• 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.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.05a
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• pp.107-113
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• 2000

최근 인터넷 사용 증가는 물론 그에 따른 인터넷 사이트의 증가가 가히 폭발적이라고 할 수 있다. 전자상거래도 인터넷 사용증가에 힘입어 더욱 증가 추세에 있으며 관광산업 또한 예외는 아니다. 호텔에서도 웹사이트를 구축하여 온라인 예약과 각종 서비스에 필요한 정보를 제공하고 있으며 점차 온라인 예약이 증가추세이다. 하지만 인터넷 웹사이트의 급격한 증가는 풍부하고 다양한 정보를 제공한다는 긍정적인 면과 함께 정보과다(information overload)로 인해 정보 검색 등에 많은 시간과 비용이 요구되는 문제를 낳았다. 위와 같은 환경에서 사용자를 대신하여 원하는 정보를 찾아주는 역할을 수행하는 에이전트(agent)의 개념이 도입되었다. 현재 전자상거래 분야에서 활용 중인 에이전트는 구매자가 직접 판매자와 접촉하여 자신에게 필요한 여러 가지정보를 얻고 필요에 따라서는 협상 등을 진행한 후 최종 거래를 성사시키는 ‘사람과 사람간의 일 대 일 거래 과정’중 일부분만을 지원하고 있는 실정이다. 이와 같은 현존 에이전트의 문제점을 보완하기 위해서 구매자와 판매자를 대표하는 에이전트를 개발하고 이들 에이전트간의 직접적인 정보교환, 가격협상 및 이를 바탕으로 한 의사결정까지의 거래 모델을 수립하는 것이 필요하다고 인식된다. 따라서 본 연구는 인터넷상에서 구매자와 판매자간의 거래를 대행하는 인터넷 다중 에이전트(Internet Multi-Agents)의 개발을 위한 개념적 거래 모델을 연구하고, 이를 호텔 예약 분야에 응용하기 위한 각 에이전트의 필요 조건 및 기능을 제시하고자 한다.

• Journal of Labour Economics
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• v.33 no.2
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• pp.27-52
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• 2010

This study, using Korean Time Use Survey 1999, analyzes how opportunity costs of maternal time affects the ways in which mothers allocate their time to market work/housework/child care/leisure. Opportunity costs include two kinds: hourly child care costs and log hourly wage rates. Results show that a unit increase in child care costs reduces market work but increases housework, child care, and leisure. The effects of log wage rates are opposite those of child care costs. The result that a unit increase in the log wage rates decreases child care lime is not consistent with a previous study for the United Stales. These results differed by mother's educational attainments. This study suggests that policy-makers should pay careful attention to the effects of various types of mother's opportunity costs on non-market time in promoting maternal employment.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.371-375
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• 2008

Nowadays, Korean Housing Market have been unstable because of the global economic fluctuation such as steady decline in the interest rate and the house price bubble. While Korean Government policy responses these state, rapidly changing policies led to deep confusion in the Korean Housing Market. In this situation, Analysis for housing market forecasting has been partial and fragmentary, therefore comprehensive solution and systematical approach is required to analyze the housing market including causal nexus between market determining factors. In an integrated point of view, applying the system dynamics modeling, the paper aims at proposing basic Korean housing market dynamics models based on Fundamental principles of housing market determined by supply and demand.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.23-31
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• 2000

Many studies in marketing and economics have attempted to model price and sales path under the dynamic diffusion process. Most of these models have been based on a fixed product lifetime. The current business climate requiring intensive development of new products however affects the diffusion of new products and their lifetime. Many products have not enjoyed the expected life cycle at the launching stage due to intense technical development competitive reactions, and financial problems. Most diffusion models however have not taken account of the lifetime uncertainty of new product. If the products do not last over the planning horizon set by those models. the optimal price derived from them could be futile. Therefore we had better take such lifetime uncertainty into consideration when developing diffusion models, In this paper we study the impact of uncertain product lifetime on its optimal pricing path in non-competitive market. We develop an optimal pricing model under uncertain product lifetimes and conduct a simulation study to investigate their effects on the optimal pricing and corresponding sales paths. The simulation study provides some interesting findings on optimal pricing policy under uncertain product lifetime. This study could be a stepping stone for the further extended study of optimal pricing strategy with uncertain product lifetime.

