• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1049-1060
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• 2009

The expansion of volatility in Korean Stock Market made it more difficult for the individual to invest directly and increased the weight of indirect investment through a fund. The purpose of this study is to construct the EIF(enhanced index fund) model achieves an excessive return among several types of fund. For this purpose, this paper propose portfolio optimization model to manage an index fund by using GA(genetic algorithm), and apply the trading amount and the closing price of standard index to earn an excessive return add to index fund return. The result of the empirical analysis of this study suggested that the proposed model is well represented the trend of KOSPI 200 and the new investment strategies using this can make higher returns than Buy-and-Hold strategy by an index fund, if an appropriate number of stocks included.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.417-425
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• 2020

In this paper, value relevance of the level of dependence on separate accounts in non-life-insurance companies is studied. As noted by Shim et al. (2015), the separate accounts of insurance companies consist of contracts with different attributes from the general accounts, so it is likely that firm value will vary depending on the insurer's dependence on the separate accounts. Thus, in this paper, an empirical analysis has been conducted using quarterly financial data and stock price data from domestic listed non-life-insurance companies from 2011 to 2018. The analysis shows that variables representing the level of dependence on separate accounts have a significant negative relevance to firm value. These results may suggest that changes in the proportion of a non-life-insurer's separate accounts may result in a change to its firm value under the same net assets and net income scales in aggregate accounts. This study provides management implications for the operation of separate accounts from the perspective of maximizing firm value. In addition, this study suggests that disclosure system improvement would be necessary to more directly report the operational performance of the separate accounts.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.135-149
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• 2021

Purpose - I analyzes risk-to-performance evaluated in the market using data from sale and lease back. Specifically, I analyze from the perspective of financial institutions that purchase sale and lease back based on the cases of investment by ship investment companies and acquisition of ships. Design/methodology/approach - I use 49 sale and lease back data from 2017 to 2019 for empirical analysis. Findings - The main results of this paper are as follows. First, after sale and lease back of domestic ships, the average amount of sales by the leased shipping company is 25.1 billion won, the average amount of investment by the purchased financial institution is 14.6 billion won (60%) and the average length of the ship is nine years. In ship finance, sale and lease back is deemed to be appropriately used as a means of restructuring for a large amount of money. Second, the main risk factor for sale and lease back of domestic ships is credit risk and can be measured in VaR in practice. As a result of the empirical analysis, the average credit risk burden ratio is 9%. As a major risk factor, low creditworthiness of restructuring companies is the key. Third, as a result of measuring the profitability of financial institutions that purchase sale and lease back of domestic ships at a net current price, it has an average value of 300 million won, but the deviation by case is very large. Fourth, the risk adjusted performance of sale and lease back of domestic ships is 0.54 on average compared to the total risk capital, and 0.52 compared to the stock-risk capital, and as with profitability earlier, the deviation of each case is very large and misaligned. In order to boost the sale and lease back market for large and long-term assets, in order to overcome low profitability as a prerequisite for future participation of commercial purchased financial institutions, it is expected that purchase decisions based on expectations versus risk will be necessary. Research implications or Originality - The results of this paper are expected to broaden the understanding of sale and lease back and foster the ability to assess long-term risk and performance. Based on this, it is believed that rapid restructuring of companies through sale and lease back of large amounts of long-term assets will greatly increase the utility of the domestic financial market.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.97-109
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• 2014

The purpose of this study is, as to verify the effect of IR announcements, the IR activity to look at the usefulness. In previous study, they found that the IR announcement leads to reductions in information asymmetry, effect to positive stock price. This study examine the abnormal returns between group by corporate characteristics. The data used in this study are daily stock market returns taken from the KOSDAQ listed company with IR announcements during the 2005-2012 year(8 year). We find that follows. First, the capital market is accepted IR activity as the positive information. Second, abnormal returns of small company is higher than big size that. We show the difference of abnormal returns between the venture company and general company, the venture company's high. The abnormal returns of corporate with high ownership is above the group of low ownership. Additionally, consider interaction by firm characteristics, we show the interaction between firm size and business type. The result of two-way ANOVA is that venture corporate with big size are more abnormal returns than others. Also, we demonstrate that firm location is the factor of difference on information effect in venture firm.

• Management & Information Systems Review
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• v.33 no.1
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• pp.45-63
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• 2014

A trading system is a computer trading program that automatically submits trades to an exchange. Mechanical a trading system to execute trade is spreading in the stock market. However, a trading system to trade a single asset might occur instability of the profit because payoff of this system is determined a asset movement. Therefore, it is necessary to develop a trading system that is trade two assets such as a pair trading that is to sell overvalued assets and buy the undervalued ones. The aim of this study is to propose a relative value based trading system designed to yield stable and profitable profits regardless of market conditions. In fact, we propose a procedure for building a trading system that is based on the rough set analysis of indicators derived from a price ratio between two assets. KOSPI 200 index futures and S&P 500 index futures are used as a data for evaluation of the proposed trading system. We intend to examine the usefulness of this model through an empirical study.

• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.269-283
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• 2023

Based on daily data from January 4, 2016 to September 27, 2022, the impact of extreme movements of BDI on shipping companies' network connectivity was analyzed using CoVaR network connectivity. The main results and policy implications are as follows. First, according to the copula model results, the Student-t copula was selected as the most suitable model for COSCO, HMM, HRAG, MAERSK, and WAN. EVER was selected as a time-varying Gumbel copula, and YANG was selected as a time-varying rotated-Gumbel copula. Second, as a result of analysis using the TVP-VAR model, the linkage between shipping companies tended to increase when the BDI turned into an extreme risk state. In the comparison of net connectivity, the roles of COSCO and EVER changed. In addition, in the analysis of net pairwise connectivity, it was found that the change in the extreme risk state of BDI also affected the connectivity of shipping companies. In particular, EVER, WAN, and COSCO showed large changes. Taken together, the extreme fluctuations in BDI changed the role of Asian shipping companies, intensifying competition among shipping companies and strengthening risk delivery. It was confirmed that BDI has a great influence on the network connectivity of shipping companies and has an important influence on the stability of the stock market network. Therefore, the results of this study should consider not only the connectivity of shipping companies according to market conditions, but also the connectivity in extreme situations.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.81-96
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• 2016

This paper analyzes the impact of information breach on shareholder value by measuring the stock price reaction associated with the announcements of data breach. The breach firms in the sample lost, on average, 1.3% of their market value, amounting to 98.9 million won of loss within two-day of the event period after the announcement. We examine the abnormal returns in various categories (i.e., source, type, size, etc.) of information breach. Although the market does not react significantly to the announcements of outside breach, we find statistically significant market reactions to inside breach. We estimate abnormal returns over the following 60 days. The mean 60-day cumulative abnormal return and BHAR (buy-and-hold abnormal returns) are both significantly far from zero. We conclude that there is a coherent market reaction following the announcement. The difference between the market reactions to IT firms and Non-IT firms is statistically significant. But breach amount, firm size, and the year the breach occurred do not show to be significant variables.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.6
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• pp.873-883
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• 2000

The purpose of this study were to investigate the relationships of situation variables, product variables. consumer variables and impulse buying behavior in apparel store. We collected data from 462 consumers of adult women living in Pusan and analysed by factor analysis, cluster analysis, analysis of variance, t-test and discriminant analysis. The results were as follows: First, The purchase situation influenced on the impulse buying behavior consisted of the Pre-purchase condition and the Point-of-purchase state. The in-store situation consisted of the Salesman/store atmosphere, the Low price and the Possibility of out of stock. And the consumption values of apparel are divided into four factors ; Emotional/aesthetical value, Epistemic value, Functional value and Social value. The clothing shopping orientation as consumer variable extracted six factors ; Recreational orientation, Economical orientation, Brand/store loyalty orientation, Careful orientation, Apathetic orientation and Positive orientation. Consumers were classified by the cloting shopping orientation into the Convenience shopper, the Recreational shopper, the Economical shopper and the Careful shopper. Second, In comparison with the unimpulse-buyin groups, the impulse-buying group is more effected by in-store situation than purchase situation, and were more effected by Emotional/aesthetical value, Social value and Epistemic value of the consumption value. In consumer types, the more was the Recreational shopper and the Convenience shopper, the more showed impulse buying behavior. And the important factor distinguished between the impulse buying group and the unimpulse buying group was the Salesman/store atmosphere of the in-store situation.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.1-7
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• 2011

The methodology of KOSPI forecast has been considered as one of the most difficult problem to develop accurately since short-term KOSPI is correlated with various factors including politics and economics. In this paper, we presents a methodology for forecasting short-term trends of stock price for five days using the feature selection method based on a neural network with weighted fuzzy membership functions (NEWFM). The distributed non-overlap area measurement method selects the minimized number of input features by removing the worst input features one by one. A technical indicator are selected for preprocessing KOSPI data in the first step. In the second step, thirty-nine numbers of input features are produced by wavelet transforms. Twelve numbers of input features are selected as the minimized numbers of input features from thirty-nine numbers of input features using the non-overlap area distribution measurement method. The proposed method shows that sensitivity, specificity, and accuracy rates are 72.79%, 74.76%, and 73.84%, respectively.