Predicting International Equity Returns: Evidence from Time-Varying Parameter Vector Autoregressive Models

Rangan Gupta, Florian Huber and Philipp Piribauer ()

No 201826, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper, we forecast monthly stock returns of eight advanced economies using a time varying parameter vector autoregressive model (TVP-VAR). Compared to standard TVP-VARs, our proposed model automatically detects whether time-variation in the parameters is needed through the introduction of a latent threshold process that is driven by the absolute size of parameter changes. The advantage of this framework is that it can dynamically detect whether a given regression coefficient is constant or time-varying during distinct time periods. We moreover compare the performance of this model with a wide range of nested alternative time-varying and constant parameter VAR models. Our results indicate that the threshold TVP-VAR outperforms its competitors in terms of point and density forecasts. A portfolio allocation exercise confirms the superiority of our proposed framework. In addition, a copula-based analysis also indicates that it pays off to adopt a multivariate modeling framework, especially during periods of stress, like the recent financial crisis.

Keywords: International equity markets; Time-varying vector autoregression; Point and density forecasts; Portfolio allocation (search for similar items in EconPapers)
JEL-codes: C32 G10 G17 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2018-04
New Economics Papers: this item is included in nep-for and nep-mac
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Journal Article: Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201826

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