• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.31-36
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• 2021

As the global economy stagnated due to the Corona 19 virus from Wuhan, China, most countries, including the US Federal Reserve System, introduced policies to boost the economy by increasing the amount of money. Most of the stock investors tend to invest only by listening to the recommendations of famous YouTubers or acquaintances without analyzing the financial statements of the company, so there is a high possibility of the loss of stock investments. Therefore, in this research, I have used artificial intelligence deep learning techniques developed under the existing automatic trading conditions to analyze and predict macro-indicators that affect stock prices, giving weights on individual stock price predictions through correlations that affect stock prices. In addition, since stock prices react sensitively to real-time stock market news, a more accurate stock price prediction is made by reflecting the weight to the stock price predicted by artificial intelligence through stock market news text mining, providing stock investors with the basis for deciding to make a proper stock investment.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.47-56
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• 2020

The stock index is used not only as an economic indicator for a country, but also as an indicator for investment judgment, which is why research into predicting the stock index is ongoing. The task of predicting the stock price index involves technical, basic, and psychological factors, and it is also necessary to consider complex factors for prediction accuracy. Therefore, it is necessary to study the model for predicting the stock price index by selecting and reflecting technical and auxiliary factors that affect the fluctuation of the stock price according to the stock price. Most of the existing studies related to this are forecasting studies that use news information or macroeconomic indicators that create market fluctuations, or reflect only a few combinations of indicators. In this paper, this we propose to present an effective combination of the news information sentiment analysis and various macroeconomic indicators in order to predict the US Dow Jones Index. After Crawling more than 93,000 business news from the New York Times for two years, the sentiment results analyzed using the latest natural language processing techniques BERT and NLTK, along with five macroeconomic indicators, gold prices, oil prices, and five foreign exchange rates affecting the US economy Combination was applied to the prediction algorithm LSTM, which is known to be the most suitable for combining numeric and text information. As a result of experimenting with various combinations, the combination of DJI, NLTK, BERT, OIL, GOLD, and EURUSD in the DJI index prediction yielded the smallest MSE value.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.60-66
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• 2009

The acceleration noise is valuable index to monitor traffic stability. However, the previous study was performed for the acceleration noise of individual vehicle. The consideration of the acceleration noise for vehicle in the network has not been studied yet. This paper proposes a new macroscopic traffic flow monitoring method based on applying network acceleration noise.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.3-14
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• 2018

The system to appraise the execution capabilities of construction companies had been began as the Construction Contract Restriction System in 1958, was changed as the Construction Subcontract Restriction System in 1961, and finally has been operated as the Appraisal and Public Announcement of Execution Capacity (APAEC) from 1996. The APAEC system has been utilized as a firm and unique tool for assessing the execution capacities of construction companies despite many problems and continuous system changes. In spite of numerous studies to improve the APAEC system, however, efforts to analyze the system from the empirical point of view were insufficient. In this study, we analyze the status of APAEC system through analyzing correlations among assessment results of the APAEC, earned values of construction works, construction management performance indexes, and macroeconomic indexes for the past 10 years from 2007 to 2016. As a result of the analysis, it was found that Appraisal Value of Execution Capacity (AVEC) is excessively inflated in engineering and landscaping areas compared to Earned Value of Construction Work (EVCW) and the correlations between the AVECs and EVECs are not high in the areas of engineering, industrial equipment, and landscaping. In addition, technical appraisal values are excessively inflated in engineering and landscaping areas and correlations between AVEC and its components are high in the areas of engineering & building, industrial equipment, and large companies, but low in the areas of engineering, building, landscaping, and small and medium companies. Finally, the concentration of the AVEC is intensifying more and more and the concentration deteriorates construction management performance indexes and macroeconomic indexes. If we continuously improve the APAEC system based on the implications derived in this study, the APAEC system will be able to maintain it's position of a firm and unique means to access the execution capacities of construction companies.

