

Articles
by
Mohd Tahir Ismail 
Total Records (
3 ) for
Mohd Tahir Ismail 





Mohd Tahir Ismail
,
Lee Siew Yong
and
Lim Ying Ming


This study investigates the relationship between MYR/USD exchange rate and 10 sectoral stock
markets indices after the pegging period which is starting from August 2005 to December 2015. The Vector
Auto Regressive or Vector Error Correction Model (VAR/VECM) framework is used in this study, nonetheless
unit root tests (ADF and KPSS) as well as cointegration test will be implemented before using VAR/VECM
framework. Since, there are longrun relationship between the significant sectoral markets which have been
chosen from regression analysis, VECM is employed. Meanwhile, the results from Granger causality test
indicates that there exists positive unidirectional from exchange rate to consumer product, finance and industrial
product respectively. In short, high exchange rate has affected these three sectoral stock markets over the
period under study. However, in longterm forecast, the variance decomposition results have shown that the
impact of exchange rate on each sectoral stock price is ranging from 1.8715.74%. 




Samsul Ariffin Abdul Karim
,
Mohd Tahir Ismail
,
Mahmod Othman
,
Mohd Faris Abdullah
,
Mohammad Khatim Hasan
and
Jumat Sulaiman


Missing data imputation is an important task in statistical and sciences discipline. Solar radiation data
obtained from the solar tracker does not complete and some data are missing due to human error in handling
the instrument or the failure of the instrument. Thus, missing data imputation can be used to predict and
estimate the unknown value of the solar radiation at certain time. This study will estimate the solar radiation by
using rational cubic Ball spline function with three parameters. The interpolating rational Ball spline is able to
give good result based on quadratic regression model. 





S. Al Wadi
,
Mohd Tahir Ismail
and
Samsul Ariffin Addul Karim


Recently, the Fast Fourier Transforms (FFT) and the Discrete Wavelet Transforms (DWT) are two time series filtering methods that are used to represent the fluctuations of stocks market. In general the basic wavelet function, Haar wavelet transform is a mathematical function that cut off the data into different frequency components, satisfies some of mathematical requirements and it has better advantages than the traditional Fourier series in analyzing financial data. Fourier transform appears to have some problem associate with its transformation because it measures the data as a function of position (in frequency domain) without consider the time while wavelet transform displays their correlation as a function of scale and time (localized in both). In this study we use financial time series data taking from the Amman Stocks Market (Jordan) for a certain period of time in order to understand the similarities and dissimilarities between both of them. We look for point of abrupt changes, closing price and normalized data. In addition, some numerical results will be presented using Matlab programming. 





