This paper presents a method to test the volatility predictions of the textbook asset-pricing exchange rate model, which imposes minimal structure on the data and does not commit to a choice of exchange rate “fundamentals.” Our method builds on existing tests of excess volatility in asset prices, combining them with a procedure that extracts unobservable fundamentals from survey-based exchange rate expectations. We apply our method to data for the three major exchange rates since 1984 and find broad evidence of excess exchange rate volatility with respect to the predictions of the canonical asset-pricing model in an efficient market.
This paper investigates the behavior of Korean trade flows during the last three decades and presents estimates of aggregate export and import equations. In particular, it considers different choices for scale and price variables and assesses the relative merits of these alternative specifications in terms of stability and forecasting performance. It also provides an assessment of the drastic change in the geographical destination of Korean exports during the 1990s.
Several authors have recently investigated the predictability of exchange rates by fitting a sequence of long-horizon error-correction regressions. By considering the implied vector error-correction model, we show that little is to be gained from estimating such regressions for horizons greater than one time period. We also show that in small to medium samples the long-horizon procedure gives rise to spurious evidence of predictive power. A simulation study demonstrates that even when using this technique on two independent series, estimates, diagnostic statistics and graphical evidence incorrectly suggest a high degree of predictability of the dependent variable.
When constructing hedged interest rate arbitrage portfolios for basket currencies, two issues arise: first, how are the unknown future basket weights optimally forecasted from past exchange rate data? And, second, how is risk—in terms of the conditional variance of expected profits from the interest rate arbitrage portfolio—appropriately measured when the basket weights are time-varying? Answers to these questions are provided within a time-varying parameter modeling framework estimated through the Kalman filter. An empirical application is devoted to the experience of the Thai baht currency basket (January 1992–February 1997).