Search results for: financial forecasting

Authors: A. Bolaji Adesoye, Alimi Olorunfemi

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This paper examines the impact of small and medium-scale enterprises (SMEs) credit financing and financial market development and their shocks on the output growth of Nigeria. The study estimated a VAR model for Nigeria using 1970-2013 annual data series. Unit root tests and cointegration are carried out. The study also explores IRFs and FEVDs in a system that includes output, commercial bank loan to SMEs, domestic credit to private sector by banks, money supply, lending rate and investment. Findings suggest that shocks in commercial bank credit to SMEs has a major impact on the output changes of Nigeria. Money supply shocks also have a sizeable impact on output growth variations amidst other financial instruments. Lastly, neutrality of investment does not hold in Nigeria as it also has impact on output fluctuations.

Keywords: SMEs financing, financial development, investment, output, Nigeria

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Authors: Raja Kannusamy

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The research focuses on reducing food waste in the restaurant industry. A study has been conducted on the chain of retail restaurant outlets. It has been observed that the food wastages are due to the inefficient inventory management systems practiced in the restaurant outlets. The major food items which are wasted more in quantity are being selected across the retail chain outlets. A moving average forecasting method has been applied for the selected food items so that their future demand could be predicted accurately and food wastage could be avoided. It has been found that the moving average prediction method helps in predicting forecasts accurately. The demand values obtained from the moving average method have been compared to the actual demand values and are found to be similar with minimum variations. The inventory optimization technique helps in reducing food wastage in restaurant supply chain outlets.

Keywords: food wastage, restaurant supply chain, inventory optimisation, demand forecasting

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Authors: Ahmad Shayeq Azizi, Yuji Toda

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In Afghanistan, floods are the most frequent and recurrent events among other natural disasters. On the other hand, lack of monitoring data is a severe problem, which increases the difficulty of making the appropriate flood countermeasures of flood forecasting. This study is carried out to simulate the flood inundation in Harirud River Basin by application of distributed hydrological model, Integrated Flood Analysis System (IFAS) and 2D hydrodynamic model, International River Interface Cooperative (iRIC) based on satellite rainfall combined with historical peak discharge and global accessed data. The results of the simulation can predict the inundation area, depth and velocity, and the hardware countermeasures such as the impact of levee installation can be discussed by using the present method. The methodology proposed in this study is suitable for the area where hydrological and geographical data including river survey data are poorly observed.

Keywords: distributed hydrological model, flood inundation, hydrodynamic model, ungauged basins

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Authors: Piotr Prewysz-Kwinto, Grazyna Voss

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Accounting policies are a set of solutions compliant with legal regulations that an entity selects and adopts, and which guarantee a proper quality of financial statements. Those solutions may differ depending on whether the entity adopts national or international accounting standards. The aim of this article is to present accounting principles (policies) in Polish and international legal regulations and their adoption in selected Polish companies listed on the Warsaw Stock Exchange. The research method adopted in this work is the analysis and evaluation of legal conditions in Polish companies.

Keywords: accounting policies, international financial reporting standards, financial statement, method of measuring

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Authors: G. C. Surya Bahadur, Ranjana Kothari

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The paper attempts to analyze linkages between corporate governance and firm performance in India. The study employs a panel data of 50 Nifty companies from 2008 to 2012. Using LSDV panel data model and 2SLS model the study reveals that that good corporate governance practices adopted by companies is positively related with financial performance. Board independence, number of board committees and executive compensation are found to have positive relationship while ownership by promoters and financial leverage have negative relationship with performance. There is existence of bi-directional relationship between corporate governance and financial performance. Companies with sound financial performance are more likely to conform to corporate governance norms and standards and implement sound corporate governance system. The findings indicate that companies can enhance business performance and sustainability by embracing sound corporate governance practices.

Keywords: board structure, corporate governance, executive compensation, ownership structure

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Authors: Chattrarat Hotrawaisaya

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This research aims to formulate the logistics collaborative model which is the management tool for orchid flower exporter. The researchers study logistics activities in orchid supply chain that stakeholders can collaborate and develop, including demand forecasting, inventory management, warehouse and storage, order-processing, and transportation management. The research also explores logistics collaboration implementation into orchid’s stakeholders. The researcher collected data before implementation and after model implementation. Consequently, the costs and efficiency were calculated and compared between pre and post period of implementation. The research found that the results of applying the logistics collaborative model to orchid exporter reduces inventory cost and transport cost. The model also improves forecasting accuracy, and synchronizes supply chain of exporter. This research paper contributes the uniqueness logistics collaborative model which value to orchid industry in Thailand. The orchid exporters may use this model as their management tool which aims in competitive advantage.

