Develop an automated trading bot that identifies and exploits mean-reversion opportunities in financial markets using the Ornstein-Uhlenbeck (OU) process.
The bot continuously ingests real-time price data, estimates OU process parameters, and generates trading signals when prices deviate significantly from the modeled mean.
The strategy was validated out-of-sample and with walk-forward analysis across multiple assets — testing how performance behaves when assumptions change, with realistic transaction costs and execution constraints.
Validated beyond the backtest: out-of-sample, walk-forward, and sensitivity-tested
Key challenges encountered during development and deployment: