Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, PMLR 15:434-442, 2011.
This paper proposes a novel on-line portfolio selection strategy named “Confidence Weighted Mean Reversion” (CWMR). Inspired by the mean reversion principle and the confidence weighted online learning technique, CWMR models a portfolio vector as Gaussian distribution, and sequentially updates the distribution by following the mean reversion trading principle. The CWMR strategy is able to effectively exploit the power of mean reversion for on-line portfolio selection. Extensive experiments on various real markets demonstrate the effectiveness of our strategy in comparison to the state of the art.