Keywords: logistics, orchid, supply chain, collaboration

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: electricity price, k-factor GARMA, LLWNN, G-GARCH, forecasting

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

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Authors: Kateřina Struhařová

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The paper gives the evidence of quality of accounting information of Czech private companies. In general the private companies in the Czech Republic do not see the benefits of providing accounting information of high quality. Based on the research of financial statements of entrepreneurs and companies in Zlin region it was confirmed that the quality of accounting information differs among the private entities and that the major impact on the accounting information quality has the fact if the financial statements are audited as well as the size of the entity. Also the foreign shareholders and lenders have some impact on the accounting information quality.

Keywords: accounting information quality, financial statements, Czech Republic, private companies

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Authors: Ari Prasetyo, Taufik Faturohman

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The COVID-19 pandemic in Indonesia is part of the ongoing worldwide pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was confirmed to have spread to Indonesia on 2 March 2020. Moreover, the government of Indonesia has been conducting a local lockdown to limit people's movement from one city to another city. Therefore, this situation has impact on business operation, especially on highway companies listed on the Indonesia stock exchange. This study evaluates and measures three companies’ financial performance and health conditions before and during the COVID-19 pandemic from 2016 – 2020. The measurement is conducted by using financial ratio analysis and the Altman Z-score method. The ratio used to measure the financial ratio analysis is taken from the decree of the Ministry of SOE’s KEP-100/MBU/2002 about the company’s health level condition. From the decree, there are eight financial ratios used such as return on equity (ROE), return on investment (ROI), current ratio, cash ratio, collection period, inventory turnover, total asset turnover, and total equity to total asset. Altman Z-score is used to calculate the financial distress condition. The result shows that the highway companies for the period 2016 – 2020 are as follows: PT Jasa Marga (Persero) Tbk (AA, BB, BB, BB, C), PT Citra Marga Nusaphala Persada Tbk (BB, AA, BB, BBB, C), and PT Nusantara Infrastructure Tbk (BB, BB, AA, BBB, C). In addition, the Altman Z-score assessment performed in 2016-2020 shows that PT Jasa Marga (Persero) Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020. PT Citra Marga Nusaphala Persada Tbk was in the grey zone area for 2015-2019 and in the distress zone for 2020. PT Nusantara Infrastructure Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020.

Keywords: financial performance, financial ratio, Altman Z-score, financial distress, highway company

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Gulnara Moldasheva

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The research explores the relationship between management responsibility and corporate governance of listed companies in Kazakhstan. This research employs firm level data of randomly selected listed non-financial firms and firm level data “operational” financial sector, consisted from banking sector, insurance companies and accumulated pension funds using multivariate regression analysis under fixed effect model approach. Ownership structure includes institutional ownership, managerial ownership and private investor’s ownership. Management responsibility of the firm is expressed by the decision of the firm on amount of leverage. Results of the cross sectional panel study for non-financial firms showed that only institutional shareholding is significantly negatively correlated with debt to equity ratio. Findings from “operational” financial sector show that leverage is significantly affected only by the CEO/Chair duality and the size of financial institutions, and insignificantly affected by ownership structure. Also, the findings show, that there is a significant negative relationship between profitability and the debt to equity ratio for non-financial firms, which is consistent with pecking order theory. Generally, the found results suggest that corporate governance and a management responsibility play important role in corporate performance of listed firms in Kazakhstan.

