Search results for: financial models

Authors: Yegnanew A. Shiferaw

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Background: commodity price volatility originating from excessive commodity price fluctuation has been a global problem especially after the recent financial crises. Volatility is a measure of risk or uncertainty in financial analysis. It plays a vital role in risk management, portfolio management, and pricing equity. Objectives: the core objective of this paper is to examine the relationship between the prices of agricultural commodities with oil price, gas price, coal price and exchange rate (USD/Rand). In addition, the paper tries to fit an appropriate model that best describes the log return price volatility and estimate Value-at-Risk and expected shortfall. Data and methods: the data used in this study are the daily returns of agricultural commodity prices from 02 January 2007 to 31st October 2016. The data sets consists of the daily returns of agricultural commodity prices namely: white maize, yellow maize, wheat, sunflower, soya, corn, and sorghum. The paper applies the three-state Markov-switching (MS) regression, the standard single-regime GARCH and the two regime Markov-switching GARCH (MS-GARCH) models. Results: to choose the best fit model, the log-likelihood function, Akaike information criterion (AIC), Bayesian information criterion (BIC) and deviance information criterion (DIC) are employed under three distributions for innovations. The results indicate that: (i) the price of agricultural commodities was found to be significantly associated with the price of coal, price of natural gas, price of oil and exchange rate, (ii) for all agricultural commodities except sunflower, k=3 had higher log-likelihood values and lower AIC and BIC values. Thus, the three-state MS regression model outperformed the two-state MS regression model (iii) MS-GARCH(1,1) with generalized error distribution (ged) innovation performs best for white maize and yellow maize; MS-GARCH(1,1) with student-t distribution (std) innovation performs better for sorghum; MS-gjrGARCH(1,1) with ged innovation performs better for wheat, sunflower and soya and MS-GARCH(1,1) with std innovation performs better for corn. In conclusion, this paper provided a practical guide for modelling agricultural commodity prices by MS regression and MS-GARCH processes. This paper can be good as a reference when facing modelling agricultural commodity price problems.

Keywords: commodity prices, MS-GARCH model, MS regression model, South Africa, volatility

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Authors: Petar Dobrev

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There is no agreed-upon definition of firm quality. While profitability and stock performance often qualify as popular proxies of quality, in this project, we aim to identify quality without relying on a firm’s financial statements or stock returns as selection criteria. Instead, we use firm-level data on management practices across small to medium-sized U.S. manufacturing firms from the World Management Survey (WMS) to measure firm quality. Each firm in the WMS dataset is assigned a mean management score from 0 to 5, with higher scores identifying better-managed firms. This management score serves as our proxy for firm quality and is the sole criteria we use to separate firms into portfolios comprised of high-quality and low-quality firms. We define high-quality (low-quality) firms as those firms with a management score of one standard deviation above (below) the mean. To study whether this proxy for firm quality can identify better-performing firms, we link this data to Compustat and The Center for Research in Security Prices (CRSP) to obtain firm-level data on financial performance and monthly stock returns, respectively. We find that from 1999 to 2019 (our sample data period), firms in the high-quality portfolio are consistently more profitable — higher operating profitability and return on equity compared to low-quality firms. In addition, high-quality firms also exhibit a lower risk of bankruptcy — a higher Altman Z-score. Next, we test whether the stocks of the firms in the high-quality portfolio earn superior risk-adjusted excess returns. We regress the monthly excess returns on each portfolio on the Fama-French 3-factor, 4-factor, and 5-factor models, the betting-against-beta factor, and the quality-minus-junk factor. We find no statistically significant differences in excess returns between both portfolios, suggesting that stocks of high-quality (well managed) firms do not earn superior risk-adjusted returns compared to low-quality (poorly managed) firms. In short, our proxy for firm quality, the WMS management score, can identify firms with superior financial performance (higher profitability and reduced risk of bankruptcy). However, our management proxy cannot identify stocks that earn superior risk-adjusted returns, suggesting no statistically significant relationship between managerial quality and stock performance.

