• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.629-639
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• 2020

The current study explains how corruption, terrorism, political stability and oil price has an effect on on the Iraq stock exchange utilizing corruption perception index as a proxy of corruption, global terrorism index as proxy for terrorism, political stability and oil price with ISX60 index as proxy of stock market for the period (2005-2019) using Ordinary Least Square method. The results show that the level of corruption, terrorism activities and political stability coefficient is significantly positive with Iraq stock exchange. In contrast, the oil price coefficient is significantly negative with Iraq stock exchange, which means that lower levels of corruption, less terrorism activities and more stability in political system have strong influence on stock market development in Iraq. The study concludes that the explanatory variables are important for Iraq stock exchange. Hence, the study suggests the policy makers to develop stock market by implementing policies and strategies to overcome high level of corruption, terrorism activities especially after ISIS/ISIL announcement has been made public. There is a need for transparency and creating stable political environment through good governance practices in order to attract more foreign investment and promote economic development. Factors like terrorism and corruption make economic and political systems unstable and has an adverse effect on on Iraq's stock exchange performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.636-647
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2-echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.159-165
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• 2003

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. Since it has been known that traditional reorder policies sometimes show poor performance in distribution systems, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately f3r the 2-echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value fur general multi-echelon systems is very complex, we provide two approximation methods. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• IE interfaces
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• v.17 no.3
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• pp.359-374
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2- echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.4
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• pp.23-33
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• 2003

The possibility of real time analysis about hot melt resins and pressure sensitive adhesives in newsprint stock was investigated by performing comparative tests using conventional image analysis method and real time contaminants analyzer. Based on the test results, the performance of real time contaminants analyzer in terms of detecting primary stickies in newsprint stock could be verified. Real time stickies analysis showed good precision and over-estimation of hot melt resins and under-estimation of pressure sensitive adhesives could be corrected by adapting new method. Real time analysis of primary stickies in the actual newsprint stock also showed good correlation with conventional image analysis and the performance of real time contaminants analyzer could be verified again. Adjustment of the contrast sensitivity of real time contaminants analyzer was enough to set the proper monitoring conditions for primary stickies in newsprint stock.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.291-301
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• 2020

This paper aims to investigate the impact of chief executive officer's (CEO) attributes on firms' performance. Specifically, it examines the influence of CEOs' education, professional experience, and tenure on Saudi firms' performance. We look at a sample of 120 listed firms on Tadawul stock exchange from 2014 to 2017. Data on financial and accounting variables are obtained from the annual reports of the selected companies. We follow the existing empirical literature and use a panel model and formulate three different equations using the GMM estimator. Findings prove that CEO educational background does matter. In particular, companies employing CEOs with business administration, economics, finance, or accounting degree will perform outstandingly better. Similarly, stock performance gets improved when the CEO has a postgraduate qualification, i.e., when the CEO holds an MBA, a master, or a PhD degree. Besides, results reveal that executives who have an experience in a related field will positively affect the firm's performance. Finally, evidence shows that high CEOs tenure improves corporate performance. Overall, these findings demonstrate that executives' attributes are key factors that would explain differences in Saudi firms' performance. These results would help shareholders to make the right decision in selecting CEOs to manage the company.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.845-853
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• 2021

The stock market shows the current health of an economy, and investment performance represents it. This study aims to clarify the relationship between financial behavior and investment decisions as well as its impact on investment results. Determine the influence of behavioral factors on individual investors' investment decisions and investment performance on the Vietnam stock market. The study surveyed 250 investors. The main analytical methods used are Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). Research results show that Heuristic, Prospect, Market, and Herding directly and positively affect investment decision-making. Besides, the above factors have a direct and positive effect on investment performance. In particular, the Prospect factor has the strongest influence on investment decision-making and investment performance. The major findings of this study suggested that the important role of Heuristic, Prospect, Market, and Herding on Investment Decision-making and Investment Performance. Prospect had the strongest impact on Investment decision-making (β = 0.275). Heuristic had the second strongest impact (β = 0.257), then Herding (β = 0.202), and finally Market (β = 0.189) had the weakest effect. Regarding Investment Performance, the Prospect factor has a higher degree of impact than Heuristic Herding and Market.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.433-446
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• 2021

This study aims to identify the elasticities and casualties of financial performance and determinants of the mining and extractive companies listed in Jordan's stock market over the 2005-2018 period. The conceptual framework is based on the Resource-Based View theory and Arbitrage Pricing theory is used to describe the relationship between the external environment and the financial performance of the companies. Profitability ratio (return on assets) is utilized as a proxy of financial performance measurement. Meantime, the company's characteristics, macroeconomic variables, and non-economic factors are utilized as independent factors. Data sources are panel data set for mining and extractive companies over the above period. Fully Modified Ordinary Least Square (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Pooled Mean Group (PMG) methods are applied. The empirical findings indicated that company size, sales growth, financial leverage, liquidity, and GDP growth were the critical determinants of mining and extractive companies' financial performance in the Amman Stock Exchange. Thus, the findings conclude that company characteristics and GDP growth mainly drive financial performance. Moreover, the findings reveal that a bidirectional causal elasticity exists between GDP and financial leverage and return on assets (ROA). Sound financial performance can be obtained by paying more attention to GDP growth and firms' characteristics.

• Journal of the Korean Society for Railway
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• v.9 no.6 s.37
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• pp.772-777
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• 2006

Three-dimensional numerical study is performed for the flow analysis around the rolling stock with square cross section (Mugungwha train model). The height (H) of rolling stock is considered as the characteristic length and the total length of rolling stock is 40 which correspond to 1/2 unit of rolling stock. The gap between the surface and rolling stock is 0.17H which is average value. The relative velocity between the surface and rolling stock is assumed to be zero and Re=10,000 based on the characteristic length. Low Re ${\kappa}-{\epsilon}$[15] is employed for the calculation of turbulence which resolve all the way to the solid surface (laminar sub-layer). Large flow separation occurred at the front head of train and a pair of vortex is generated on both top and side of rolling stock. The behavior of vortices on the top of the rolling stock is believed to affect the performance of the pantograph which should be intensively investigated. The difference between the high pressure in the front stagnation region of train and the low pressure in the rear separated region causes a large pressure drag. A large pair or vortex are generated in the rear of train and the size of vortex is increased more than the size of cross section of train.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.154-161
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• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.