Keywords: ownership, corporate governance, debt to equity ratio, corporate performance

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Authors: Javaid Ahmad Dar, Mohammad Asif

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The present study investigates the long-run impact of financial development, energy consumption and economic growth on greenhouse gas emissions for India, in presence of endogenous structural breaks, over a period of 1971-2013. Autoregressive distributed lag bounds testing procedure and Hatemi-J threshold cointegration technique have been used to test the variables for cointegration. ARDL bounds test did not confirm any cointegrating relationship between the variables. The threshold cointegration test establishes the presence of long-run impact of financial development, energy use and economic growth on greenhouse gas emissions in India. The results reveal that the long-run relationship between the variables has witnessed two regime shifts, in 1978 and 2002. The empirical evidence shows that financial sector development and energy consumption in India degrade environment. Unlike previous studies, this paper finds no statistical evidence of long-run relationship between economic growth and environmental deterioration. The study also challenges the existence of environmental Kuznets curve in India.

Keywords: cointegration, financial development, global warming, greenhouse gas emissions, regime shift, unit root

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Authors: Shehu Usman Hassan

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Published accounting information in financial statements are required to provide various users - shareholders, employees, suppliers, creditors, financial analysts, stockbrokers and government agencies – with timely and reliable information useful for making prudent, effective and efficient decisions. The widespread failure in the financial information quality has created the need to improve the financial information quality and to strengthen the control of managers by setting up good firms structures. This paper investigates firm attributes from perspective of structure, monitoring, performance elements of listed deposit money banks in Nigeria. The study adopted correlational research design with balanced panel data of 14 banks as sample of the study using multiple regression as a tool of analysis. The result reveals that firms attributes (leverage, profitability, liquidity, bank size and bank growth) has as significant influence on earnings quality of listed deposit money banks in Nigeria after the adoption of IFRS, while the pre period shows that the selected firm attributes has no significant impact on earnings quality. It is therefore concluded that the adoption of IFRS is right and timely.

Keywords: earnings quality, firm attributes, listed deposit money bank, Nigeria

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Authors: Liwen Wang, Yuting Chen, Tong Wu, Shaolei Hu

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In order to enhance the security of critical financial infrastructure, this study carries out a transformation of the architecture of a financial trading terminal to a zero trust architecture (ZTA), constructs an active defense system for cybersecurity, improves the security level of trading services in the Internet environment, enhances the ability to prevent network attacks and unknown risks, and reduces the industry and security risks brought about by cybersecurity risks. This study introduces the SDP technology of ZTA, adapts and applies it to a financial trading terminal to achieve security optimization and fine-grained business grading control. The upgraded architecture of the trading terminal moves security protection forward to the user access layer, replaces VPN to optimize remote access, and significantly improves the security protection capability of Internet transactions. The study achieves 1. deep integration with the access control architecture of the transaction system; 2. no impact on the performance of terminals and gateways, and no perception of application system upgrades; 3. customized checklist and policy configuration; 4. introduction of industry-leading security technology such as single-packet authorization (SPA) and secondary authentication. This study carries out a successful application of ZTA in the field of financial trading and provides transformation ideas for other similar systems while improving the security level of financial transaction services in the Internet environment.

Keywords: zero trust, trading terminal, architecture, network security, cybersecurity

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Authors: Nikki Berrange, Gizelle Willows

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Business rescue has become increasingly popular since its inclusion in the Companies Act of South Africa in May 2011. The Alternate Exchange (AltX) of the Johannesburg Stock Exchange has experienced a marked increase in the number of companies entering business rescue. This study sampled twenty companies listed on the AltX to determine whether Altman’s Z-score model for emerging markets (ZEM) or Taffler’s Z-score model is a more accurate model in predicting financial distress for small to medium size companies in South Africa. The study was performed over three different time horizons; one, two and three years prior to the event of financial distress, in order to determine how many companies each model predicted would be unlikely to succeed as well as the predictive ability and accuracy of the respective models. The study found that Taffler’s Z-score model had a greater ability at predicting financial distress from all three-time horizons.

Keywords: Altman’s ZEM-score, Altman’s Z-score, AltX, business rescue, Taffler’s Z-score

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Authors: Adebiyi Sunday Adeyanju, Kola Benson Ajeigbe, Fortune Ganda

