Maizah Hura Ahmad
Universiti Teknologi Malaysia
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Publication
Featured researches published by Maizah Hura Ahmad.
THE 2ND ISM INTERNATIONAL STATISTICAL CONFERENCE 2014 (ISM-II): Empowering the Applications of Statistical and Mathematical Sciences | 2015
Siti Roslindar Yaziz; Noor Azlinna Azizan; Maizah Hura Ahmad; Roslinazairimah Zakaria; Manju Agrawal; John Boland
Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.
Journal of Interdisciplinary Mathematics | 2010
Norizan Mohamed; Maizah Hura Ahmad; Zuhaimy Ismail; Khairil Anuar Arshad
Abstract This paper presents the use of two artificial neural networks models, namely the multilayer feedforward neural network (MLFF) and the recurrent neural network (RNN) are applied for Malaysia’s load forecasting. For this purpose, a half hourly load data is divided equally into three distinct sets for training, validation and testing. We use backpropagation as the learning algorithm and the sigmoid function as the transfer function for both hidden land output layers. The forecasting performances of were compared between these two models. We use the sum squared error (SSE) as the measure of performance and the correlation coefficient r , as the measure of relationship between the actual and the predicted values. Results show that, multilayer feedforward neural network (MLFF) and recurrent neural network (RNN) have comparable accuracy but the sum squared error for multilayer feedforward neural network (MLFF) is lower, thus making it better model than recurrent neural network (RNN).
Journal of Physics: Conference Series | 2017
Siti Roslindar Yaziz; Roslinazairimah Zakaria; Maizah Hura Ahmad
The model of Box-Jenkins - GARCH has been shown to be a promising tool for forecasting higher volatile time series. In this study, the framework of determining the optimal sample size using Box-Jenkins model with GARCH is proposed for practical application in analysing and forecasting higher volatile data. The proposed framework is employed to daily world gold price series from year 1971 to 2013. The data is divided into 12 different sample sizes (from 30 to 10200). Each sample is tested using different combination of the hybrid Box-Jenkins - GARCH model. Our study shows that the optimal sample size to forecast gold price using the framework of the hybrid model is 1250 data of 5-year sample. Hence, the empirical results of model selection criteria and 1-step-ahead forecasting evaluations suggest that the latest 12.25% (5-year data) of 10200 data is sufficient enough to be employed in the model of Box-Jenkins - GARCH with similar forecasting performance as by using 41-year data.
ADVANCES IN INDUSTRIAL AND APPLIED MATHEMATICS: Proceedings of 23rd Malaysian National Symposium of Mathematical Sciences (SKSM23) | 2016
Pung Yean Ping; Maizah Hura Ahmad; Norazlina Ismail
As the interaction between international and domestic financial markets increases, the interaction between gold market and financial markets also increases. Today, the financial attributes of gold play a more evidence role in dominating the gold price. Taking into account time-varying and dynamic properties of volatility spillover effect in the financial markets, this paper investigates the time-varying volatility relationship between gold markets and U.S. dollar by using the bivariate-BEKK. This paper also investigate whether gold volatility is significantly affected by its own pre-fluctuations, its aggregation and lasting properties, and the bi-directional volatility spillover between the gold market and U.S. dollar.
INTERNATIONAL CONFERENCE ON QUANTITATIVE SCIENCES AND ITS APPLICATIONS (ICOQSIA 2014): Proceedings of the 3rd International Conference on Quantitative Sciences and Its Applications | 2014
Pung Yean Ping; Maizah Hura Ahmad
World gold price is a popular investment commodity. The series have often been modeled using univariate models. The objective of this paper is to show that there is a co-movement between gold price and USD foreign exchange rate. Using the effect of the USD foreign exchange rate on the gold price, a model that can be used to forecast future gold prices is developed. For this purpose, the current paper proposes a multivariate GARCH (Bivariate GARCH) model. Using daily prices of both series from 01.01.2000 to 05.05.2014, a causal relation between the two series understudied are found and a bivariate GARCH model is produced.
Mathematika | 2006
Norliza Adnan; Maizah Hura Ahmad; Robiah Adnan
Journal of Applied Sciences | 2011
Siti Roslindar Yaziz; Maizah Hura Ahmad; Lee Chee Nian; Noryanti Muhammad
Mathematika | 2010
Norizan Mohamed; Maizah Hura Ahmad; Zuhaimy Ismail; [No Value] Suhartono
Journal of Educational Multimedia and Hypermedia | 2008
Kok Boon Shiong; Baharuddin Aris; Maizah Hura Ahmad; Mohamad Bilal Ali; Jamalludin Harun; Zaidatun Tasir
World applied sciences journal | 2013
Nur Adilah Abd Jalil; Maizah Hura Ahmad; Norizan Mohamed