We propose a heuristic algorithm for war-game model that is appropriate for warfare in which the maneuver of the attacker is relatively certain. Our model is based on a multi-weapon extention of the Lanchester's square law. However, instead of dealing with the differential equations, we use a multi-period linear approximation which not only facilitates a solution method but also reflects discrete natures of warfare. Then our game model turns out to be a continuous game known to have an ${\varepsilon}$-Nash equilibrium for all ${\varepsilon}{\geq}0$. Therefore, our model approximates an optimal warfare strategies for both players as well as an efficient reinforcement of area defense system that guarantees a peaceful equilibrium. Finally, we report the performance of a practical best-response type heuristic for finding an ${\varepsilon}$-Nash equilibrium for a real-scale problem.

We analyzed the structures and properties of the global financial market networks using social network analysis approach. The Minimum Spanning Tree (MST) lengths and networks of the global financial markets based on the correlation coefficients have been analyzed. Firstly, similar to the previous studies on the global stock indices using MST length, the diversification effects in the global multi-asset portfolio can disappear during the crisis as the correlations among the asset class and within the asset class increase due to the system risks. Second, through the network visualization, we found the clustering of the asset class in the global financial markets network, which confirms the possible diversification effect in the global multi-asset portfolio. Meanwhile, we found the changes in the structure of the network during the crisis. For the last one, in terms of the degree centrality, the stock indices were the most influential to other assets in the global financial markets network, while in terms of the betweenness centrality, Gold, Silver and AUD. In the practical perspective, we propose the methods such as MST length and network visualization to monitor the change of the correlation risk for the risk management of the multi-asset portfolio.

Markowitz's portfolio selection model is used to construct an optimal portfolio which has minimum variance, while satisfying a minimum required expected return. The model uses estimators based on analysis of historical data to estimate the returns, standard deviations, and correlation coefficients of individual stocks being considered for investment. However, due to the inaccuracies involved in estimations, the true optimality of a portfolio constructed using the model is questionable. To investigate the effect of estimation inaccuracy on actual portfolio performance, we study the changes in a portfolio's realized return and standard deviation as the accuracy of the estimations for each stock's return, standard deviation, and correlation coefficient is increased. Furthermore, we empirically analyze the portfolio's performance by comparing it with the performance of active mutual funds that are being traded in the Korean stock market and the KOSPI benchmark index, in terms of portfolio returns, standard deviations of returns, and Sharpe ratios. Our results suggest that, among the three input parameters, the accuracy of the estimated returns of individual stocks has the largest effect on performance, while the accuracy of the estimates of the standard deviation of each stock's returns and the correlation coefficient between different stocks have smaller effects. In addition, it is shown that even a small increase in the accuracy of the estimated return of individual stocks improves the portfolio's performance substantially, suggesting that Markowitz's model can be more effectively applied in real-life investments with just an incremental effort to increase estimation accuracy.

Together with soaring interest on Big Data, now there are vigorous reports that unearth various social values lying underneath those data from a number of application areas. Among those reports many are using such data as Internet search histories from Google site, social relationships from Facebook, and transactional or locational traces collected from various ubiquitous devices. Many of those researches, however, are conducted based on the data sets that are accumulated over the North American and European areas, which means that direct interpretation and application of social values exhibited by those researches to the other areas like Korea can be a disturbing task. This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google search volume on a carefully selected set of terms shows high market performance. A huge difference between North American and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume over a specified word set needs more conscious approach.

Circular shareholding is established when at least three member firms in a business group hold stock in other member firms and form a series of ownership in a circular way. Although there have been many studies which investigated a negative effect of circular shareholding on firm's value, few studies have discussed how to resolve the problem given complicated ownership structures of large business groups. This paper is based on a mixed integer programming model, which was proposed in the author's previous research and can identify the ownership share divested in order to resolve circular shareholding. Since the optimization model becomes too complicated for large business groups and requires a sophisticated software to solve it, we propose a simple heuristic method that can find a good approximate solution to the model. Its applications to twelve Korean large business groups show that the heuristic method is not just computationally attractive but also provides near-optimal solutions in most cases.

In this paper, we examine factors of success in online P2P (peer-to-peer) lending auctions. This paper finds the following empirical results. First, loan applicants with a stable employment status are more likely to succeed in the auction than loan applicants with an unstable employment status. Second, loan applicants, who actively share personal information and interact with lenders through online message boards, are likely to succeed in the auction. Third, the purpose of a loan for debt repayment has a significant impact on the success of the auction. However, the purpose of a loan for essential living expenses such as housing, living, and medical expenses has an insignificant relationship with the success of the auction. Our results imply that the characteristics of loan applicants such as employment status and social interaction are the factors of success in online P2P lending auctions.

Information system (IS) security continues to present a challenge for firms. Especially, IT security accident is recently taking place successively in the financial sector. Thus, a comprehensive measure on this is demanded. A large part of a research on security relies upon technical design in nature and is restrictive in a consideration of person and organizational issue. To achieve a goal of firm security, it is possible with an effort of organizational management and supervision for maintaining the technical and procedural status. Based on a theory of accountability, we propose that the security countermeasures of organization lead to an increase in accountability and reduction in risk of IT security in a financial firm and further to firm performance like promotion in firm reliability. In addition, we investigate which difference a theoretical model shows by comparison between South Korean and American financial firms. As a result of analysis, it found that South Korea and America have significant difference, but that a measure on the financing IT security is important for both countries. We aim to enhance interpretability of a research on security by comparatively analysis between countries and conducting a study focus on specific firm called financial business. Our study suggest new theoretical framework to a research of security and provide guideline on design of security to financial firm.