Keywords: excess stock returns, management, profitability, quality

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: L. Sierra, N. Gambetta, M. A. Garcia-Benau, M. Orta

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Financial scandals and financial crisis have led to an international debate on the value of auditing. In recent years there have been significant legislative reforms aiming to increase markets’ confidence in audit services. In particular, there has been a significant debate on the need to improve the communication of auditors with audit reports users as a way to improve its informative value and thus, to improve audit quality. The International Auditing and Assurance Standards Board (IAASB) has proposed changes to the audit report standards. The International Standard on Auditing 701, Communicating Key Audit Matters (KAM) in the Independent Auditor's Report, has introduced new concepts that go beyond the auditor's opinion and requires to disclose the risks that, from the auditor's point of view, are more significant in the audited company information. Focusing on the companies included in the Financial Times Stock Exchange 100 index, this study aims to focus on the analysis of the determinants of the number of KAM disclosed by the auditor in the audit report and moreover, the analysis of the determinants of the different type of KAM reported during the period 2013-2015. To test the hypotheses in the empirical research, two different models have been used. The first one is a linear regression model to identify the client’s characteristics, industry sector and auditor’s characteristics that are related to the number of KAM disclosed in the audit report. Secondly, a logistic regression model is used to identify the determinants of the number of each KAM type disclosed in the audit report; in line with the risk-based approach to auditing financial statements, we categorized the KAM in 2 groups: Entity-level KAM and Accounting-level KAM. Regarding the auditor’s characteristics impact on the KAM disclosure, the results show that PwC tends to report a larger number of KAM while KPMG tends to report less KAM in the audit report. Further, PwC reports a larger number of entity-level risk KAM while KPMG reports less account-level risk KAM. The results also show that companies paying higher fees tend to have more entity-level risk KAM and less account-level risk KAM. The materiality level is positively related to the number of account-level risk KAM. Additionally, these study results show that the relationship between client’s characteristics and number of KAM is more evident in account-level risk KAM than in entity-level risk KAM. A highly leveraged company carries a great deal of risk, but due to this, they are usually subject to strong capital providers monitoring resulting in less account-level risk KAM. The results reveal that the number of account-level risk KAM is strongly related to the industry sector in which the company operates assets. This study helps to understand the UK audit market, provides information to auditors and finally, it opens new research avenues in the academia.

Keywords: FTSE 100, IAS 701, key audit matters, auditor’s characteristics, client’s characteristics

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Authors: Ayman Mutahar Alrassas, Shaoran Ren, Renyuan Ren, Hung Vo Thanh, Mohammed Hail Hakimi, Zhenliang Guan

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The significant effect of CO₂ on global climate and the environment has gained more concern worldwide. Enhance oil recovery (EOR) associated with sequestration of CO₂ particularly into the depleted oil reservoir is considered the viable approach under financial limitations since it improves the oil recovery from the existing oil reservoir and boosts the relation between global-scale of CO₂ capture and geological sequestration. Consequently, practical measurements are required to attain large-scale CO₂ emission reduction. This paper presents an integrated modeling workflow to construct an accurate 3D reservoir geological model to estimate the storage capacity of CO₂ under geological uncertainty in an unconventional oil reservoir of the Paleogene Shahejie Formation (Es1) in the block Nv32, Shenvsi oilfield, China. In this regard, geophysical data, including well logs of twenty-two well locations and seismic data, were combined with geological and engineering data and used to construct a 3D reservoir geological modeling. The geological modeling focused on four tight reservoir units of the Shahejie Formation (Es1-x1, Es1-x2, Es1-x3, and Es1-x4). The validated 3D reservoir models were subsequently used to calculate the theoretical CO₂ storage capacity in the block Nv32, Shenvsi oilfield. Well logs were utilized to predict petrophysical properties such as porosity and permeability, and lithofacies and indicate that the Es1 reservoir units are mainly sandstone, shale, and limestone with a proportion of 38.09%, 32.42%, and 29.49, respectively. Well log-based petrophysical results also show that the Es1 reservoir units generally exhibit 2–36% porosity, 0.017 mD to 974.8 mD permeability, and moderate to good net to gross ratios. These estimated values of porosity, permeability, lithofacies, and net to gross were up-scaled and distributed laterally using Sequential Gaussian Simulation (SGS) and Simulation Sequential Indicator (SIS) methods to generate 3D reservoir geological models. The reservoir geological models show there are lateral heterogeneities of the reservoir properties and lithofacies, and the best reservoir rocks exist in the Es1-x4, Es1-x3, and Es1-x2 units, respectively. In addition, the reservoir volumetric of the Es1 units in block Nv32 was also estimated based on the petrophysical property models and fund to be between 0.554368

