What Does the Yield Curve Tell Us About Exchange Rate Predictability?

Chen, Yu-Chin; Tsang, Kwok Ping

doi:10.2139/ssrn.1731787

Cited by 35 publications

(41 citation statements)

References 45 publications

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“…14 Possible explanations include: the presence of a time-varying risk premium (Fama, 1984;Backus, Foresi and Telmer, 2001); estimation biases (Bekaert and Hodrick, 2001); imprecise standard errors Bollerslev, 2000, Rossi, 2007a); and small samples (Chinn and Meredith, 2004, who …nd positive evidence in longer samples, and Chen and Tsang, 2011, who pool information from the whole term structure). 15 The half-life measures how many time periods it takes for the e¤ects of a shock to PPP to decrease by 50%.…”

Section: (B) Price and In ‡Ation Di¤erentialsmentioning

confidence: 99%

Exchange Rate Predictability

Rossi

2013

Journal of Economic Literature

507

338

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The main goal of this article is to provide an answer to the question: "Does anything forecast exchange rates, and if so, which variables?". It is well known that exchange rate ‡uctuations are very di¢ cult to predict using economic models, and that a random walk forecasts exchange rates better than any economic model (the Meese and Rogo¤ puzzle). However, the recent literature has identi…ed a series of fundamentals/methodologies that claim to have resolved the puzzle. This article provides a critical review of the recent literature on exchange rate forecasting and illustrates the new methodologies and fundamentals that have been recently proposed in an upto-date, thorough empirical analysis. Overall, our analysis of the literature and the data suggests that the answer to the question: "Are exchange rates predictable?" is, "It depends" -on the choice of predictor, forecast horizon, sample period, model, and forecast evaluation method. Predictability is most apparent when one or more of the following hold: the predictors are Taylor rule or net foreign assets, the model is linear, and a small number of parameters are estimated. The toughest benchmark is the random walk without drift.

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Section: (B) Price and In ‡Ation Di¤erentialsmentioning

confidence: 99%

Exchange Rate Predictability

Rossi

2013

Journal of Economic Literature

507

338

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“…Combining monetary fundamentals and policy, with yield curve factors -which reflect expectations and risk premiums -further helps to explain exchange rate movements and excess currency returns one month to two years ahead, outperforming the random walk (Chen and Tsang, 2011). Conversely, as Engel and West (2005) show, exchange rates are useful in forecasting future monetary policy, consistent with the idea that the exchange rate reflects the market's expectations of monetary policy.…”

mentioning

confidence: 88%

Macro Approaches to Foreign Exchange Determination

Chinn

2012

Handbook of Exchange Rates

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“…7 If the R-squared of equation (5) increases, or the out-of-sample relative Mean Square Prediction Error (MSPE) decreases with time horizon h, it is taken as evidence that the exchange rate converges to its long-run value over time and therefore is predictable at long horizons.…”

Section: Long-horizon Regressions Under E-w Explanationmentioning

confidence: 99%

Can Long-Horizon Forecasts Beat the Random Walk Under the Engel-West Explanation?

Engel¹,

Wang²,

Wu³

2009

gwp

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Engel and West (EW, 2005) argue that as the discount factor gets closer to one, presentvalue asset pricing models place greater weight on future fundamentals. Consequently, current fundamentals have very weak forecasting power and asset prices in these models appear to follow approximately a random walk. We connect the Engel-West explanation to the studies of long-horizon regressions. As expected, 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 when the discount factor is large. However, when EW's assumptions are violated in a particular way, our analytical and simulation results show that long-horizon regressions can have substantial power, even when the discount factor is close to one and the power of short-horizon regressions is low. One example for the substantial power improvement at long horizons is the existence of unobservable stationary fundamentals, such as the risk premium, in present-value asset pricing models. Consistent with our model's prediction, we find that the risk premium calculated from survey data can forecast exchange rates at long horizons. These results suggest that the presence of stationary unobservable fundamentals may have played a large role in the power improvement of long-horizon regressions found in empirical studies.JEL codes: F31, F41, G12, G15

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What Does the Yield Curve Tell Us About Exchange Rate Predictability?

Cited by 35 publications

References 45 publications

Exchange Rate Predictability

Exchange Rate Predictability

Macro Approaches to Foreign Exchange Determination

Can Long-Horizon Forecasts Beat the Random Walk Under the Engel-West Explanation?

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