• Management & Information Systems Review
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• v.35 no.4
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• pp.1-19
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• 2016

The researchers in strategic management have focused on identifying the effects of CEO's demographic characteristics and experience on the strategic choices and performance of firms. On the other hand, they have failed to identifying the effects of CEO's psychological characteristics on them because of the difficulties over data collection and measurement for variables. To overcome this limitation of prior researches, this study is designed to achieve two specific objectives. The first is to examine the effect of CEO narcissism on diversification strategy and performance of listed corporations on Korean securities market in an economic downturn. The other is to examine the moderating effects of various corporate governance systems that are related to board and/or ownership structures on those relationships. The empirical setting for this study was drawn from a multi-year(2011~2014) sample of large listed corporations in Korean securities market. To achieve the objectives, the hypotheses of research are analyzed by implementing multiple regression analyses in two separate models. The results of these analyses show that CEO narcissism is positively related to the diversification of listed large corporations in Korean securities market. Regrading the moderating effects, the stake of institutional investors weakens the positive relationship between CEO narcissism and firm's diversification. The findings of this research imply that CEO narcissism can intensify the tendency of Korean corporations to adopt high-risk and high return strategy in an economic downturn. Thus, firms might be able to use CEO narcissism to drastically restructure the business portfolio in an economic downturn. However, Korean corporations should be very cautions to maximize the positive effect of CEO narcissism. They might be use the institutional investors as their corporate governance system to monitor and control the opportunism of CEO in the decision for diversification in an economic downturn.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.63-75
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• 2023

This study conducted empirical analysis on the factors affecting the investment performance of 205 domestic venture funds (with a total liquidation amount of 7.25 trillion KRW) newly formed from 2007 to 2017 and completely liquidated as of the end of 2022. Due to the nature of private equity funds, obtaining empirical data is extremely challenging, especially for data post-COVID-19 era liquidations. Nevertheless, despite these challenges, it is meaningful to analyze the impact on the investment returns of domestic venture funds using the most recent data available from the past 10 years. This study categorized the factors influencing venture fund performance into external environmental factors and internal factors. External environmental factors included "economic cycles," "stock markets," "venture markets," and "exit markets," while internal factors included the fund management company's capabilities in terms of "experience," "professional personnel," and "assets under management (AUM)." The fund structure was also categorized into "fund size" and "fund length" for comparative analysis. In summary, the analysis yielded the following results: First, the 3-year government bond yield, which represents economic cycles well, was found to have a significant impact on fund performance. Second, the average 3-month KOSDAQ index return after fund formation had a statistically significant positive effect on fund performance. Third, the number of IPOs, indicating the competition intensity at the time of venture fund liquidation, was shown to have a negative effect on fund performance. Fourth, it was observed that the larger the AUM of the fund management company, the better the fund's returns. Finally, venture fund returns showed variations depending on the year of formation (Vintage). Therefore, when individuals consider investing in venture funds, it is considered a highly effective investment strategy to construct an investment portfolio taking into account not only external environmental factors and internal fund factors but also the vintage year.

• Journal of Christian Education in Korea
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• v.61
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• pp.165-201
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• 2020

The purpose of this study is to explore the development of language education of Christian early childhood education by exploring the change of pre-Christian preschool teachers through the development of biblical language education activities. Interviews, surveys, action plans, and reflections of 19 Christian education students who participated in the development of bible-based language education activities for children based on the language of early childhood language, were conducted from September 3 to December 28, 2018. The data were collected through a portfolio. By analyzing the collected data, the key categories were derived and categorized. For the objectification of data analysis and interpretation, two thematic and early childhood education specialists were identified. As a result, the preparatory Christian teacher experience for the development of bible-based langage education activities for young children was categorized into cognitive change, personality change and practical change. First, through the development of bible-based early childhood language education activities, Christian pre-service early childhood teachers have brought cognitive changes as 'processes not outcomes', 'integration not separation', 'living non-curriculum' and 'meaning not effect'. In developing bible-based language education activities for young children, Christian pre-service early childhood teachers experienced a cognitive change in the 'process of language education activities' rather than the developmental achievements and results of early childhood language education. Christian pre-service early childhood teachers recognized the necessity of 'integration of listening-speaking-reading-writing', not the separation of early childhood language education. They recognized the importance of 'informal language education in kindergarten life', as well as teacher-centered formal language education. In addition, they have made a cognitive change that 'child-centered meaningful language education experience' is more important than the effectiveness of early childhood language education. Second, in developing bible-based language education activities for young children, Christian pre-service early childhood teachers showed personality changes as 'confident teachers', 'professional teachers', and 'teachers with reflective thoughts and attitudes'. Finally, in developing bible-based language education activities for young children, Christian pre-service early childhood teachers recognized the power of positive language and practiced it to form habits of using the right language and to link Christian education with early childhood education. Through the development of bible-based language education activities for young children, Christian pre-service early childhood teachers are equipped with the heart attitude and enthusiasm required to become true early childhood teachers for young children in unpredictable educational conditions and rapidly changing educational realities. Teacher efficacy has improved. In the future, it is expected that various teacher education programs linking Christian education and early childhood education will be continuously and systematically implemented.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.