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The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes

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  • Paskalis Glabadanidis

Abstract

I present evidence that a moving average (MA) trading strategy dominates buying and holding the underlying asset in a mean-variance sense using monthly returns of value-weighted and equal-weighted US REIT indexes over the period January 1980 until December 2010. The abnormal returns are largely insensitive to the four Carhart factors and produce economically and statistically significant alphas of between 10 and 15% per year after transaction costs. This performance is robust to different lags of the MA and in subperiods while investor sentiment, liquidity risks, business cycles, up and down markets, and the default spread cannot fully account for its performance. The MA strategy works just as well with randomly generated returns and bootstrapped returns. The substantial market timing ability of the MA strategy appears to be the main driver of the abnormal returns. The returns to the MA strategy resemble the returns of an imperfect at-the-money protective put strategy relative to the underlying portfolio. The lagged signal to switch has substantial predictive power over the subsequent return of the REIT index. The MA strategy avoids the sharp downturn at the beginning of 2008 and substantially outperforms the cumulative returns of the buy-and-hold strategy using all of the 20 REIT indexes. The results from applying the MA strategy with 274 individual REITs largely corroborate the findings for the REIT indexes.

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  • Paskalis Glabadanidis, 2014. "The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes," International Review of Finance, International Review of Finance Ltd., vol. 14(2), pages 161-202, June.
  • Handle: RePEc:bla:irvfin:v:14:y:2014:i:2:p:161-202
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    File URL: http://hdl.handle.net/10.1111/irfi.12018
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    5. Yung-Ching Tseng & Wo-Chiang Lee, 2016. "Investor Sentiment and ETF Liquidity - Evidence from Asia Markets," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 6(1), pages 1-5.
    6. Liu, Xiaojia & An, Haizhong & Wang, Lijun & Guan, Qing, 2017. "Quantified moving average strategy of crude oil futures market based on fuzzy logic rules and genetic algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 444-457.

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