Modified Box-Jenkins and GARCH for forecasting highly volatile time series data

The Box-Jenkins model has widely been used either as the forecasting, benchmarking or as the integrated model in the current research of time series. The Box-Jenkins modelling is one of the most powerful forecasting techniques available in research practice of the time series analysis. Most of the t...

وصف كامل

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Siti Roslindar, Yaziz
التنسيق:	أطروحة
اللغة:	الإنجليزية
منشور في:	2019
الموضوعات:	Q Science (General) T Technology (General)
الوصول للمادة أونلاين:	http://umpir.ump.edu.my/id/eprint/29284/1/Modified%20box-jenkins%20and%20garch%20for%20forecasting%20highly%20volatile%20time%20series%20data.wm.pdf

مواد مشابهة

SWGARCH : an enhanced GARCH model for time series forecasting
حسب: Shbier, Mohammed Z. D
منشور في: (2017)

Modelling and forecasting volatile data by using ARIMA and GARCH models
حسب: Miswan, Nor Hamizah
منشور في: (2013)

Symmetric and asymmetric garch models for forecasting the prices of gold
حسب: Pung, Yean Ping
منشور في: (2013)

Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
حسب: Mahpol, Khairil Asmani
منشور في: (2005)

A hybrid of bekk garch with neural network for modeling and forecasting time series
حسب: Pung, Yean Ping
منشور في: (2021)

A hybrid multivariate time series m odel for forecasting m eteorological data in peninsular malaysia
حسب: Norrulashikin, Siti Mariam
منشور في: (2018)

A hybrid Box-Jenkins and decomposition model drought forecasting in Kuala Terengganu
حسب: Ho, Mee Chyong
منشور في: (2013)

A hybrid Box-Jenkins and decomposition model for drought forecasting in Kuala Terengganu
حسب: Ho, Mee Chyong
منشور في: (2013)

Naive weight fuzzy time series for forecasting in a case study for stationary and non-stationary data
حسب: Efendi , Riswan
منشور في: (2010)

Forecasting Stock Market Volatility Using Wavelet Transformation Algorithm Of Garch Model
حسب: Audu, Buba
منشور في: (2017)

Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
حسب: Siow, Kent Woh
منشور في: (2020)

Time arrival in series forecasting model for tourist National Park Kuala Tahan, Pahang
حسب: Megat Muhammad Afif, Megat Muainuddin
منشور في: (2021)

Forecasting natural rubber production in Malaysia: box-jenkins vs artificial neural network method / Liyana Husna Shamsudin and Nur Fadhliana Ithnin
حسب: Shamsudin, Liyana Husna, وآخرون
منشور في: (2018)

Parameter estimation of box-jenkins model using genetic algorithm
حسب: Rusdi, Nur'afifah
منشور في: (2013)

Implementation of genetic algorithm in model identification of box-jenkins methodology
حسب: Md. Maarof, Mohd. Zulariffin
منشور في: (2013)

Implementation of genetic algorithm in model identification of box-jenkins methodology
حسب: Md. Maarof, Mohd. Zulariffin
منشور في: (2013)

A Hybrid Markov Switching Garch Model Approach For Improving Volatility Dynamics
حسب: Hossain, Md Jamal
منشور في: (2021)

Pembentukan Model Stokastik Box-Jenkins dan Aplikasi dalam Industri Utiliti
حسب: Syariza, Abdul Rahman
منشور في: (2003)

The enhanced group method of data handling models for time series forecasting
حسب: Samsudin, Ruhaidah
منشور في: (2012)

Multivariate time series modelling of taxes revenue in Nigeria
حسب: Baba Gimba, Alhassan
منشور في: (2022)

Symmetric and asymmetric garch models for forecasting the prices of gold
حسب: Pung, Yean Ping
منشور في: (2013)

Time horizon volatility forecasting of Malaysian property stocks
حسب: Gooi, Leong Mow
منشور في: (2019)

The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
حسب: Sallehuddin, Roselina, وآخرون
منشور في: (2009)

Improved models in fuzzy time series for forecasting
حسب: Sadaei, Hossein Javedani
منشور في: (2013)

Generalised Autoregressive Conditional Heteroscedasticity (Garch) Models For Stock Market Volatility
حسب: Choo, Wei Chong
منشور في: (1998)

Application of Arima and Garch models in forecasting crude oil prices
حسب: Lee, Chee Nian
منشور في: (2009)

Hybridization of nonlinear and linear models for time series forecasting
حسب: Salleh@Sallehuddin, Roselina
منشور في: (2010)

Role of high-frequency data, distribution assumption and trading volume in volatility forecasting in China stock market
حسب: Liu, Min
منشور في: (2021)

Error magnitude and directional accuracy for time series forecasting evaluation
حسب: Nor, Maria Elena
منشور في: (2014)

Detecting Structural Break In Commodity Time Series Data
حسب: Jatarona , Nurul Najwa
منشور في: (2010)

Combining group method of data handling models using artificial bee colony algorithm for time series forecasting
حسب: Yahya, Nurhaziyatul Adawiyah
منشور في: (2019)

Comparative performance of ARIMA and GARCH models in modelling and forecasting volatility of Kuala Lumpur composite index / Hasma Basyirah Bakar , Nik Sofiah Nik Rusdi and Nurul Athirah Rushdi
حسب: Bakar, Hasma Basyirah, وآخرون
منشور في: (2019)

Combine holts winter and support vector machines in forecasting time serie
حسب: Alfa, Mohammed Salisu
منشور في: (2013)

Combine holts winter and support vector machines in forecasting time series
حسب: Salisu, Alfa Mohammed
منشور في: (2013)

Time series modeling and designing and artificial neural network (ANN) for revenue forecasting
حسب: Mohd Yusof, Norfadzlia
منشور في: (2006)

Developing defuzzifying method of fuzzy time-variant series for forecasting product demand
حسب: Saeed, Akbarnatajbisheh
منشور في: (2013)

Time series forecasting of airline passenger no-shows using fir neural network
حسب: Muhammad Hussein, Muhammad Zaly Shah
منشور في: (2002)

Time series modeling and designing of artifical neural network (ANN) for revenue forecasting
حسب: Mohd. Yusof, Norfadzlia
منشور في: (2005)

Measuring, Monitoring And Forecasting System For Carbon Monoxide Concentrations
حسب: Raji, Usharani
منشور في: (2005)

Neuromorphic learning machine based on stochastic reservoir computing for time series data processing and classification
حسب: Saw, Chia Yee
منشور في: (2023)