کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
388184 | 660920 | 2009 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Forecasting volatility based on wavelet support vector machine
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
One of the challenging problems in forecasting the conditional volatility of stock market returns is that general kernel functions in support vector machine (SVM) cannot capture the cluster feature of volatility accurately. While wavelet function yields features that describe of the volatility time series both at various locations and at varying time granularities, so this paper construct a multidimensional wavelet kernel function and prove it meeting the mercer condition to address this problem. The applicability and validity of wavelet support vector machine (WSVM) for volatility forecasting are confirmed through computer simulations and experiments on real-world stock data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 2, Part 2, March 2009, Pages 2901–2909
Journal: Expert Systems with Applications - Volume 36, Issue 2, Part 2, March 2009, Pages 2901–2909
نویسندگان
Ling-Bing Tang, Ling-Xiao Tang, Huan-Ye Sheng,