ABSTRACT

As we have proposed several online portfolio selection (OLPS) algorithms, we are interested in whether they work in real markets. To examine their empirical efficacy, we conducted an extensive set of empirical studies on a variety of real datasets. In our evaluations, we adopted six real datasets, which were collected from several diverse financial markets. The performance metrics include cumulative wealth (return) and risk-adjusted returns (based on volatility risk and drawdown risk). We also compared the proposed algorithms with various existing algorithms. The results clearly demonstrate that the proposed algorithms sequentially surpass the state-of-the-art techniques in terms of either metric.