(2005) argue that “any evaluation of these models must necessarily be selective” because “the universe of empirical models that have been examined over the floating period is enormous”. 2 First, in an exercise like this, one has to be selective with respect to model choice as to keep the results manageable. We use only one of the models considered by Meese and Rogoff, the flexible-price monetary model, and justify this approach on three grounds. To explore the possibility that models are more capable of outperforming the random walk over long forecasting horizons, we generate forecasts over horizons ranging between one month and six months. Specifically, we re-examine the puzzle by (i) using measures of direction accuracy and profitability, in addition to the root mean square error, to judge forecasting power (ii) introducing dynamics and (iii) using time-varying parameters. In particular, we endeavor to demonstrate that the “unbeatable random walk” is a myth by exploring the attempts that have been made to resolve the puzzle and by conducting some alternative empirical tests. Two questions arise out of this state of affairs: (i) is failure to outperform the random walk a puzzle that constitutes failure of international monetary economics? and (ii) is the random walk unbeatable in exchange rate forecasting? This paper addresses both of these questions. Emphasis must be placed on the phrase “root mean square error and similar metrics”.
In fact we will find out that claims of the ability to outperform the random walk in terms of the root mean square error are based on flawed procedures. Based on the root mean square error and similar metrics, the Meese and Rogoff results cannot be overturned and are still largely perceived to represent a puzzle. (2005) find that a wide range of models are not successful in forecasting exchange rates. However, Berben and van Dijk, 1998, Berkowitz and Giorgianni, 2001 criticize these studies, particularly the assumption of a stable cointegrating relation. By referring to this paradigm, Meese seems to be questioning the theoretical pillars of conventional exchange rate models.Ĭontrary to what Meese and Rogoff found, some economists claim that it is possible to outperform the random walk (using the root mean square error and similar metrics as criteria) in the medium or long run (for example, Mark, 1995, Chinn and Meese, 1995, MacDonald, 1999, Mark and Sul, 2001). 1 Meese (1990) adds other explanations such as improper modeling of expectations and over-reliance on the representative agent paradigm.
While Voss and Willard (2009) do not consider the forecasting accuracy of exchange rate models, they emphasize the point that monetary policy innovations have asymmetric effects on the exchange rate, which means that imposing the assumption of symmetry may be yet another reason for the failure to outperform the random walk. In their original paper, Meese and Rogoff (1983) attributed the failure to simultaneous equations bias, sampling errors, stochastic movements in the true underlying parameters, misspecification and nonlinearities (hence all of their explanations are related to the underlying econometrics). Several reasons have been put forward for the failure of exchange rate models to outperform the random walk. Empirical studies of exchange rate models typically corroborate the Meese and Rogoff results. Likewise, Bacchetta and van Wincoop (2006) point out that the poor explanatory power of existing exchange rate models is most likely the major weakness of international macroeconomics. Furthermore, Frankel and Rose (1995) argue that the negative results have had a “pessimistic effect” on the field of exchange rate modeling in particular and international finance in general. In another study they describe the finding as “the most researched puzzle in macroeconomics” (Evans and Lyons, 2004). Evans and Lyons (2005) suggest that the Meese–Rogoff finding “has proven robust over the decades”. (2005) describe as a “major puzzle in international finance” the inability of models based on monetary fundamentals to outperform the random walk. This view is still widely accepted to the extent that it is typically argued that the Meese–Rogoff results, which are “yet to be overturned”, constitute a puzzle. Since the publication of the highly-cited paper of Meese and Rogoff (1983), it has become something like an undisputable fact of life that conventional exchange rate determination models cannot outperform the naïve random walk model in out-of-sample forecasting.
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