Accounting

Artificial intelligence (AI) systems have significantly changed the audit process; nevertheless, the AI revolution opponents view this growth as a step-back as many auditors will fail to adapt to this new environment and will drop behind. Our descriptive study examines the perceived ease of use, usefulness, and contribution to the audit quality of different AI’s types. To address local audit firms concerns about their readiness to use AI systems in auditing processes and to advance auditing research, we examine whether perceived ease of use, usefulness, and contribution to audit quality vary by AI systems type (Assisted, Augmented, and Autonomous). An online questionnaire was used to collect data from 124 auditors representing local audit firms in Jordan. Our results indicate that auditors perceive Assisted and Augmented AI systems as ease of use in auditing while perceiving Autonomous AI systems as complicated to use. Besides, Auditors are underestimating Autonomous AI systems’ capabilities and perceived it as not useful for auditing. The results also reveal a significant difference between the perceived contribution to audit quality by the three AI systems types. This study contributes to the existing literature on AI and auditing by developing and testing a measure for AI systems’ perceived contribution to audit quality. This study also provides empirical evidence on how Jordan local firms auditors perceive AI use in auditing.

Ibrahim Albawwat

Yaser Al Frijat

An analysis of auditors’ perceptions towards artificial intelligence and its contribution to audit quality

T. Abdel-Jalil

A. Daher

G. Rumman

A. Bsoul

The market reaction to profitability: Does leverage matter?

盈利能力的市场反应：杠杆是否重要？

Research on stock exchange markets is essential to stock market investors as it offers sensitivities to risk management. This research investigates the patterns of the volatility of stock market prices in ten African stock markets. We estimated the dynamic GARCH model of Engle using the method of maximum likelihood estimation. Daily time series from January 1, 2021 to December 30, 2022, were obtained from African Stock (Securities) Exchange database. The findings established the existence of a normally distributed Senegalese stock market as against time-varying volatility of stock prices in Nigeria, Ghana, Mali, Burkina Faso, Togo, Niger Republic, Benin Republic, Ivory Coast, and Gambian. Hence, the likelihood that an asset or stock is being overpriced (overvalued) or underpriced (undervalued) in the Senegal stock market is low. It is therefore easier for stock traders and investors in Senegal to pick entry and exit points. Unfortunately, this cannot be said of the investors in stock markets of other countries. In effect, the closing price of a stock is most often heavily deviated with significant outliers. This further infers that variations of stock prices in these markets are very wide, heavy, and unpredicted. Hence, it is a case of the volatility of volatilities.

David Umoru

Beauty Igbinovia

Hussein Oseni Omomoha

Volatility patterns of stock prices

股票价格的波动模式

This article introduces a comprehensive analysis of 20 leading companies, scrutinized through their financial metrics across various sectors. By deploying multi-criteria decision-making (MCDM) techniques, we aim to offer investors a clear and objective perspective on which companies stand out as the best investment options. Among the MCDM techniques, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is utilized, renowned for its efficiency in handling complex decision-making scenarios which is conducted by two clauses. 1) Implementing TOPSIS with assigning equal weights and same share to every chosen metrics as criteria and 2) employ BWM (Best Worst Method) to calculate these weights base on their significance and relevancy to the prosses of ranking. According to the Result gained from the computation, ranks 1 to 5 belong to the similar companies with both assumptions which are Ford Motor Co, BP plc, Tesla Inc, General Motors Co and Exxon Mobil Corp. The consistency in rankings across two different weighting assumptions highlights the robustness of the criteria used, ensuring stable and reliable outcomes. This enhances the credibility of the findings, making them more trustworthy and citable for those who seek reliable and robust methodologies for informed investment decisions.

Seyedeh Yalda Ghorbani Amrei

Amir Teymourian

An application of TOPSIS and BWM for portfolio allocation

TOPSIS与BWM在投资组合分配中的应用

This paper analyses the causal relationship between Foreign Portfolio Investment (FPI), Equities Market Volatility, Exchange Rate and Inflation in Zimbabwe using a monthly time series data between October 2018 and November 2021. The granger causality model was used to present the link between the variables, and EGARCH was used to account for volatility and asymmetric effects on the variables. To incorporate innovations and responses into the Granger model, impulse response functions were used. Links between exchange rate and foreign portfolio investments were found. This only suggests that exchange rate volatility will vary when overseas investors purchase and sell financial securities on the Zimbabwe Stock Exchange (ZSE). In contrast, foreign investors sell local financial securities when local stock market returns are negative, leading to a significant outflow of foreign portfolio investment thereby reducing demand for currency. A significant causal relationship was found between the volatility of the exchange rate and stock market returns. It is assumed that stock market returns, and foreign portfolio investments are caused by fluctuating currency rates. The relationship between exchange rate and ZSE returns, and inflation was found based on Granger causality. This implies that stocks are not suitable for long-term investments that compensate investors for their diminished purchasing power. Policy makers should advise the Zimbabwe Stock Exchange to recommend a reduction in capital gains tax and withholding tax and this encourages investors to hold local equities for a long time.

