Pair Trading

Pair trading is a statistical arbitrage strategy aiming to profit from the mean reversion of price spreads between correlated assets. Current research heavily emphasizes the application of reinforcement learning (RL), often incorporating recurrent neural networks like GRUs and attention mechanisms, to optimize trading decisions and manage risk more effectively than traditional methods. This focus extends to exploring various model architectures, including Kalman filters augmented with neural networks, to improve accuracy and robustness in diverse markets like cryptocurrencies and stocks. The resulting advancements hold significant potential for improving algorithmic trading strategies and enhancing portfolio performance.