Can Linear Predictability Models Time Bull and Bear Real Estate Markets? Out-of-Sample Evidence from REIT Portfolios

被引:10
|
作者
Bianchi, Daniele [1 ]
Guidolin, Massimo [1 ,2 ]
机构
[1] Bocconi Univ, Dept Finance, I-20136 Milan, Italy
[2] Bocconi Univ, IGIER, I-20136 Milan, Italy
来源
关键词
REIT returns; Predictability; Strategic asset allocation; Markov switching; Vector autoregressive models; Out-of-sample performance; RETURNS; VOLATILITY; US; INVESTMENTS; PERFORMANCE; ALLOCATION;
D O I
10.1007/s11146-013-9411-6
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
A recent literature has shown that REIT returns contain strong evidence of bull and bear dynamic regimes that may be best captured using nonlinear econometric models of the Markov switching type. In fact, REIT returns would display regime shifts that are more abrupt and persistent than in the case of other asset classes. In this paper we ask whether and how simple linear predictability models of the vector autoregressive (VAR) type may be extended to capture the bull and bear patterns typical of many asset classes, including REITs. We find that nonlinearities are so deep that it is impossibile for a large family of VAR models to either produce similar portfolio weights or to yield realized, ex-post out-of-sample long-horizon portfolio performances that may compete with those typical of bull and bear models. A typical investor with intermediate risk aversion and a 5-year horizon ought to be ready to pay an annual fee of up to 5.7 % to have access to forecasts of REIT returns that take their bull and bear dynamics into account instead of simpler, linear forecast.
引用
收藏
页码:116 / 164
页数:49
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