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In the past three decades, there has been a notable increase in the number of firms delisting from the Johannesburg Stock Exchange (JSE) in South Africa. The recent increasing rate of delisting waves of corporate listed firms motivated this study. This study aims to explore the influence of institutional investor perceptions on the financial distress experienced by delisted firms within the South African market. The study further examined the impact of financial distress on the corporate performance of delisted firms. Using the data of delisted firms spanning from 2000 to 2023 and the FGLS (Feasible Generalized Least Squares) for the short run and PCSE (Panel-Corrected Standard Errors) for the long run effects of the relationship. The finding indicated that a decline in institutional investors’ perceptions was associated with the corporate financial distress of the delisted firms, particularly during the delisting year and the few years preceding the announcement of the delisting. This study addressed the importance of investor recognition in corporate financial distress and the delisting wave among listed firms- a finding supporting the stakeholder theory. This study is an insight for companies’ managements, investors, governments, policymakers, stockbrokers, lending institutions, bankers, the stock market, and other stakeholders in their various decision-making endeavours. Based on the above findings, it was recommended that corporate managements should improve their governance strategies that can help companies’ financial performances. Accountability and transparency through governance must also be improved upon with government support through the introduction of policies and strategies and enabling an easy environment that can help companies perform better.

Keywords: delisting wave, institutional investors, financial distress, corporate performance, investors’ perceptions

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Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression

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Authors: Vithul Kalki

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The mainstream political economy failed to explain the nature and causes of systemic failures and thus to compare and comprehend how contemporary capitalist systems work. An alternative research framework of Critical Macro-Finance (CMF) is an attempt to collaborate political theory with post-Keynesian economics with an objective to find answers to unresolved questions that emerged since the international financial crisis and repeated failures of capital systems. This unorthodox approach brings out four main propositions, namely : (a) that the adoption of American financial practices has anchored financial globalization in market-based finance; (b) that global finance is a set of interconnected, hierarchical balance sheets, increasingly subject to time-critical liquidity; (c) that credit creation in market-based finance involves new forms of money; and (d) that market-based finance structurally requires a de-risking state capable both of protecting systemic liabilities and creating new investment opportunities. The ongoing discussion of CMF literature is yet to be tested or even fully framed. This qualitative paper will critically examine the CMF framework and will engage in discussions aiming to connect the CMF with theories of capitalism in a wider context to bring a holistic approach for analyzing contemporary financial capitalism.

Keywords: critical macro-finance, capitalism, financial system, comparative political economy

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

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Authors: Rym Ghariani, Younes Boujelbene

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In contemporary times, global technological advancements, particularly those in the realm of digital technology, have emerged as pivotal instruments for enterprises in fostering viable partnerships and forging meaningful alliances with other firms. The advent of these digital innovations is poised to revolutionize nearly every facet and operation within corporate entities. The primary objective of this study is to explore the correlation between digitization, integration of supply chains, and the financial efficacy of the agro-industrial sector in Tunisia. To accomplish this, data collection employed a questionnaire as the primary research instrument. Subsequently, the research queries were addressed, and hypotheses were examined by subjecting the gathered data to principal component analysis and linear regression modeling, facilitated by the utilization of SPSS26 software. The findings revealed that digitalization within the supply chain, along with external supply chain integration, exerted discernible impacts on the financial performance of the organization.

Keywords: digitalization, supply chain integration, financial performance, Tunisian agro-industrial sector

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Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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Authors: Pedram Saadati, Zahra Nazari

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Today, the role and importance of financial technology businesses in Iran have increased significantly. Although, in Iran, there is no Islamic or non-Islamic personal financial planning field of study in the universities or educational centers, the profession of personal financial planning is not defined, and there is no software introduced in this regard for advisors or consumers. The largest sales network of financial services in Iran belongs to the insurance industry, and there is an untapped market for international companies in Iran that can contribute to 130 thousand representatives in the insurance industry and 28 million families by providing training and personal financial advisory software. To the best of the author's knowledge, despite the lack of previous internal studies in this field, the present study investigates the level of readiness of the salesforce of the insurance industry to accept this career and its technology. The statistical population of the research is made up of managers, insurance sales representatives, assistants and heads of sales departments of insurance companies. An 18-minute video was prepared that introduced and taught the job of Islamic personal financial planning and explained its difference from its non-Islamic model. This video was provided to the respondents. The data collection tool was a research-made questionnaire. To investigate the factors affecting technology acceptance and job change, independent T descriptive statistics and Pearson correlation were used, and Friedman's test was used to rank the effective factors. The results indicate the mental perception and very positive attitude of the insurance industry activists towards the usefulness of this job and its technology, and the studied sample confirmed the intention of training in this knowledge. Based on research results, the change in the customer's attitude towards the insurance advisor and the possibility of increasing income are considered as the reasons for accepting. However, Restrictions on using investment opportunities due to Islamic financial services laws and the uncertainty of the position of the central insurance in this regard are considered as the most important obstacles.

