Research / Strategy lab
Portfolio Trading Robot
A research platform for repeatable testing of trading hypotheses, risk allocation and strategy execution.
01Data→02Signals→03Risk→04Paper orders
Context
A trading idea becomes useful only when it can be replayed consistently on historical data, with signal logic separated from risk and every system decision traceable.
How it works
Combined backtesting, technical indicators, ML filtering and risk-allocation rules. Scheduled jobs ingest market data, produce signals and log paper orders with their execution context.
What it enables
Each hypothesis follows the same research path, from historical validation to observable paper execution. Strategies can be compared through system behavior rather than disconnected experiments.