Keywords: CO₂ storage capacity, 3D geological model, geological uncertainty, unconventional oil reservoir, block Nv32

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Authors: Emily J. Morey, Kevin Galvin, Thomas Riley, R. Eddie Wilson

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The key challenges faced by integrating autonomous rail operations into the existing mainline railway environment have been identified through the understanding and framing of the problem space and stakeholder analysis. This was achieved through the completion of the first four steps of Soft Systems Methodology, where the problem space has been expressed via conceptual models. Having identified these challenges, we investigated one of them, namely capacity, via the use of models and simulation. This paper examines the approach used to move from the conceptual models to a simulation which can determine whether the integration of autonomous trains can plausibly increase capacity. Within this approach, we developed an architecture and converted logical models into physical resource models and associated design features which were used to build a simulator. From this simulator, we are able to analyse mixtures of legacy-autonomous operations and produce fundamental diagrams and trajectory plots to describe the dynamic behaviour of mixed mainline railway operations.

Keywords: autonomy, executable architecture, modelling and simulation, railway capacity

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Authors: Marat Kozhomberdiev

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The research will investigate the modern corporate finance management technologies currently used in the era of digitalization of the global economy and the degree to which financial institutions are utilizing these new technologies in the field of corporate finance management in Kyrgyzstan. The main purpose of the research is to reveal the role of financial management technologies as joint service centers, intercompany banks, specialized payment centers in the third-world country. Particularly, the analysis of the implacability of automated corporate finance management systems such as enterprise resource planning system (ERP) and treasury management system (TMS) will be carried out. Moreover, the research will investigate the role of cloud accounting systems in corporate finance management in Kyrgyz banks and whether it has any impact on the field of improving corporate finance management. The study will utilize a data collection process via surveying 3 banks in Kyrgyzstan, namely Mol-Bulak, RSK, and KICB. The banks were chosen based on their ownerships, such as state banks, private banks with local authorized capital, and private bank with international capital. The regression analysis will be utilized to reveal the correlation between the ownership of the bank and the use of new financial management technologies. The research will provide policy recommendations to both private and state banks on developing strategies for switching and utilizing modern corporate finance management technologies in their daily operations.

Keywords: digital economy, corporate finance, digital environment, digital technologies, cloud technologies, financial management

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Authors: S. Sadallah

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In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

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Authors: Mohd Adib Abd Muin

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Social entrepreneurship has become a new phenomenon in a country in order to reduce social problems and eradicate poverty communities. However, the study based on Islamic social entrepreneurship from the social entrepreneurial activity is still new especially in the Islamic perspective. In addition, this research found that is lacking of model on social entrepreneurship that focus on Islamic perspective. Therefore, the objective of this paper is to identify the issues and research gap based on Islamic perspective from existing models and to develop a concept of Islamic social entrepreneurship according to Islamic perspective and Maqasid Shari’ah. The research method used in this study is literature review and comparative analysis from 11 existing models of social entrepreneurship. The research finding shows that 11 existing models on social entrepreneurship has been analyzed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: component, social entrepreneurship, Islamic perspective, research gap

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Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: Muhammad Izzam Bin Mohd Khazar, Nur Adibah Binti Zainudin

