کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
968808 931662 2008 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Forecasting gold price changes: Rolling and recursive neural network models
موضوعات مرتبط
علوم انسانی و اجتماعی اقتصاد، اقتصادسنجی و امور مالی اقتصاد و اقتصادسنجی
پیش نمایش صفحه اول مقاله
Forecasting gold price changes: Rolling and recursive neural network models
چکیده انگلیسی

This paper analyzes recursive and rolling neural network models to forecast one-step-ahead sign variations in gold price. Different combinations of techniques and sample sizes are studied for feed forward and ward neural networks. The results shows the rolling ward networks exceed the recursive ward networks and feed forward networks in forecasting gold price sign variation. The results support the use of neural networks with a dynamic framework to forecast the gold price sign variations, recalculating the weights of the network on a period-by-period basis, through a rolling process. Our results are validated using the block bootstrap methodology with an average sign prediction of 60.68% with a standard deviation of 2.82% for the rolling ward net.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multinational Financial Management - Volume 18, Issue 5, December 2008, Pages 477–487
نویسندگان
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