Forecasting Exchange Rate by Finding Trend Change
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In this article we propose a new type of time trend forecasting algorithm (TFA) which effectively incorporates a recent trend change into the forecaster by finding a proper trend from “recent length l segment” of exchange rate data. It will be shown that choice of l is critical for successful implementation of TFA and that predictive error-based method works pretty well for a proper choice of l. In addition monitoring tool is provided for checking the validity of the forecaster. An empirical study for exchange rate forecasting of Korea Won (KRW) to US Dollar (USD) is done for evaluation of the algorithm, which verifies usefulness of TFA particularly for yearly forecasting.
Abstract
In this article we propose a new type of time trend forecasting algorithm (TFA) which effectively incorporates a recent trend change into the forecaster by finding a proper trend from “recent length l segment” of exchange rate data. It will be shown that choice of l is critical for successful implementation of TFA and that predictive error-based method works pretty well for a proper choice of l. In addition monitoring tool is provided for checking the validity of the forecaster. An empirical study for exchange rate forecasting of Korea Won (KRW) to US Dollar (USD) is done for evaluation of the algorithm, which verifies usefulness of TFA particularly for yearly forecasting.
참고문헌 (17)
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