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Islamic banking as one of the financial institutions is highly required to maintain a prudent approach to ensure that any financing given is able to generate income to their respective shareholders. As the default payment of customers is probably occurred in the financing, having a prudent approach in the recovery process is a must to ensure that financing losses are within acceptable limits. The objective of this research is to provide the best practice of recovery which is anticipated to benefit both bank and customers. This study will address arising issue on the current practice of recovery process and followed by providing humanising recovery solutions in the light of the Maqasid Shariah. The study identified main issues pertaining to Islamic recovery process which can be categorized into knowledge crisis, process issues, specific treatment cases and system issues. Knowledge crisis is related to direct parties including judges, solicitors and salesperson, while the recovery process issues include the process of issuance of reminder, foreclosure and repossession of asset. Furthermore, special treatment for particular cases also should be observed since different contracts in Islamic banking products will need different treatment. Finally, issues in the system used in the recovery process are still unresolved since the existing technology is still young in this area to embraced Islamic finance requirements and nature of calculation. In order to humanize the financial services in Islamic banking recovery process, we have highlighted four main recommendation to be implemented by Islamic Financial Institutions namely; 1) early deterrent by improving the awareness, 2) improvement of the internal process, 3) reward mechanism, and 4) creative penalty to provide awareness to all stakeholders.

Keywords: humanizing financial services, Islamic Finance, Maqasid Syariah, recovery process

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Authors: Salahaeddine Sbai

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Air quality analysis using machine learning models is a method employed to assess and predict air pollution levels. This approach leverages the capabilities of machine learning algorithms to analyze vast amounts of air quality data and extract valuable insights. By training these models on historical air quality data, they can learn patterns and relationships between various factors such as weather conditions, pollutant emissions, and geographical features. The trained models can then be used to predict air quality levels in real-time or forecast future pollution levels. This application of machine learning in air quality analysis enables policymakers, environmental agencies, and the general public to make informed decisions regarding health, environmental impact, and mitigation strategies. By understanding the factors influencing air quality, interventions can be implemented to reduce pollution levels, mitigate health risks, and enhance overall air quality management. Climate change is having significant impacts on Morocco, affecting various aspects of the country's environment, economy, and society. In this study, we use some machine learning models under python environment to predict and analysis air quality change over North of Morocco to evaluate the climate change impact on agriculture.

Keywords: air quality, machine learning models, pollution, pollutant emissions

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Authors: Sepideh Khavarinezhad, Paolo Pietro Biancone

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This paper sheds light on how gender entrepreneurship is influenced by economic freedom in OECD countries. Our study empirically explores the interaction of financial institutions and its effect of both motivations on total entrepreneurial activities (TEA) of women and men in these countries and to discuss the differences between women and men in this field, which is always a hot topic in entrepreneurship. Employing a dynamic method, we conducted panel data analysis in the time frame from 2012-2015. In this regard, we evaluate the relationship between the Index of Economic Freedoms and its three years, and both indicators of Global Entrepreneurship Monitor (GEM) on supportive financial institutions. We investigate that economic liberalization tends to persuade men and women entrepreneurs to start their businesses or to reduce motivation entrepreneurship. In particular, our paper demonstrates that motivation entrepreneurship seems to benefit from government support and fade barriers in legal structure in business, while we expect to confirm that free trade and economic freedom stimulate the entrepreneur’s motivation and their participation to start own business.

Keywords: economic freedom, gender entrepreneurship, financial institutions, OECD countries

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Authors: Samuel Opeyemi Williams, Razali Bin Adul Hamid, M. S. Misnan, Taki Eddine Seghier, D. I. Ajayi

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Construction sites are characterized with occupational risks. Review of literature on construction accidents reveals that a lot of theories have been propounded over the years by different theorists, coupled with multifarious models developed by different proponents at different times. Accidents are unplanned events that are prominent in construction sites, involving materials, objects and people with attendant damages, loses and injuries. Models were developed to investigate the causations of accident with the aim of preventing its occurrence. Though, some of these theories were criticized, most especially, the Heinrich Domino theory, being mostly faulted for placing much blame on operatives rather than the management. The purpose of this paper is to unravel the significant construction accident causation theories and models for the benefit of understanding of the theories, and consequently enabling construction stakeholders identify the possible potential hazards on construction sites, as all stakeholders have significant roles to play in preventing accident. Accidents are preventable; hence, understanding the risk factors of accident and the causation theories paves way for its prevention. However, findings reveal that still some gaps missing in the existing models, while it is recommended that further research can be made in order to develop more models in order to maintain zero accident on construction sites.