• KDI Journal of Economic Policy
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• v.15 no.4
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• pp.3-35
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• 1993

본고(本稿)의 "연간거시모형(年間巨視模型)"은 경제구조(經濟構造)가 비교적 동질적(同質的)이라 할 수 있는 1970년대 이후의 연간자료(年間資料)를 이용하여 주요총량지표(主要總量指標)의 변동을 통합(統合) 단순화(單純化)된 구조식으로 파악함으로써, 거시경제정책(巨視經濟政策) 효과분석(效果分析)과 중(中) 단기(短期) 예측에 적합하도록 개발되었다. 동(同) 모형(模型)은 주요가격변수(主要價格變數)들의 내생화와 GNP갭변수의 도입을 통해 기존모형들의 가격의 내생성(內生性) 경시 및 공급측면(供給側面) 경시적 구조를 보완하고 있으며, 80년대 이후 최근에 이르기까지 우리 경제의 거시경제변동(巨視經濟變動)을 상당히 안정적(安定的)으로 추적하는 것으로 나타났다. "연간거시모형(年間巨視模型)"에 의한 통화(通貨) 금리정책(金利政策) 효과의 분석 결과, 여(與) 수신금리(受信金利)의 인상(引上)은 실질소득(實質所得) 및 물가(物價)의 하락(下落)과 국제수지(國際收支)의 개선(改善)을 가져오는 것으로 나타났으며, 계속충격(繼續衝擊)의 경우 여(與) 수신금리(受信金利) 1%포인트의 인상은 평균 0.277%의 실질소득(實質所得) 감소효과(減少效果)를 갖는 것으로 나타났다. 계속적인 통화량(通貨量) 1%의 증가는 물가(物價)를 누적적(累積的)으로 상승시켜서 4년후에는 상승효과(上昇效果)가 0.249%에 달하게 되는 것으로 나타났다. 동(同) 모형(模型)에서는 여신금리의 인상이 경제안정화(經濟安定化) 효과(效果)를 통해 오히려 실세금리(實勢金利)의 안정(安定)에 기여하는 것으로 나타났다. 재정정책(財政政策)의 정책실험 결과, 정부소비(政府消費)의 증가로 나타나는 재정규모(財政規模) 증대의 경우 재정적자(財政赤字)를 수반하는 경우와 수반하지 않는 경우의 차이가 단적으로 나타났다. 재정규모(財政規模)의 증대(增大)는 두가지 경우 모두에 있어서 물가상승(物價上昇)을 유발하지만 그 실제적(實際的) 크기는 재정적자(財政赤字)를 수반하는 경우 훨씬 크게 나타났다. 재정규모(財政規模)의 증가(增加)가 일시적일 경우, 두가지 경우 모두에 있어 물가에 대한 정(正)의 효과(效果)는 지속적인 반면 실질소득(實質所得)에 대한 효과(效果)는 일시적인 것으로 나타났다.

• The Journal of Bigdata
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• v.2 no.1
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• pp.59-69
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• 2017

According to precedent research of disaster economics, most of the studies are either based on belated macroeconomic indicators or are limited to specific industries. It is certain that preventing disaster is important, but immediate analysis and reconstruction policy are crucial as well. This research analyzed the ripple effect of consumer spending followed by April 16 ferry disaster and MERS outbreak; it was done by applying credit card company's real-time big data with Marketing Mix Modeling. The main focus of this research is to see if it is possible to predict the scale of damage during ongoing disasters. It is found that setting up weekly MMM and moving the timeline draws significance conclusion. When disasters or events occur in future, this research may be the basis of building quick and intuitive indicator to monitor possible effects.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.431-444
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• 2014

We introduce the empirical model decomposition (EMD) to decompose a time series into a set of components in the time-frequency domain. By using EMD, we also extract cycle and trend components from major Korean macroeconomic indices and forecast the indices with the components combined. In order to evaluate their efficiencies, we investigate volatility, autocorrelation, persistence, Granger causality, nonstationarity, and forecasting performance. They are then compared with those by Hodrick-Prescott filter which is the most commonly used method.