Keywords: fintech, insurance, personal financial planning, wealth management

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Authors: Shobhit Mittal

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Headcount budgeting stands as a pivotal element in organizational financial management, extending beyond traditional budgeting to encompass strategic resource allocation for workforce-related expenses. This process is integral to maintaining financial stability and fostering a productive workforce, requiring a comprehensive analysis of factors such as market trends, business growth projections, and evolving workforce skill requirements. It demands a collaborative approach, primarily involving Human Resources (HR) and finance departments, to align workforce planning with an organization's financial capabilities and strategic objectives. The dynamic nature of headcount budgeting necessitates continuous monitoring and adjustment in response to economic fluctuations, business strategy shifts, technological advancements, and market dynamics. Its significance in talent management is also highlighted, aligning financial planning with talent acquisition and retention strategies to ensure a competitive edge in the market. The consequences of incorrect headcount budgeting are explored, showing how it can lead to financial strain, operational inefficiencies, and hindered strategic objectives. Examining case studies like IBM's strategic workforce rebalancing and Microsoft's shift for long-term success, the importance of aligning headcount budgeting with organizational goals is underscored. These examples illustrate that effective headcount budgeting transcends its role as a financial tool, emerging as a strategic element crucial for an organization's success. This necessitates continuous refinement and adaptation to align with evolving business goals and market conditions, highlighting its role as a key driver in organizational success and sustainability.

Keywords: strategic planning, fiscal budget, headcount planning, resource allocation, financial management, decision-making, operational efficiency, risk management, headcount budget

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Authors: Morteza Raei Dehaghi, Seyed Mohammad Mirhashemi

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The current study explored the effect of economic development, financial development and institutional quality on environmental destruction in upper-middle income countries during the time period of 1999-2011. The dependent variable is logarithm of carbon dioxide emissions that can be considered as an index for destruction or quality of the environment given to its effects on the environment. Financial development and institutional development variables as well as some control variables were considered. In order to study cross-sectional correlation among the countries under study, Pesaran and Friz test was used. Since the results of both tests show cross-sectional correlation in the countries under study, seemingly unrelated regression method was utilized for model estimation. The results disclosed that Kuznets’ environmental curve hypothesis is confirmed in upper-middle income countries and also, financial development and institutional quality have a significant effect on environmental quality. The results of this study can be considered by policy makers in countries with different income groups to have access to a growth accompanied by improved environmental quality.

Keywords: economic development, environmental destruction, financial development, institutional development, seemingly unrelated regression

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Authors: Kristel Faye Tandog

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The State Owned Enterprise (SOE) or also called Public Enterprise (PE) has been playing a vital role in a country’s social and economic development. Following this idea, this study focused on the Factor Structures of Financial Performance of the Local Economic Enterprises (LEEs) namely: Food Court, Market, Slaughterhouse, and Terminal in Matalam, Cotabato. It aimed to determine the profile of the LEEs in terms of organizational structure, manner of creation, years in operation, source of initial operating requirements, annual operating budget, geographical location, and size or description of the facility. This study also included the different financial ratios of LEE that covered a five year period from Calendar Year 2009 to 2013. Primary data using survey questionnaire was administered to 468 respondents and secondary data were sourced out from the government archives and financial documents of the said LGU. There were 12 dominant factors identified namely: “management”, “enforcement of laws”, “strategic location”, “existence of non-formal competitors”, “proper maintenance”, “pricing”, “customer service”, “collection process”, “rentals and services”, “efficient use of resources”, “staffing”, and “timeliness and accuracy”. On the other hand, the financial performance of the LEE of Matalam, Cotabato using financial ratios needs reformatting. This denotes that refinement as to the following ratios: Cash Flow Indicator, Activity, Profitability and Growth is necessary. The cash flow indicator ratio showed difficulty in covering its debts in successive years. Likewise, the activity ratios showed that the LEE had not been effective in putting its investment at work. Moreover, profitability ratios revealed that it had operated in minimum capacity and had incurred net losses and thus, it had a weak profit performance. Furthermore, growth ratios showed that LEE had a declining growth trend particularly in net income.

