• Management Science and Financial Engineering
• /
• v.2 no.1
• /
• pp.73-101
• /
• 1996

We show assets can be classified into diversifiable risks and non-diversifiable risks based on aggregate endowment and spanning so that in equilibrium agents eliminate diversifiable risks which must have zero values. Consequently, the benchmark portfolio that represents a pricing operator should have only a non-diversifiable risk, aggregate endowment should earn a positive risk premium over a riskless asset, and, even in incomplete markets, there should be a pricing operator represented by a function of aggregate endowment if any asset mean-independent of aggregate endowment is diversifiable. These results apply to both the CAPM and a representative agent model.

• Journal of Information Technology Applications and Management
• /
• v.23 no.2
• /
• pp.195-206
• /
• 2016

Mobile financial services with incorporated into IT are actively introduced and being operated worldwide. Meanwhile, a relationship setting of industrial capital and financial capital has a close connection with development process of the financial markets and the economic development. If the relationship setting of industrial capital and financial capital are right, it will be good opportunity to ensure economic development, positive economic effect and global competitiveness of the financial industry as other developed countries. In order to expand the positive effects of these mobile financial services, a ICT companies, etc. should ease regulations to allow entry to the mobile financial services market. That is, the separation of banking and commerce should be abolished.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.361-381
• /
• 2023

Research on corporate bankruptcy prediction has been focused on financial information. Since the company's financial information is updated quarterly, there is a problem that timeliness is insufficient in predicting the possibility of a company's business closure in real time. Evaluated companies that want to improve this need a method of judging the soundness of a company that uses information other than financial information to judge the soundness of a target company. To this end, as information technology has made it easier to collect non-financial information about companies, research has been conducted to apply additional variables and various methodologies other than financial information to predict corporate bankruptcy. It has become an important research task to determine whether it has an effect. In this study, we examined the impact of electronic payment-related information, which constitutes non-financial information, when predicting the closure of business operators using electronic payment service and examined the difference in closure prediction accuracy according to the combination of financial and non-financial information. Specifically, three research models consisting of a financial information model, a non-financial information model, and a combined model were designed, and the closure prediction accuracy was confirmed with six algorithms including the Multi Layer Perceptron (MLP) algorithm. The model combining financial and non-financial information showed the highest prediction accuracy, followed by the non-financial information model and the financial information model in order. As for the prediction accuracy of business closure by algorithm, XGBoost showed the highest prediction accuracy among the six algorithms. As a result of examining the relative importance of a total of 87 variables used to predict business closure, it was confirmed that more than 70% of the top 20 variables that had a significant impact on the prediction of business closure were non-financial information. Through this, it was confirmed that electronic payment-related information of non-financial information is an important variable in predicting business closure, and the possibility of using non-financial information as an alternative to financial information was also examined. Based on this study, the importance of collecting and utilizing non-financial information as information that can predict business closure is recognized, and a plan to utilize it for corporate decision-making is also proposed.

• The Journal of Industrial Distribution & Business
• /
• v.11 no.2
• /
• pp.25-31
• /
• 2020

Purpose: The AEO (Authorized Economic Operator) program, created in 2001 in the United States due to 9.11 terrorist's attack, fundamentally changed the trade environment. Korea, which introduced AEO program in 2009, has become one of the world's top countries in the program by ranking 6th in the number of AEO certified companies and the world's No. 1 in MRA (Mutual Recognition Agreement) conclusions. In this paper, we examined what trade-economic and non-economic effects the AEO program and its MRA have in Korea. Research design, data and methodology: In this study we developed a model to verify the impact between utilization of AEO and trade-economic effects of the AEO and its MRA. After analyzing the validity and reliability of the model through Structural Equation Model we conducted a survey to request AEO companies to respond their experience on the effects of AEO program and MRA. As a result, 196 responses were received from 176 AEO companies and utilized in the analysis. Results: With regard to economic effects, the AEO program and the MRA have not been directly linked to financial performance, such as increased sales, increased export and import volumes, reduced management costs, and increased operating profit margins. However, it was analyzed that the positive effects of supply chain management were evident, such as strengthening self-security, monitoring and evaluating risks regularly, strengthening cooperation with trading companies, enhancing cargo tracking capabilities, and reducing the time required for export and import. Conclusions: When it comes to the trade-economic effects of AEO program and its MRA, AEO companies did not satisfy with direct effects, such as increased sales and volume of imports and exports, reduced logistics costs. However, non-economic effects, such as reduced time in customs clearance, freight tracking capability, enhanced security in supply chain are still appears to be big for them. In a rapidly changing trade environment the AEO and MRA are still useful. Therefore the government needs to encourage non-AEO companies to join the AEO program, expand MRA conclusion with AEO adopted countries especially developing ones and help AEO companies make good use of AEO and MRA.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.69-85
• /
• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.