Keywords: domino theory, construction site, site safety, accident causation model

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Authors: M. Wigwe, J. G Akpa, E. N Wami

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Mathematical models of the absorber of a glycol dehydration facility was developed using the principles of conservation of mass and energy. Models which predict variation of the water content of gas in mole fraction, variation of gas and liquid temperatures across the parking height were developed. These models contain contributions from bulk and diffusion flows. The effect of diffusion on the process occurring in the absorber was studied in this work. The models were validated using the initial conditions in the plant data from Company W TEG unit in Nigeria. The results obtained showed that the effect of diffusion was noticed between z=0 and z=0.004 m. A deviation from plant data of 0% was observed for the gas water content at a residence time of 20 seconds, at z=0.004 m. Similarly, deviations of 1.584% and 2.844% were observed for the gas and TEG temperatures.

Keywords: separations, absorption, simulation, dehydration, water content, triethylene glycol

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Authors: Khaoula Hidouri, Ali Benhmidene, Bechir Chouachi

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The purification of brackish seawater becomes a necessity and not a choice against demographic and industrial growth especially in third world countries. Two models can be used in this work: simple solar still and simple solar still coupled with a heat pump. In this research, the productivity of water by Simple Solar Distiller (SSD) and Simple Solar Distiller Hybrid Heat Pump (SSDHP) was determined by the orientation, the use of heat pump, the simple or double glass cover. The productivity can exceed 1.2 L/m²h for the SSDHP and 0.5 L/m²h for SSD model. The result of the global efficiency is determined for two models SSD and SSDHP give respectively 30%, 50%. The internal efficiency attained 35% for SSD and 60% of the SSDHP models. Convective heat coefficient can be determined by attained 2.5 W/m²°C and 0.5 W/m²°C respectively for SSDHP and SSD models.

Keywords: productivity, efficiency, convective heat coefficient, SSD model, SSDHPmodel

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Authors: Mirjana Dragas, Marli Gonan Bozac, Morena Paulisic

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Corporate social responsibility (CSR) is a balance between strategic and financial goals of companies, as well as social needs. The integration of competitive strategy and CSR in food and beverage industry has allowed companies to find new sources of competitive advantage. The paper discusses the fact that socially responsible companies encourage co-operation with socially responsible suppliers in order to strengthen market competitiveness. In addition to the descriptive interpretation of the results obtained by a questionnaire, factor analysis was used, while principal components analysis was applied as a factor extraction method. The research results based on two multiple regression analyses show that: (1) selecting the CSR supplier explains a statistically significant part of the variance of the results on the scale of financial aspects of competitiveness (as much as 44.7% of the explained variance); and (2) selecting the CSR supplier is a significant predictor of non-financial aspects of competitiveness (explains 43.9% of the variance of the results on the scale of non-financial aspects of competitiveness). A successful competitive strategy must ultimately support the growth strategy. This implies an analytical approach to finding factors that influence competitiveness through socially sustainable solutions and satisfactory top management decisions.

Keywords: competitiveness, corporate social responsibility, food and beverage industry, supply chain decision making

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Authors: Jitendra Aswani

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In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that.

Keywords: global financial crisis, Asian stock markets, network science, Kruskal algorithm

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Authors: Sally A. Brown

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Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aid teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role

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Authors: Oulad Naoui Noureddine, Cherif ELAmine, Djehiche Abdelkader

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Water resources management includes several disciplines; the modeling of rainfall-runoff relationship is the most important discipline to prevent natural risks. There are several models to study rainfall-runoff relationship in watersheds. However, the majority of these models are not applicable in all basins of the world.  In this study, a new stochastic method called The Only Corresponding Competitor method (OCC) was used for the hydrological modeling of M’ZAB   Watershed (South East of Algeria) to adapt a few empirical models for any hydrological regime.  The results obtained allow to authorize a certain number of visions, in which it would be interesting to experiment with hydrological models that improve collectively or separately the data of a catchment by the OCC method.

