Out-of-sample exchange rate predictability with Taylor rule fundamentals

By Tanya Molodtsova, David H. Papell. 2009

402 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e01069b16302640075154d18ae2be8bda4754e4a

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In Economics and Econometrics

Citations in the corpus

The Continuing Puzzle of Short Horizon Exchange Rate Forecasting (2008, methodology): “Using only single-country equations and the asymptotic CW test statistic, Molodtsova and Papell (2008) conclude that the Taylor rule outperforms the driftless random walk for 10 out of 12 currencies for forecasts one period ahead.”
What Does the Yield Curve Tell Us about Exchange Rate Predictability? (2013, neutral): “13 See Engel and West (2005), Molodtsova and Papell (2008), and Wang and Wu (2009) as examples.”
On the sources of uncertainty in exchange rate predictability (2018, positive): “We obtain monthly data via a quadratic-match-average interpolation method from quartely data, as in Molodtsova and Papell (2009).”
Out-of-Sample Forecast Tests Robust to the Choice of Window Size (2011, neutral): “The column labeled “Test based on single R” in Table 12 reports the empirical results in the literature based on a window size R equal to 120, the same window size as used in Molodtsova and Papell (2009).”
Taylor Rules with Real-Time Data: A Tale of Two Countries and One Exchange Rate (2008, methodology): “Molodtsova and Papell (2008) use quasi-revised data and find evidence of predictability at the 10 percent significance level with and without smoothing, but only with heterogeneous coefficients and a symmetric specification.”
Exchange Rate Predictability (2013, neutral): “Slightly more positive ndings have been reported by Clark and West (2006) at short-horizons, and Molodtsova and Papell (2009) for some countries.13 Insample empirical evidence is not favorable to UIRP either.”
Exchange rate predictability in a changing world (2014, neutral): “and Papell (2009) and Rossi (2013) find that empirical exchange rate models conditioned on an information set from Taylor rules outperform the random walk benchmark in out-ofsample forecasting, especially at short-horizons.”
Can Oil Prices Forecast Exchange Rates (2011, neutral): “There is, however, some empirical evidence that models with Taylor rule fundamentals may have some predictive ability (Wang and Wu, 2008, Molodtsova and Papell, 2009; and Molodtsova, Nikolsko-Rzhevskyy and Papell, 2008).”
Reality Checks and Comparisons of Nested Predictive Models (2012, background): “…Kilian (1999); Butler, Grullon and Weston (2005); Sarno, et al. (2005); Cooper and Gulen (2006); Guo (2006); Rapach and Wohar (2006); Bruneau, et al. (2007); Rapach and Strauss (2007); Moench (2008); Billmeier (2009); Chen, et al. (2009); Hendry and Hubrich (2009); and Molodtsova and Papell (2009).”
Risk Appetite and Exchange Rates (2010, neutral): “Molodtsova and Papell (2008) introduce a Taylor rule as a structural fundamental and exhibit evidence that their single equation framework outperforms driftless random walk for 10 out of 12 countries at monthly forecast horizons.”