• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.87-124
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• 2004

Some studies indicate that investors systematically underreact to new information in the stock market and Other studies indicate that investors systematically overreact. If investors irrationally react to the R&D intensity information, The portfolio strategy based on the R&D intensity information will be provided substantial excess returns. This study investigate that investors systematically underreact or overreact to the R&D intensity and whether portfolio strategy based on the R&D intensity is useful or not. Major results we as follows. First, This study indicate that investor systematically underreact to high R&D intensity and overreact low R&D intensity information. Second, after controlling the firm's specific factor such as firm size, BV/MV and past price performance, it is found that the performance of portfolio strategy based on the R&D intensity is not significant.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.188-198
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• 2016

This study examined the effects of a smoking cessation coaching program based on the motivation stage applying the Transtheoretical Model to stop the smoking of patients in terms of the amount of smoking, nicotine dependence, CO level, and urine cotinine. The study design was a multi-repeat multiple repeat intermittent time series study with one-group, a pre-post design. The participants were 47 smoking patients (44 males and 3 females), who were treated at a public hospital in N city. The participants were 4 (8.51%) subjects in the action stage and 43 subjects (91.49%) in the preparation stage of the motivation stage. The coaching program intervention was conducted at the first day, second week, and 6th week. The smoking cessation maintenance of the subjects was checked at the 12th week. A chi-square test and t-test were used to analyze the data. The subjects in the action stage were kept under the condition of no smoking and nicotine dependence. After the program of subjects in the preparation stage, the amount of smoking, nicotine dependence, and CO level were significantly lower compared to the pre-test (p<.001). The findings suggest that the coaching program based on the motivation stage was effective in improving the smoking cessation for patients who smoke. On the other hand, the patients in the smoking cessation program may require much more financial assistance than those of healthy people. A greater workforce and budget will be needed for patients to stop smoking.