Keywords: modelling, optimization, rainfall-runoff relationship, empirical model, OCC

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Authors: Mikhail V. Khachaturyan, Inga A. Koryagina, Maria Nikishova

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The study investigates the impact of the ongoing financial crisis, started in the 2^nd half of 2014, on marketing budgets spent by Fast-moving consumer goods companies. In these conditions, special importance is given to efficient possessory risk management systems. The main objective for establishing and developing possessory risk management systems for FMCG companies in a crisis is to analyze the data relating to the external environment and consumer behavior in a crisis. Another important objective for possessory risk management systems of FMCG companies is to develop measures and mechanisms to maintain and stimulate sales. In this regard, analysis of risks and threats which consumers define as the main reasons affecting their level of consumption become important. It is obvious that in crisis conditions the effective risk management systems responsible for development and implementation of strategies for consumer demand stimulation, as well as the identification, analysis, assessment and management of other types of risks of economic security will be the key to sustainability of a company. In terms of financial and economic crisis, the problem of forming and developing possessory risk management systems becomes critical not only in the context of management models of FMCG companies, but for all the companies operating in other sectors of the Russian economy. This study attempts to analyze the specifics of formation and development of company possessory risk management systems. In the modern economy, special importance among all the types of owner’s risks has the risk of reduction in consumer activity. This type of risk is common not only for the consumer goods trade. Study of consumer activity decline is especially important for Russia due to domestic market of consumer goods being still in the development stage, despite its significant growth. In this regard, it is especially important to form and develop possessory risk management systems for FMCG companies. The authors offer their own interpretation of the process of forming and developing possessory risk management systems within owner’s management models of FMCG companies as well as in Russian economy in general. Proposed methods and mechanisms of problem analysis of formation and development of possessory risk management systems in FMCG companies and the results received can be helpful for researchers interested in problems of consumer goods market development in Russia and overseas.

Keywords: FMCG companies, marketing budget, risk management, owner, Russian economy, organization, formation, development, system

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Authors: Nela Milosevic, Sladjana Barjaktarovic Rakocevic, Sladjana Benkovic, Nemanja Milanovic

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Nowadays, performance measurement systems play a key role in evaluating the strategic performances of an organization. On the other hand, there has been a shift towards the Balanced Scorecard (BSC), which has been recognized as a valuable managerial approach. The main goal of this paper is to analyze the main performances of Serbian banks measured at the branches level, through the usage of the Balanced Scorecard framework. Although an extensive number of practitioners have an interest in the Balanced Scorecard approach, little empirical research has been conducted on the implementation of its concept in the service sector like banks, especially within developing countries. From the beginning of August till the end of September 2015, authors have been conducting in-depth interviews among a number of experts from the most successful banks in Serbia. The results show that the non-financial measures, especially, customer oriented indicators and product/ service oriented indicators, seem to be very important factors for improving not only the financial situation within the bank, but also overall business performances. Additionally, the findings prove that there is the cause-effect relationship between non-financial and financial dimensions of the Balanced Scorecard. Having in mind that the banks are still using outdated performance evaluation systems, such as annual, quarterly and monthly reports, we hope that this paper will contribute to the knowledge of how banks in Serbia may apply the Balanced Scorecard approach to evaluate their performance on the most efficient and effective way.

Keywords: balanced scorecard approach, bank management, performance measurement systems, strategic performances

