کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5097134 | 1376572 | 2007 | 41 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Can the random walk model be beaten in out-of-sample density forecasts? Evidence from intraday foreign exchange rates
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
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![عکس صفحه اول مقاله: Can the random walk model be beaten in out-of-sample density forecasts? Evidence from intraday foreign exchange rates Can the random walk model be beaten in out-of-sample density forecasts? Evidence from intraday foreign exchange rates](/preview/png/5097134.png)
چکیده انگلیسی
It has been documented that random walk outperforms most economic structural and time series models in out-of-sample forecasts of the conditional mean dynamics of exchange rates. In this paper, we study whether random walk has similar dominance in out-of-sample forecasts of the conditional probability density of exchange rates given that the probability density forecasts are often needed in many applications in economics and finance. We first develop a nonparametric portmanteau test for optimal density forecasts of univariate time series models in an out-of-sample setting and provide simulation evidence on its finite sample performance. Then we conduct a comprehensive empirical analysis on the out-of-sample performances of a wide variety of nonlinear time series models in forecasting the intraday probability densities of two major exchange rates-Euro/Dollar and Yen/Dollar. It is found that some sophisticated time series models that capture time-varying higher order conditional moments, such as Markov regime-switching models, have better density forecasts for exchange rates than random walk or modified random walk with GARCH and Student-t innovations. This finding dramatically differs from that on mean forecasts and suggests that sophisticated time series models could be useful in out-of-sample applications involving the probability density.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 141, Issue 2, December 2007, Pages 736-776
Journal: Journal of Econometrics - Volume 141, Issue 2, December 2007, Pages 736-776
نویسندگان
Yongmiao Hong, Haitao Li, Feng Zhao,