Active Trading Strategy Performance: An Empirical Comparison using US REIT Data

Over the last thirty years a large literature has developed that considered the investment opportunities that arise within the REIT (Real Estate Investment Trust) sector. This literature has considered an array of issues, including the relationship and diversification across different REIT sectors (e.g. Chong et al., 2012; Stevenson 2016), the role REITs can play in both real estate (e.g. Stevenson, 2001) and capital market (Liu & Mei, 1992; Lee & Stevenson, 2005) portfolios and also issues relating to international diversification in public real estate. Some papers have considered portfolio trading strategies within REITS (e.g. Cici et al., 2011; Feng et al., 2022; Zhou & Anderson, 2013) and also the analysis of Smart Beta strategies (Guidolin & Pedio, 2019) or the predictability of REIT returns (e.g. Akinsomi et al., 2016; Letdin et al., 2019; Ling et al., 2000; Li & Wang, 1995; Serrano & Hoesli, 2010, Stevenson, 2001). However, the majority of this literature has focused on relatively low-frequency data, on a monthly frequently or less. This paper takes a slightly different approach, focusing on both higher-frequency data, at a daily frequency, and more active trading strategies. The paper utilizes data obtained for the US Equity REIT sector and compares the performance of a variety of trading strategies commonly adopted by active traders. The analysis utilizes data source from Bloomberg and considers the viability of active trading strategies in the US Equity REIT sector. The strategies included consider approaches such as Relative Strength, Momentum and Mean Reversion over a variety of time horizons. The analysis also examines more fundamentally based measures, including Price to FFO (Funds from Operations).