Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment

Massimo Guidolin and Stuart Hyde

Computational Statistics & Data Analysis, 2012, vol. 56, issue 11, 3546-3566

Abstract: In a typical strategic asset allocation problem, the out-of-sample certainty equivalent returns for a long-horizon investor with constant relative risk aversion computed from a range of vector autoregressions (VARs) are compared with those from nonlinear models that account for bull and bear regimes. In a horse race in which models are not considered in their individuality but instead as an overall class, it is found that a power utility investor with a relative risk aversion of 5 and a 5 year horizon is ready to pay as much as 8.1% in real terms to be allowed to select models from the Markov switching (MS) class, while analogous calculation for the whole class of expanding window VARs leads to a disappointing 0.3% per annum. Most (if not all) VARs cannot produce portfolio rules, hedging demands, or out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks.

Keywords: Predictability; Strategic asset allocation; Markov switching; Vector autoregressive models; Out-of-sample performance (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:11:p:3546-3566

DOI: 10.1016/j.csda.2010.10.006

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