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.

This paper elaborates risk shifting in debt financing system as the ultimate cause of the global financial crisis. In contrast, risk sharing in equity financing like sukuk helps the economic system to be better sustained. Nevertheless, some types of sukuk are haunted by the issue of imitation with bonds. The critics on the imitation issue not only have raised doubt on the ability of sukuk to diminish risk shifting behavior but also the ability of this Islamic financial instrument to ensure better future financial stability. Through that, this paper provides discussion on the possibility of sukuk to induce risk shifting and how equity financing may help sukuk to be free from risk shifting. This paper is important in the sense that sukuk receives a significant demand from investors throughout the world. For this instrument to be supportive in the future economic stability, the issue of imitation needs to be identified and addressed. Furthermore, critics cannot be focused on debts and its ability to gauge the financial flux but also to sukuk due to their structures similarity.

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.

In the modern financial market, investors have to make quick and efficient investment decisions. The problem arises when the investor does not know the right tools to use in investment decision making. Different tools can be implemented in trading strategies to predict future stock prices. Therefore, the primary objective of this paper is to analyse the performance of the Geometric Brownian Motion (GBM) model in forecasting Nestle stock price by assessing the performance evaluation indicators. To analyse the stocks, two software were used, namely Microsoft Excel and Python. The model is trained for 16 weeks (4 months) of data from May to August 2019 and 2020. The simulated sample is for four weeks (1 month) which is for September 2019 and 2020. The findings show that during the Pandemic Covid-19, short-term prediction using GBM is more efficient than long-term prediction as the lowest Mean Square Error (MSE) value is at one week period. In addition, the Mean Absolute Percentage Error (MAPE) for all GBM simulations is highly accurate as it shows that MAPE values are less than 10%, indicating that the GBM method can be used to predict Nestle stock price during an economic downturn.

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.

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