• The Korean Journal of Financial Management
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• v.15 no.2
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• pp.211-233
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• 1998

본 연구에서는 대기업의 부도가 은행주가수익률에 미친 영향을 분석하였다. 분석대상사건은 1997년의 한보철강 부도, 삼미그룹 법정관리신청, 기아자동차 부도유예협약적용을 택하였다. 분석결과는 다음과 같다. 첫째, 사건기간의 시장모형(OLS Market Model)에 의한 평균초과수익률과 누적평균초과수익률이 은행전체와 대출은행 그룹에 대하여 유의한 (-)의 반응을 보여 신정보가설이 지지되었다. 둘째, 대출은행그룹의 평균초과수익률과 누적평균초과수익률이 기타은행그룹에 대하여 유의한 (-)의 차이를 나타내었다. 그러나 기타은행의 경우에도 사건일을 전후하여 평균초과수익률이 유의한 (-)의 반응을 보여 일부 투자자감염효과가 나타났고, 대출은행의 누적초과수익률이 대출지분비율(=부도 대기업에의 대출금액/자기자본)과 유의한 (-)의 선형관계를 보이지 않아 주가반응 정도가 대출정도를 반영한다는 합리적가격결정가설은 기각되었다. 셋째, 대출은행의 누적초과수익률과 자기자본비율(=자기자본/총자산)이 사건기간 전체에 대하여 유의한 (+)의 선형관계로 나타나지 않아 재무건전성이 높은 은행이 거래기업의 부도와 같은 부정적 정보에 더 저항적일 것이라는 자본적합성가설은 기각되었다. 이상의 결과는 신정보가설을 제외하고는 미국 등의 선행연구와 다른 것이며 우리나라의 경우 대기업 부도에 따른 은행주가반응에 관한 한 준강형 효율적 시장가설을 지지하는 증거가 부족하다는 것을 시사한다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.109-118
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• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.75-106
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• 2007

In this study, it is analyzed whether oil price plays a major role in the pricing return on Koran stock market and examined why the covariance risk between oil and return on stock is different in each industry. Firstly, this study explores whether the expected rate of return on stock is pricing due to global oil price factors as a function of risk premium by using a two-factor APT. Also, it is examined whether spill-over effects of oil price volatility affect the beta risk to oil price. Considering the asymmetry of oil price volatility, we use the GJR model. As a result, it shows that oil price is an independent pricing factor and oil price volatility transmits to stock return in only electricity and electrical equipment. Secondly, the two step-analyzing process is introduced to find why the covariance between oil price factor and stock return is different in each industry. The first step is to study whether beta risk exists in each industry by using two proxy variables like size and liquidity as control variables. The second step is to grasp the systematic relationship between the difference of liquidity and size and beta to oil price factor by using the panel-data model which can be analyzed efficiently using the cross-sectional data formed with time series. Through the analysis, we can argue that oil price factor is an independent pricing factor in only electricity and electrical equipment having the greatest market capitalization, and know that beta risk to oil price factor is a proxy of size in the other industries. According to the result of panel-data model, it is argued that the beta to oil price factor augments when market capitalization increases and this fact supports the first assertion. In conclusion, the expected rate of return of electricity and electrical equipment works as a function of risk premium to market portfolio and oil price, and the reason to make beta risk power differentiated in each industry attributes to the size.

• Management & Information Systems Review
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• v.29 no.4
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• pp.1-22
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• 2010

There have been arguments in Korea that fair value accounting system improves quality of accounting information through the asset revaluation. These arguments are based on the fact that investors prefer fair value to cost value information. Others argue that cost principles may offer more proper information to the investors because financial statements applied the cost principles are more objective and thus more reliable. Prior researches focused mainly on the motives of asset revaluation but I examined the effects of the tangible asset revaluation on the stock prices. The empirical findings indicate that : (1) the gains on the tangible asset revaluation are positively correlated with the stock prices; (2) the net book values applied the cost principles explain stock prices better than the net book values applied fair values. My findings suggest that the gains on the tangible asset revaluation constitute a part of the firms' values but the accounting informations measured fair value are not always useful to the investors in the capital market.

• Journal of Korea Technology Innovation Society
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• v.9 no.4
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• pp.627-653
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• 2006

The purpose of this study lies in understanding how the spectrum assigned for each mobile operator affects the consumers of mobile service. For this purpose, we have observed the change of path coefficient in the structural equation, using control variables. However, the structure of the mobile service market in Korea has become fixed. Considering this tendency and the conclusion of this study, the 'lock-in effect' occurs seriously in the mobile service market in Korea. It can be explained by the fact that CS(Customer Satisfaction) of the cellular subscribers little affects customer loyalty but the market dominance of the cellular service in the actual market has continued for a long time. In this study, we figured out a strong prejudice about call quality, which is caused by spectrum difference among competitors. Cellular subscribers tends to believe that call quality of their cellular service is better than that of PCS. In addition, we found that PCS operators can catch customer's retention by investment into network in order to increase call quality.