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Sector rotation, a tactical approach to investing, is an investment strategy that attempts to achieve profits by alternating between sectors during different stages of a business cycle. Since "each industrial sector responds to macroeconomic factors, economic policies, and news in a different and unique way" (Lamponi [2014]), this would imply that "sector exposure may be a more effective way for investors to find the desired spot on the risk/reward spectrum" (Baiocchi and Britt [2012]). It should, therefore, not come as a surprise that sectors, and by extension, sector rotation, "receive so much attention from both the financial community and society as a whole" (Held [2009]).
As indicated by Chisholm et al. [2013], this popularity is very much linked to the historical returns of the U.S. equity market. For the period December 1990 to December 2012, Chisholm et al. [2013] found that "factors tied to a specific company have been the single most important explanatory variable for the returns of stocks," which explain on average 61% of historical returns, with sector exposure the second-most influential factor (on average, 22%). They attribute the remaining performance to style (12%) and market capitalization (5%).
This article adds to the wealth of knowledge on sector rotation by studying the incorporation of economic factors in the deployment of strategies. The economic factors we utilize are part of a common set of 18 variables contained within the Eta® pricing model (Chong et al. [2012]), with the unique feature being that many of these factors are low frequency in nature (e.g., monthly or quarterly). "If indeed economic factors are relevant to pricing asset values, then they must contain information that would enhance the risk-adjusted returns of investment portfolios" (Chong and Phillips [2012]). As such, we would like our investment strategies to exploit information that works its way into prices over time rather than instantaneously.
In addition, we use sector exchangetraded funds (ETFs) for our long-only strategies. This recent trend not only is easier to implement than selecting stocks within sectors (Chen [2014]), but it also provides a methodological advantage in that historical data on ETFs do not suffer from the same survivorship bias that often accompanies historical stock data.1
The research presented could be viewed as an accompaniment to Chong et al....