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Can long-horizon forecasts beat the random walk under the Engel-West explanation?

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  • Charles Engel
  • Jian Wang
  • Jason Wu

Abstract

Engel and West (EW, 2005) argue that as the discount factor gets closer to one, present-value asset pricing models place greater weight on future fundamentals. Consequently, current fundamentals have very weak forecasting power and exchange rates appear to follow approximately a random walk. We connect the Engel-West explanation to the studies of exchange rates with long-horizon regressions. We find that under EW's assumption that fundamentals are I(1) and observable to the econometrician, long-horizon regressions generally do not have significant forecasting power. However, when EW's assumptions are violated in a particular way, our analytical results show that there can be substantial power improvements for long-horizon regressions, even if the power of the corresponding short-horizon regression is low. We simulate population R squared for long-horizon regressions in the latter setting, using Monetary and Taylor Rule models of exchange rates calibrated to the data. Simulations show that long-horizon regression can have substantial forecasting power for exchange rates.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Dallas in its series Globalization and Monetary Policy Institute Working Paper with number 36.

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Date of creation: 2009
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Handle: RePEc:fip:feddgw:36

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Keywords: Foreign exchange rates ; Financial markets ; Asset pricing ; Forecasting ; Random walks (Mathematics) ; Regression analysis;

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Cited by:
  1. Jian Wang & Jason J. Wu, 2009. "The Taylor rule and forecast intervals for exchange rates," International Finance Discussion Papers 963, Board of Governors of the Federal Reserve System (U.S.).

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