Improving Time Series Models Prediction Based On Empirical Mode Decomposition Using Stock Market Data
Time series analysis and prediction is a very important and active research area. In this age of profuse data generation, proper use of available data has become crucial in forecasting and decision making. This thesis presents the research study involving the development of five advanced forecasting...
محفوظ في:
المؤلف الرئيسي: | Hossain, Mohammad Raquibul |
---|---|
التنسيق: | أطروحة |
اللغة: | English |
منشور في: |
2021
|
الموضوعات: | |
الوصول للمادة أونلاين: | http://eprints.usm.my/53227/1/MOHAMMAD%20RAQUIBUL%20HOSSAIN%20-%20TESIS24.pdf http://eprints.usm.my/53227/ |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Empirical Mode Decomposition based on Theta Method for Forecasting Daily Stock Price
بواسطة: Hossain, Mohammad Raquibul, وآخرون
منشور في: (2020) -
Empirical mode decomposition based on theta
method for forecasting daily stock price
بواسطة: Hossain, Mohammad Raquibul, وآخرون
منشور في: (2020) -
Forecasting Performance Of Nonlinear And Nonstationary Stock Market Data Using Empirical Mode Decomposition
بواسطة: Awajan, Ahmad Mohammad Al-Abd
منشور في: (2018) -
Application of empirical mode decomposition in improving group method of data handling.
بواسطة: Abdul Razif, Nur Rafiqah, وآخرون
منشور في: (2023) -
Application of Empirical Mode Decomposition with Local Linear
Quantile Regression in Financial Time Series Forecasting
بواسطة: M. Jaber, Abobaker, وآخرون