• Land and Housing Review
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• v.14 no.4
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• pp.39-46
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• 2023

This study explores the interrelationship between 'KRX Construction' and 'Business Survey Index'. KRX Construction is a leading economic indicator of construction industry, implying the potential interdependence with BSI Construction. Previous papers have investigated the relationship between the released stock price index and BSI. Using Granger causality tests, this study investigates how the BSI Construction is associated with the trend and noise-trading components of KRX Construction, respectively. The decomposition of KRX Construction of trend and noise-trading is based on the state-space model. The results document unilateral Granger causalities from released KRX Construction, trend component, noise-trading component to BSI Construction. In sum, this study demonstrates that construction company CEOs view stock price index as a leading economic indicator.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.78-82
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• 2004

Volatility may be defined as the sum of fundamental volatility caused by information arrival and transitory volatility caused by noise trading. This study decomposes the observed KOSPI volatility into fundamental volatility and transitory volatility using Kalman filtering method. This study investigates the effects of the introduction of cyber trading on the KOSPI volatility. Most studies investigates the effect on the observed volatility. In contrast to other studies, this study investigates the effect on the fundamental volatilty and transitory volatility individually. Analysis showed that observed volatility is increased significantly at 1％ level, but transitory volatility is not increased. This means that noise trading by irrational investors is not increased.

• Korean Business Review
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• v.20 no.2
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• pp.15-27
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• 2007

This paper analyzed the relationship between Housing Purchase Price volatility of Seoul and Housing Purchase Price volatility of local large city. Other studies investigates the effect on the observed volatility Observed volatility consists of fundamental volatility and transitory volatility. Fundamental volatility is caused by information arrival and transitory volatility is caused by noise trading. Fundamental volatility is trend component and is modelled as a random walk with drift. Transitory volatility is cyclical component and is modelled as a stationary process. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Observed volatility is estimated by GJR GARCH(1,1) model. We find that GJH GARCH model is superior to GARCH model and good news is more remarkable effect on volatility than bad news. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. The findings in this paper is as follows. The correlation between Seoul housing price volatility and Busan housing price volatility is high. But, the correlation between Seoul and Daejeon is low. And the correlation between Daejeon and Busan is low. As a distinguishing feature, the correlation between fundamental volatilities is high in the case of all pairs. But, the correlation between transitory volatilities turns out low. The reason is as follows. When economic information arrives, Seoul, Daejeon, and Busan housing markets, all together, are affected by this information.

• The Journal of Information Technology
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• v.3 no.1
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• pp.45-59
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• 2000

This study evaluates empirically differences of performance in the two types of the decision-making. There exist implied noises in the information but consensus mitigates or clears noises from available information in the decision-making process. Decision-making peformance depends on information quality. Therefore the higher quality information are used, the more peformance decision-makers have. The results of this study shows that group decision-making is better than individual in decision making performance. It indicates that consensus mitigates or clears noises in the information. As variant individuals, however, have different performance, individual decision-makers also have different ability in analyzing information.

• Proceedings of the CALSEC Conference
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• 1998.10b
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• pp.477-486
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• 1998

여러 산업 분야에서 인터넷의 채택으로 인터넷을 기반으로 하는 전자상거래 시스템 구축이 일반화되고 있으며, 전자상거래에 연관된 표준들이 제기되고 있다. 전자상거래가 인터넷의 네트워크를 고려한다면, 전자상거래 시스템은 클라이언트/서버나 분산 아키텍쳐를 요구한다. 즉, 객체지향 패러다임이 새롭고 효율적인 개발 방법으로써 널리 받아들여져 왔다. OMG의 CORBA가 객체지향 분산 아키텍쳐를 위한 실제적인 표준으로 잡음으로써, 진보된 인터넷 상거래시스템들 구축하는데 있어 CORBA를 이용하기 위한 기술을 요구한다. 본 논문에서는 CORBA 기반의 전자상거래 시스템의 아키텍쳐를 제시하며, CORBA가 인터넷 상거래 시스템의 성능과 다른 특성들을 어떻게 향상시킬 수 있는지를 제안한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.163-171
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• 2021

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.15-27
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• 2012

