Wilkie investment model is a stochastic investment model that was built by Wilkie in 1984 and wasupdated in 1995. The model building objective is forecasting. Box-Jenkins method was the basicstructure of Wilkie model. It involves various type of forecasting model. Some model handle station-ary time series such as autoregressive moving average (ARMA) model while some of them handlenon-stationary time series such as autoregressiveintegrated moving average (ARIMA) model. Thereare four sub-models in the Wilkie model which is retail price index model, share dividend yieldmodel, share dividend index model and Consols yield model. In this paper, the Wilkie share pricemodel [4] was apply to Malaysia data in analysing and forecasting FTSE Bursa Malaysia KLCI shareprice index for 36 month ahead from November 2015 to October 2018. Monthly historical data fromJanuary 1996 to October 2015 are use as the base. We use ARIMA model to forecast the shareprice index in Malaysia. ARIMA(0,1,2) model was chosen as the best fit forecasting model. Throughforecasting, we are able to evaluate the performance of the share price index in Malaysia. Keywords:Box Jenkins Model, Forecasting, Share Prices, Wilkie Investment Model.

The current study provides a numerical method that is derived in a backward difference formulation for ordinary differential equations. The proposed method employs a constant step size algorithm of order 12. The backward difference formulation serves as a competitive algorithm for solving ordinary differential equations. In the current study, the backward difference method is used to analyze the dynamics of capital stocks in terms of depreciation rate for the capital–labor ratio. Results provided in this study will validate the accuracy of the backward difference algorithm hence proving it as a viable alternative for analyzing economic problems in the form of ordinary differential equations.

This study examines financial literacy and its association with financial anxiety among the Malaysian population during the Covid-19 pandemic. Specifically, it evaluates the public’s understanding of the government’s financial relief initiatives, such as the Moratorium and EPF withdrawal schemes (i-Sinar, i-Lestari, and i-Citra). Using a survey of 372 respondents, the research measures financial literacy and anxiety levels through a Likert-scale questionnaire incorporating the Financial Anxiety Scale (FAS). Results indicate that only 9% of respondents demonstrated high financial literacy concerning these relief schemes, with factors like age and education significantly influencing literacy levels. The study also reveals a positive correlation between financial literacy and financial anxiety. These findings underscore the need for improved financial education to mitigate financial stress, particularly in crisis situations like the pandemic.

With Malaysia amid transforming itself into a cashless society, digital wallet (e-wallet) providers are playing their part to change people mind sets and ensure that all Malaysians can keep up with digital payment. Due to this, understanding factors that influence the intention behind the usage of e-wallet such as perceived usefulness, perceived ease of use, social influence, security and perceive value is essential. This study applied technology acceptance model to investigate the factors that affect university student’s behavioral intention to use the e-wallet. The study used survey as the data collection method and the total respondents collected are 384 respondents. Data analysis used in this research includes the reliability test, descriptive analysis, variance inflation factor and ordinal logistic regression. The result showed that social influence is the most significant factor that influences behavioral intention to use the e-wallet because respondents are influenced by their family, friends, and advertisement to use the e-wallet.

In reaction to economic uncertainty, there has been a rise in financial anxiety, which is defined as the psychological distress brought on by financial circumstances. The current study looks into how financial literacy—which encompasses financial behaviour, impulsivity, vulnerability, and knowledge—affects financial anxiety among Malaysians. The data gathered from 389 individuals served as the basis for the analysis. The findings show that the most important predictor of financial anxiety is financial vulnerability, most especially the inability to pay monthly obligations. A major contributing factor to reckless spending is the heightened anxiety that accompanies rash financial decisions. On the other hand, forming sound financial practices, such making on-time bill payments and keeping a careful eye on funds, significantly reduces financial stress. The study shows that misunderstandings of financial concepts exacerbate anxiety, underscoring the necessity for proper financial education. Demographic factors including age, gender, and marital status have an impact on financial anxiety. In particular, stress tends to be somewhat higher in younger people, women, and unmarried people. These findings emphasise the need for tailored financial literacy programs that address behaviour and knowledge gaps, promote financial self-control, and provide specific help to excluded groups. The study underscores the critical role that financial literacy plays in mitigating financial anxiety and improving overall financial well-being. It contends that in order to effectively address these challenges, future interventions should prioritise the use of behavioural change strategies and practical financial education.

