부산대학교 도서관

We present a simple model that uses time series momentum in order to construct strategies that systematically outperform their benchmark. The simplicity of our model is elegant: We only require a benchmark time series and several related investable indizes, not requiring regression or other models to estimate our parameters. We find that our one size fits all approach delivers significant outperformance in both equity and bond markets while meeting the ex-ante risk requirements, nearly doubling yearly returns vs. the MSCI World and Bloomberg Barclays Euro Aggregate Corporate Bond benchmarks in a long-only backtest. We then combine both approaches into an absolute return strategy by benchmarking vs. the Eonia Total Return Index and find significant outperformance at a sharpe ratio of 1.8. Furthermore, we demonstrate that our model delivers a benefit versus a static portfolio with fixed mean weights, showing that timing of excess return momentum has a sizeable benefit vs. static allocations. This also applies to the passively investable equity factors, where we outperform a static factor exposure portfolio with statistical significance. Also, we show that our model delivers an alpha after deducting transaction costs.
Comment: 23 pages, 10 figures