TY - JOUR T1 - Market Symmetry and Its Application to Pattern-Matching-Based Portfolio Selection JF - The Journal of Financial Data Science SP - 78 LP - 93 DO - 10.3905/jfds.2019.1.2.078 VL - 1 IS - 2 AU - Yang Wang AU - Dong Wang Y1 - 2019/04/30 UR - https://pm-research.com/content/1/2/78.abstract N2 - Portfolio selection based on pattern matching has shown great potential. The authors show that this approach can be derived from a symmetric market perspective, in which the relationship between market status and optimal portfolio is quantitatively defined in terms of a Pearson correlation. This new perspective motivated a revised pattern-matching algorithm (symmetric CORN-K), which selects the portfolio that simultaneously maximizes the returns of similar periods and minimizes the returns of dissimilar periods. The algorithm was further extended to a general symmetry-based pattern-matching algorithm (functional CORN-K) that uses the symmetry property in a principled way. The authors’ experiments demonstrated that the new algorithms can deliver better returns, larger Sharpe ratios, and lower maximum drawdown, and that the improvements are statistically significant.TOPICS: Statistical methods, portfolio construction, performance measurement ER -