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Authors: Mirjana Dokmanovic

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The paper will introduce main findings of the research of the responses of the Central European and South Eastern European (CEE/SEE) countries to the global economic and financial crisis in 2008 from human rights and gender perspectives. The research methodology included desk research and qualitative analysis of the available data, studies, statistics, and reports produced by the governments, the UN agencies, international financial institutions (IFIs) and international network of civil society organizations. The main conclusion of the study is that the governments in the region missed to assess the impacts of their anti-crisis policies both ex ante and ex post from the standpoint of human rights and gender equality. Majority of the countries have focused their efforts solely on prompting up the banking and financial sectors, and construction business sectors. The tremendous debt which the states have accumulated for the rescue of banks and industries lead to further cuts in social expenses and reduction of public services. Decreasing state support to health care and social protection and declining family incomes made social services unaffordable for many families. Thus, the economic and financial crisis stirred up the care crisis that was absorbed by women’s intensifying unpaid work within a family and household to manage household survival strategy. On the other hand, increased burden of the care work weakened the position of women in the labour market and their opportunities to find a job. The study indicates that the artificial separation of the real economy and the sphere of social reproduction still persist. This has created additional burden of unpaid work of women within a family. The aim of this paper is to introduce the lessons learnt for future: (a) human rights may not be derogated in the times of crisis; (b) the obligation of states to mitigate negative impacts of economic policies to population, particularly to vulnerable groups, must be prioritized; (c) IFIs and business sector must be liable as duty bearers with respect to human rights commitments.

Keywords: CEE/SEE region, global financial and economic crisis, international financial institutions, human rights commitments, principle of non-derogability of human rights

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Authors: Candida Petrogalli, Giovanni Incerti, Luigi Solazzi

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This paper describes three lumped parameters models for the study of the dynamic behaviour of a boom crane. The models proposed here allow evaluating the fluctuations of the load arising from the rope and structure elasticity and from the type of the motion command imposed by the winch. A calculation software was developed in order to determine the actual acceleration of the lifted mass and the dynamic overload during the lifting phase. Some application examples are presented, with the aim of showing the correlation between the magnitude of the stress and the type of the employed motion command.

Keywords: crane, dynamic model, overloading condition, vibration

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Authors: Jill Round

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In the economic system, the financial sector plays a crucial role as an intermediary between market participants, other financial institutions, and customers. Financial institutions such as banks have to make decisions to satisfy the demands of all the participants by keeping abreast of regulatory change. In recent years, progress has been made regarding frameworks, development of rules, standards, and processes to manage risks in the banking sector. The increasing focus of regulators and policymakers placed on risk management, corporate governance, and the organization’s culture is of special interest as it requires a well-resourced risk controlling function, compliance function, and internal audit function. In the past years, the relevance of these functions that make up the so-called Three Lines of Defense has moved from the backroom to the boardroom. The approach of the model can vary based on the various organizational characteristics. Due to the intense regulatory requirements, organizations operating in the financial sector have more mature models. In less regulated industries there is more cloudiness about what tasks are allocated where. All parties strive to achieve their objectives through the effective management of risks and serve the identical stakeholders. Today, the Three Lines of Defense model is used throughout the world. The research looks at trends and emerging issues in the professions of the Three Lines of Defense within the banking sector. The answers are believed to helping to explain the increasing regulatory requirements for the banking sector. While the number of supervisory practices increases the risk management requirements intensify and demand more regulatory compliance at the same time. The Structural Equation Modeling (SEM) is applied by making use of conducted surveys in the research field. It aims to describe (i) the theoretical model regarding the applicable linearity relationships, (ii) the causal relationship between multiple predictors (exogenous) and multiple dependent variables (endogenous), (iii) taking into consideration the unobservable variables and (iv) the measurement errors. The surveys conducted on the research field suggest that the observable variables are caused by various latent variables. The SEM consists of the 1) measurement model and the 2) structural model. There is a detectable correlation regarding the cause-effect relationship among the performed supervisory practices and the increasing scope of regulation. Supervisory practices reinforce the regulatory density. In the past, controls were placed after supervisory practices were conducted or incidents occurred. In further research, it is of interest to examine, whether risk management is proactive, reactive to incidents and supervisory practices or can be both at the same time.

