Point, interval and density forecasts of exchange rates with time varying parameter models

Angela Abbate () and Massimiliano Marcellino

Journal of the Royal Statistical Society Series A, 2018, vol. 181, issue 1, 155-179

Abstract: We explore whether modelling parameter time variation improves the point, interval and density forecasts of nine major exchange rates vis‐à‐vis the US dollar over the period 1976–2015. We find that modelling parameter time variation is needed for an accurate calibration of forecast confidence intervals and is better suited at long horizons and in high volatility periods. The biggest forecast improvements are obtained by modelling time variation in the volatilities of the innovations, rather than in the slope parameters. We do not find evidence that parameter time variation helps to unravel exchange rate predictability by macroeconomic fundamentals. However, an economic evaluation of the various forecast models reveals that controlling for parameter time variation and macroeconomic fundamentals leads to higher portfolios returns, and to higher utility values for investors.

Date: 2018
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Citations: View citations in EconPapers (17)

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https://doi.org/10.1111/rssa.12273

Related works:
Working Paper: Point, interval and density forecasts of exchange rates with time-varying parameter models (2016)
Working Paper: Point, interval and density forecasts of exchange rates with time-varying parameter models (2016)
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