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Sector Outperformance Over The Business Cycle
The Conventional Sector Rotation Model



Chart showing preferred Sector Allocation through the business cycle according to the conventional
		wisdon regaring sector rotation
  • The conventional wisdom on outperforming with a sector rotation strategy is comprehensively set out in S&P's "Guide to Sector Investing" by Sam Stovall
  • It postulates that an investment strategy involving a series of specific sector allocation shifts through the stages of the business cycle outperforms a passive strategy
  • Stangl, Jacobsen and Visaltanachoti tested this strategy using monthly industry-group returns between for 1948-2006 and actual NBER business cycle timing, in their 2007 research paper "Sector Rotation over Business-Cycles"
  • They found that considering real world factors - primarily transaction costs and the problems inherent in forecasting the business cycle - renders excess returns from the conventional sector rotation strategy at best insignificant, although gross returns do partially validate it.
  • Performance is uneven across the business cycle
 
  • Sector rotation returns tend towards the same pattern as the broad market, with the best and worst performance during late and early stage recession respectively, for a Sharpe ratio that is somewhat worse than a purely passive strategy
  • During early to middle expansion preferred sectors underperform the broad market and conversely strongly outperform during early recession
  • The latter conclusion is interesting in light of an alternative study "Sector Rotation and Monetary Conditions" that examines a more straightforward rotation strategy switching between broadly defined cyclical and defensive sectors depending on whether monetary  policy is easing or tightening
  • Stangl, Jacobsen and Visaltanachoti's findings that sector returns are unevenly distributed across the business cycle confirm the opportunity to generate excess returns with superior sector based strategies that capture part of the Sector Momentum Anomaly


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