes the timing and software environment part of the experiment itself.