Keywords: factor structures, financial performance, financial ratios, state owned enterprises

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Authors: Rodrigo Zepeda

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Transaction cost analysis (TCA) is a way of analyzing the relative performance of different intermediaries and different trading strategies for trades undertaken in financial instruments. It is a way for an investor to determine the overall quality of execution of a particular trade, and there are many different approaches to undertaking TCA. Under the updated Markets in Financial Instruments Directive (2014/65/EU) (MiFID II), investment firms are required when executing orders, to take all sufficient steps to obtain the best possible result for their clients. This requirement for 'Best Execution' must take into account price, costs, speed, likelihood of execution and settlement, size, nature or any other consideration relevant to the execution of the order. The new regulatory compliance framework under MiFID II will now also apply across a very broad range of financial instruments. This article will provide a comprehensive technical analysis of how TCA and Best Execution will significantly change under MiFID II. It will also explain why harmonization of post-trade reporting requirements under MiFID II could potentially support the development of peer group analysis, which in turn could provide a new and highly advanced framework for TCA that could more effectively support Best Execution requirements under MiFID II. The study is significant because there are no studies that have dealt with TCA and Best Execution under MiFID II in the literature.

Keywords: transaction cost analysis, execution quality, best execution, MiFID II, financial instruments

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Authors: Ifedapo Francis Awolowo

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The unrelenting series of embarrassing audit failures should stimulate a paradigm shift in accounting. And in this age of information revolution, there is need for a constant improvement on the products or services one offers to the market in order to be relevant. This study explores the perceptions of external auditors, forensic accountants and accounting academics on whether a paradigm shift to forensic accounting can reduce financial statement frauds. Through Neo-empiricism/inductive analytical approach, findings reveal that a paradigm shift to forensic accounting might be the right step in the right direction in order to increase the chances of fraud prevention and detection in the financial statement. This research has implication on accounting education on the need to incorporate forensic accounting into present day accounting curriculum. Accounting professional bodies, accounting standard setters and accounting firms all have roles to play in incorporating forensic accounting education into accounting curriculum. Particularly, there is need to alter the ISA 240 to make the prevention and detection of frauds the responsibilities of bot those charged with the management and governance of companies and statutory auditors.

Keywords: financial statement fraud, forensic accounting, fraud prevention and detection, auditing, audit expectation gap, corporate governance

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Authors: Rusudan Kinkladze, Guguli Kurashvili, Ketevan Chitaladze

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Foreign direct investment is a driving force in the development of the interdependent national economies, and the study and analysis of investments is an urgent problem. It is particularly important for transitional economies, such as Georgia, and the study and analysis of investments is an urgent problem. Consequently, the goal of the research is the study and analysis of direct foreign investments in Georgia, and identification and forecasting of modern trends, and covers the period of 2006-2015. The study uses the methods of statistical observation, grouping and analysis, the methods of analytical indicators of time series, trend identification and the predicted values are calculated, as well as various literary and Internet sources relevant to the research. The findings showed that modern investment policy In Georgia is favorable for domestic as well as foreign investors. Georgia is still a net importer of investments. In 2015, the top 10 investing countries was led by Azerbaijan, United Kingdom and Netherlands, and the largest share of FDIs were allocated in the transport and communication sector; the financial sector was the second, followed by the health and social work sector, and the same trend will continue in the future. 

Keywords: foreign direct investments, methods, statistics, analysis

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Authors: Rodrigo Zeidan

Abstract:

The paper identifies failures of decision making and corporate governance that allow non-financial companies around the world to develop hedging strategies that lead to hefty losses in the aftermath of the financial crisis. The sample is comprised of 346 companies from 10 international markets, of which 49 companies (and a subsample of 13 distressed companies) lose a combined US$18.9 billion. An event study shows that most companies that present losses in derivatives experience negative abnormal returns, including a number of companies in which the effect is persistent after a year. The results of a probit model indicate that the lack of a formal hedging policy, no monitoring to the CFOs, and considerations of hubris and remuneration contribute to the mismanagement of hedging policies.

Keywords: risk management, hedging, derivatives, monitoring, corporate governance structure, event study, hubris

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