Exchange-Traded Funds (ETFs)



This chapter discusses trading strategies for exchange-traded funds (ETFs), including detailed mathematical descriptions. Momentum-based strategies include sector momentum rotation, which can be augmented with a filter based on moving averages. Another momentum strategy is based on dual-momentum sector rotation, which utilizes both cross-sectional momentum and time-series momentum. The chapter also discusses other strategies such as those based on ETF alpha rotation with alphas obtained using a serial regression against the three Fama–French factors, cross-sectional R-squared also known as “selectivity” obtained using the residuals of a serial regression against the three Fama–French factors plus Carhart’s momentum factor, mean-reversion using internal bar strength (IBS), arbitraging a long-run negative drift in leveraged ETFs by shorting a leveraged ETF and a leveraged inverse ETF, and multi-asset trend-following strategies using ETFs.


Exchange-traded funds (ETFs) Sector momentum rotation Moving average Dual-momentum sector rotation Cross-sectional momentum Time-series momentum Alpha rotation Serial regression Fama–French factors R-squared strategy Selectivity Carhart’s momentum factor Mean-reversion Internal bar strength (IBS) Leveraged ETF Leveraged inverse ETF Multi-asset trend following Absolute momentum Relative momentum Sector ETF Drift Dynamic asset allocation Weighting scheme Jensen’s alpha Regression coefficient 


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© The Author(s) 2018

Authors and Affiliations

  1. 1.Quantigic Solutions LLCStamfordUSA
  2. 2.Universidad del CEMABuenos AiresArgentina

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