This study examines the non-linear stochastic Consols yield model for Malaysia inspired by Whitten and Thomas model in year 1999. Whitten and Thomas model consist six subs-models which are price inflation model, wage inflation model, share dividends, share yields, Consols yield and base rate. We only considered the Consols yield model in this study. Aim of this study is to apply the Consols yield inspired Whitten and Thomas model to Malaysian data by using Threshold Autoregressive (TAR) method for data estimation. From that, we able to determine the most suitable model for Consols yield in Malaysia. Hence, we compare our model with the inspired Wilkie model for Malaysia developed by Ishak (2015). The data that we used in this study is a 10-Year Malaysian Government Securities (MGS) yield. The data is based on monthly data from year 2006-2016. Descriptive statistics is used to test the statistical behavior of the data. This study shows a positive kurtosis and skewness which indicates that the distribution has heavier tail than the normal distribution. This study also shows that there is threshold effect on Malaysian Consols yield which is below 3.71% and the most suitable TAR model for Malaysian Consols yield is TAR (3). Keywords: Whitten and Thomas model; consols yield; mgs yield; threshold autoregressive (tar)

Riccati differential equations are one of the most common type of non-linear differential equation used to model real life applications from various fields. The issue when dealing with non-linear differential equations is obtaining their exact solutions. In this research, a three-point block multi-step method in backward difference form is introduced to provide approximated solutions for these Riccati differential equations. The accuracy of the proposed three-point block method will be tested against known numerical methods. The efficiency of the method will apparent when compared with another multi-step method.

Establishing optimal allocation for different stocks in a portfolio via modern portfolio theory is highly depended on the accuracy of the return and risk estimation. For retail investors, technological advancement has made it possible for them to apply thecomplex estimation procedure for decision making. Therefore, this study aims to assess the mean-variance Shariah-compliant portfolio performance with model-based return and risk estimation. The methodology adopted is based on the implementation of ARMA and GARCH model, focused on the daily stock prices from the year 2011 until 2018. Further, we used one-step-ahead forecast for the best ARMA-GARCH model as well as an arithmetic mean and variance estimation to prepare the composition of diversified portfolioweights for top 10 constituent companies listed in FBM Hijrah Shariah (FBMHS) Index. We also measure out of sample performance in a constructed portfolio using Sharpe, Treynor and Jensen’s measures. The result shows that the stock allocation for the model-based portfolio is less diversified as compared to the non-model-based portfolio. The composition of the model-based portfolio weight is capable of achieving high annual returns which can compensate for high risk. The out of sample portfolio performance of both techniques is capable to outperform the FBMHS Index. Keywords:Return Risk Estimation;Shariah-Compliant Portfolio;Model-Based Portfolio;Portfolio Performance

Grey system theory has evolved, since, it was first introduced roughly 40years ago. It has been used in many applications and environments by different researchers worldwide. The aim of this study is to demonstrate the said theory in education environment by looking at the performance outcome in learning a mathematical subject at secondary school level through analysis and forecasting. The results show that the GM(1,1) Model produced 3.8% mean relative percentage error and future research will focus on how to optimize the forecasting.

The aim of this paper is to examine the best portfolio diversification strategy in three subperiods which are during the global financial crisis (GFC), post-global financial crisis and during the non-crisis period. Two types of diversification strategies are used and compared which are Markowitz’s mean-variance approach and naïve diversification. From past studies, many pieces of evidence have shown that naïve diversification strategy sometimes performed better or not as compared to the mean-variance framework. Therefore, in this study, we incorporate ten securities from five different industries to minimize the risk portfolio. We found that during the non-crisis period, the portfolio is not well diversified. Then, we construct ten efficient portfolios from the mean-variance approach. We choose and com-pare the optimal portfolio selected based on the risk-averse preference with the naïve portfolio. Performance wise that optimal portfolio dominated the naïve strategy throughout the three subperiods tested. All the optimal portfolios selected are yielding more return com-pared to the equal weight portfolio.

This research proposes a three-point block method for solving Duffing type higher order ordinary differential equations (ODEs) which is also commonly referred as the Duffing oscillator. The research conducted implements a variable order step size technique for approximating the exact solution for the Duffing Oscillator. The proposed algorithm will be tested against various Duffing oscillators and numerical approximation will be compared with current viable methods. The accuracy and efficiency of the proposed method will be illustrated in the numerical results.

The current research aims to provide a viable numerical method for solving difficult engineering and science problems which are in the form of higher order ordinary differential equations. The proposed method approximates these ordinary differential equations using Newton-Gregory backward difference polynomial in predictor–corrector mode. The predictor–corrector algorithm is then fitted with a variable order step size algorithm to reduce computational cost. The variable order stepsize algorithm allows the method to predetermine the preferred level of accuracy with the added advantage of less computational cost. The method is subsequently programmed with a two-point block formulation which can be altered for parallel programming. This research also discusses order and stepsize strategies of the variable order stepsize algorithm. Stability and convergence estimations of the method are also established. Numerical results obtained will validate the accuracy and efficiency of the method using various types of linear and nonlinear higher order ordinary differential equations