Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach

Afees Salisu, Rangan Gupta and Elie Bouri ()
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Elie Bouri: School of Business, Lebanese American University, Lebanon

No 202211, Working Papers from University of Pretoria, Department of Economics

Abstract: We examine the power of global economic conditions (GECON) in forecasting the daily return volatility of various international Real Estate Investment Trusts (REITs) indices. To this end, we use the GARCH-MIDAS framework due to the mixed frequencies of the variables under study and given its merit of circumventing the problems of information loss due to data aggregation and biases through data disaggregation. The results show evidence of forecast gains in the model that accommodates GECON, and significant in-sample forecastability where improvements in global economic conditions lower the risk associated with the international REITs particularly in the US and emerging markets. Further analysis shows the possibility of gaining higher returns on REITs by exploiting the information contents of GECON. A robustness analysis indicates that other measures of global economic conditions such as Global Weakness Index (GWI) and Global Intensity Index (GII) contain lower forecasting power than GECON but with significant improvements in their forecast outcomes when combined with the latter using the principal components analysis. Consequently, monitoring the global economic dynamics via GECON as well as other indices (GWI and GII) is crucial for optimal investment decisions.

Keywords: REITs volatility; global economic conditions; mixed data analysis; GARCH-MIDAS model; forecasting (search for similar items in EconPapers)
JEL-codes: C32 C53 E32 R30 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2022-02
New Economics Papers: this item is included in nep-for, nep-mac and nep-rmg
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Journal Article: Testing the forecasting power of global economic conditions for the volatility of international REITs using a GARCH-MIDAS approach (2023)
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