Keywords: risk management, structural equation model, supervisory practice, three lines of defense

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Rebecca Hafner, Daniel Read, David Elmes

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The persuasive potential of normative and feedback (financial vs. environmental) information in ‘nudging’ people towards making environmentally sound decisions was explored in a hypothetical choice experiment. The research was specifically focused on determining how subtle variations in the decision frame could be used to increase the selection of energy efficient vs. standard technologies, using the context of home heating choice. Participants were given a choice of a standard heating system (a gas boiler) and a relatively more-energy efficient option (a heat pump). The experiment had a 2 (normative vs. no normative information) by 3 feedback type (financial, environmental, none) design. The last group constituted the control. Half of the participants were given normative information about what the majority of others in their neighbourhood had opted to do when faced with the same choice set, prior to making their decision. The other half received no such information. Varying feedback frames were incorporated by providing participants with information on either financial or environmental savings that could be achieved by choosing the heat pump. No such information was provided in the control group. A significant interaction was found between normative information and feedback frame type. Specifically, the impact of feedback frames was found to be reduced when normative information was provided; illustrating the overriding influence of normative information on option preference. Participants were significantly more likely to select the heat pump if they were vs. were not given normative information. Yet when no normative information was provided, the persuasive influence of the financial frame was increased – highlighting this as an effective means of encouraging uptake of new technologies in this instance. Conversely, the environmental frame was not found to differ significantly from the control. Marginal carryover effects were also found for stated future real-life decision-making behaviour, with participants who were versus were not given normative information being marginally more likely to state they would consider installing a heat pump when they next need to replace their heating system in real life. We conclude that normative and financial feedback framing techniques are highly effective in increasing uptake of new, energy efficient heating technologies involving significant upfront financial outlay. The implications for researchers looking to promote ‘green’ choice in the context of new technology adoption are discussed.

Keywords: energy-efficient technology adoption, environmental decision making, financial vs. environmental feedback framing techniques, social norms

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Authors: Muhammad Fanseem E. M., Rama Satya Satish Kumar, Indrajeet Bhausaheb Bhavar, Deepak M.

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Keeping the right balance of electricity between the supply and demand sides of the grid is one of the most important objectives of electrical grid operation. Power generation and demand forecasting are the core of power management and generation scheduling. Large, centralized producing units were used in the construction of conventional power systems in the past. A certain level of balance was possible since the generation kept up with the power demand. However, integrating renewable energy sources into power networks has proven to be a difficult challenge due to its intermittent nature. The power imbalance caused by rising demands and peak loads is negatively affecting power quality and dependability. Demand side management and demand response were one of the solutions, keeping generation the same but altering or rescheduling or shedding completely the load or demand. However, shedding the load or rescheduling is not an efficient way. There comes the significance of virtual power plants. The virtual power plant integrates distributed generation, dispatchable load, and distributed energy storage organically by using complementing control approaches and communication technologies. This would eventually increase the utilization rate and financial advantages of distributed energy resources. Most of the writing on virtual power plant models ignored technical limitations, and modeling was done in favor of a financial or commercial viewpoint. Therefore, this paper aims to address the modeling intricacies of VPPs and their technical limitations, shedding light on a holistic understanding of this innovative power management approach.

Keywords: cost optimization, distributed energy resources, dynamic modeling, model quality tests, power system modeling

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Lucie Cote, Sonia McFadden

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Mental health problems in the workplace are currently one of the main causes of absences. Research work has highlighted the importance of a collaborative process involving the stakeholders in the return-to-work process and has established the best management practices to ensure a successful return-to-work. However, very few studies have specifically explored the combination of various management models and determined whether they could satisfy the needs of the stakeholders. The objective of this study is to analyze two models for managing the return to work: the ‘medical-administrative’ and the ‘support of the worker’ in order to understand the actions and actors involved in these models. The study also aims to explore whether these models meet the needs of the actors involved in the management of the return to work. A qualitative case study was conducted in a Canadian federal organization. An abundant internal documentation and semi-directed interviews with six managers, six workers and four human resources professionals involved in the management of records of employees returning to work after a mental health problem resulted in a complete picture of the return to work management practices used in this organization. The triangulation of this data facilitated the examination of the benefits and limitations of each approach. The results suggest that the actions of management for employee return to work from both models of management ‘support of the worker’ and ‘medical-administrative’ are compatible and can meet the needs of the actors involved in the return to work. More research is needed to develop a structured model integrating best practices of the two approaches to ensure the success of the return to work.

Keywords: return to work, mental health, management models, organizations

Procedia PDF Downloads 206