Talent Kondo

Simba Mutsvangwa

Felix Chari

Sithokozile Bafana

Foreign portfolio investment, returns, exchange rate and inflation for Zimbabwe: A Granger Causality and EGARCH approach

外国投资组合、回报率、汇率与津巴布韦的通货膨胀：格兰杰因果关系与EGARCH方法

This research aims to enhance portfolio selection by integrating machine learning regression algorithms for predicting stock returns with various risk measures. These measures include mean-value-at-risk (VaR) variance (Var), semi-variance mean-absolute-deviation (MAD) and conditional value-at-risk (C-VaR). Addressing gaps in existing literature. Traditional methods lack adaptability to dynamic market conditions. We propose a hybrid approach optimized by genetic algorithms. The study employs multiple machine learning models. These include Random Forest, AdaBoost XGBoost, Support Vector Machine Regression (SVR) K-Nearest Neighbors (KNN) and Artificial Neural Network (ANN). These models are used to forecast stock returns. Utilizing monthly data from the Tehran Stock Exchange, the results indicate that the genetic algorithm prediction model combined with mean-VaR, Var semi-variance and MAD, produces the most efficient portfolios. These portfolios offer superior returns with minimized risk compared to other models. This hybrid strategy provides a robust and efficient method for investors aiming to optimize returns while managing risk effectively. To implement this approach successfully it is crucial to balance investments. This involves both traditional and alternative asset classes, ensuring diversification. It also capitalizes on market opportunities. Regular review and adjustment of fund allocation are essential. Maintain an optimized strategy for maximum returns and minimal risk.

Amir Hossein Gandomi

Seyed Jafar Sadjadi

Babak Amiri

Stock price prediction portfolio optimization using different risk measures on application of genetic algorithm for machine learning regressions

基于遗传算法机器学习回归的股票价格预测投资组合优化：不同风险度量的应用

In today's dynamic business landscape, the audit profession encounters numerous obstacles, particularly in adapting to the necessity of computer-assisted audits due to the immense volume of data requiring scrutiny. Despite the emergence of different digital auditing tools, there is a gap in research regarding the level of adoption, and its effects on the quality of audit services especially in the context of developing countries. This study seeks to investigate the impact of digitalization of audit tasks on the quality of audit services of accounting firms in Nigeria. The study, which has its foundation on the Technology Acceptance Model (TAM) integrated with the Technology, Organization, and Environment (TOE) framework, adopted the survey research design. The population of study was made up practitioners of accounting firms in Abuja and Lagos, Nigeria. A self-designed questionnaire was used as a tool for data collection for the study. Findings of the study indicate that automation of audit tasks enhances the quality of audit services suggesting that adopting IT infrastructures leads to more reliable audit procedures, improved efficiency and accuracy, as well as mitigating audit risks. Results also revealed that Big Four auditors are significantly ahead in the adoption of digital technologies compared to the non-Big Four auditors, confirming the dominance of larger accounting firms in application of emerging technologies in performing audit tasks.

Sunday Otuya

Audit tasks Digitalization and quality of audit services in Nigeria

尼日利亚审计任务数字化与审计服务质量

Publication Information	Publisher: Growing Science，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2018，Proportion of original research papers: 0.00%，Self Citation Rate:N.A.， Gold OA Rate: 0.00%
Average review cycle	20 weeks

Accounting

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An analysis of auditors’ perceptions towards artificial intelligence and its contribution to audit quality

The market reaction to profitability: Does leverage matter?

The market reaction to profitability: Does leverage matter?

Volatility patterns of stock prices

An application of TOPSIS and BWM for portfolio allocation

Volatility patterns of stock prices

An application of TOPSIS and BWM for portfolio allocation

Foreign portfolio investment, returns, exchange rate and inflation for Zimbabwe: A Granger Causality and EGARCH approach

Stock price prediction portfolio optimization using different risk measures on application of genetic algorithm for machine learning regressions

Audit tasks Digitalization and quality of audit services in Nigeria