We have studied the realized variance(RV) of intra-day returns and market microstructure noise based on high-frequency stock transaction data for the four largest companies in terms of market capitalization in the KOSPI. First, non-negligible biases are observed for the RV and for the bias-corrected realized variance($RV_{AC_1}$) which is constructed by adjusting RV for the first order autocorrelation in intra-day returns. Bias is more obvious for the RV and the $RV_{AC_1}$ when intra-day returns are sampled more frequently than every 2 minutes. Transaction Time Sampling(TTS) is shown to be better than Calendar Time Sampling(CTS) in terms of biases of the RV and the $RV_{AC_1}$ for the 4 companies. The analysis reveals that market microstructure noise is temporally dependent. Second, by using the Noise-to-Signal Ratio(NSR), we estimate sampling frequencies that are optimal in terms of the Mean Square Errors(MSE) of the RV and the $RV_{AC_1}$. The optimal sampling frequencies are around 200 for RV and is around 5000 for the $RV_{AC_1}$ for all the four stock prices. For the 6 hour transaction period of the Korean stock trading, these correspond to about 2 minutes and 6 seconds.

• Korean Business Review
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• v.19 no.1
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• pp.81-92
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• 2006

This study investigates the relation between institutional investor's net purchase and the volatility of KOSPI. Some portion of volatility in stock prices comes from noise trading of irrational traders. Observed volatility may be defined as the sum of the portion caused by information arrival, fundamental volatility, and the portion caused by noise trading, transitory volatility. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. Most studies investigates the effect on the observed volatility. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Estimation results show that institutional investor's net purchase was not significantly related to all kinds of volatility(observed volatility, fundamental volatility and transitory volatility). This means that institutional investor's net purchase did not increase noise trading.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.89-91
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• 2003

최근 들어 전력 계통은 점차 복잡해지고 계통 규모 역시 빠른 속도록 성장하고 있다. 이러한 환경 하에서 전력계통 운영을 담당하고 있는 한국전력거래소가 계통의 현 상태를 정확하게 파악하고 가능한 상정 고장에 대비하여 전력계통을 안정적으로 운영하는 것은 매우 중요하다고 할 수 있다. 이를 위해 기존의 스카다를 사용하여 계통의 상황을 파악하는 방법은 통신상의 잡음 및 측정값의 부정확성으로 인해 계통을 전체적으로 정확하게 파악하고 실시간 상정고장 분석과 같은 검토를 하는데 한계가 있다. 따라서 차세대 에너지 관리 시스템(NEMS)을 구축하는 단계에서 한국전력거래소는 상태추정 및 관련 응용프로그램을 실계통에 도입하여 전력 계통의 안정 운영에 기여하려 하고 있다. 상태추정이란 에러를 포함하고 있는 측정값과 네트워크 모델을 사용하여 현 계통의 전압, 위상각, 조류 둥의 실제 상태를 추정하는 방법으로 상태추정을 사용하여 현 상태 감시 및 실시간 상정고장 분석, 안전도 개선과 같은 기능을 수행할 수 있다. 본 논문에서는 차세대 EMS에 적용된 상태추정을 설명하고 실계통에 적용하여 파악한 상태추정의 기능을 보여주고 있다.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.99-102
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• 2002

본 논문에서는 한국어 대어휘 연속음성 인식 시스템의 성능향상을 위하여 Multi-Pass 탐색 방법을 도입하고, 그 유효성을 확인하고자 한다. 연속음성 인식실험을 위하여, 최근 실험용으로 널리 사용되고 있는 HTK와 Multi-Pass 탐색 방법을 이용한 음성인식 시스템의 비교 실험을 수행한다. 대어휘 연속음성 인식 시스템에 사용한 언어 모델은 ARPA 표준 형식의 단어 N-gram 언어모델로, 1-pass에서는 2-gram 언어모델을, 2-pass 에서는 역방향 3-gram 언어모델을 이용하여 Multi-Pass 탐색 방법으로 인식을 수행한다. 본 논문에서는 Multi-Pass 탐색 방법을 한국어 연속음성인식에 적합하게 구성한 후, 다양한 한국어 음성 데이터 베이스를 이용하여 인식실험을 수행하였다. 그 결과, 전화망을 통하여 수집된 잡음이 포함된 증권거래용 연속음성 데이터 베이스를 이용한 연속음성 인식실험에서 HTK가 $59.50\%$, Multi-Pass 탐색 방법을 이용한 시스템은 $73.31\%$의 인식성능을 나타내어 HTK를 이용한 연속음성 인식률 보다 약 $13\%$의 인식률 향상을 나타내었다.