• Korean Journal of Social Welfare
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• v.58 no.3
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• pp.245-268
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• 2006

The purpose of this study is to investigate the empirical relation between economic growth and poverty in Korea. Especially, the focus is put on exploring if there are any changes in the relation of economic growth and poverty. From 1982-2004 Korea Urban Household Survey, I constructed the annual data of poverty rate. I also obtained the annual data of the real GDP and the unemployment rate from the National Statistical Office. Using these annal data of the poverty rate and the macroeconomic performance, I analyzed the relation of them. As the result, I found that the macroeconomic growth have played very important role in reducing the poverty rate in Korea. Since 2000, the macroeconomic growth have still worked as an effective instrument for poverty reduction. However, there have been poverty increase that has not been explained by the macroeconomic growth since 2000. Based on these results, this paper suggests that the anti-poverty strategy in Korea should be changed from the old strategy emphasizing only economic growth to the new strategy pursuing both economic growth and social security simultaneously.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.19-24
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• 2020

Artificial intelligence technology, which is the core of the 4th industrial revolution, is making intelligent judgments through deep learning techniques and machine learning that it is impossible to predict if it is applied to stock prediction beyond human capabilities. In US fund management companies, artificial intelligence is replacing the role of stock market analyst, and research in this field is actively underway. In this study, we use BLSTM to reduce errors that occur in unidirectional prediction of the existing LSTM method, reduce errors in predictions by predicting in both directions, and macroscopic indicators that affect stock prices, namely, economic growth rate, economic indicators, interest rate, analyze the trade balance, exchange rate, and volume of currency. To help stock investment by accurately predicting the target price of stocks by analyzing the PBR, BPS, and ROE of individual stocks after analyzing macro-indicators, and by analyzing the purchase and sale quantities of foreigners, institutions, pension funds, etc., which have the most influence on stock prices.

• KDI Journal of Economic Policy
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• v.19 no.1
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• pp.51-104
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• 1997

최근의 고금리논쟁과 자본시장개방에 대응한 정책방안을 둘러싼 많은 논의의 핵심은 우리나라의 제반 거시경제여건을 반영하는 장기적 의미에서의 균형금리수준이 어느 정도인가에 대한 것이다. 장기적인 관점에서 볼 때 한 나라의 금리수준은 그 나라의 거시경제여건을 반영하는 균형금리의 추세를 반영하기 마련이며, 이러한 균형금리수준을 왜곡하는 정책 및 규제는 경제의 불안정성을 야기할 뿐, 민간부문의 규제회피노력 등으로 결국은 무력화될 소지가 높기 때문이다. 본 연구의 목적은 우리나라 금리변동의 요인 및 특성에 대해 세밀히 살펴보고, 국내외 실질금리격차의 실증분석을 통하여 그 구조적 원인을 파악하여 보며, OECD 국제비교분석을 통하여 현재 우리나라의 균형금리수준을 가늠하여 봄으로써, 향후 본격적인 자본시장개방에 대응한 통화금융정책의 모색에 하나의 지표를 제시하여 보려는데 있다. 본고의 연구분석결과에 의하면 우리나라의 명목금리는 실질경제성장률 외에도 기대인플레이션 및 경상수지적자와 밀접한 관계가 있으며, 해외금리 및 예상환율절하율도 점차 주요한 금리의 설명변수로서 나타나고 있다. 엄밀한 의미에서의 피셔효과는 기각되나 기대인플레이션이 명목 및 실질금리의 가장 주요한 변동요인으로 나타나 물가안정을 통한 인플레이션 기대심리의 불식이 향후 금리안정의 관건으로 분석되었다. 특히 통화공급의 유동성효과는 단기적으로만 나타나며 장기적으로는 오히려 금리상승을 유발하는 것으로 나타나 금리안정을 위해서는 안정적인 통화관리가 중요한 것으로 분석되었다. OECD 국제비교분석을 통하여 추정해 본 결과 우리나라의 1997년 균형금리수준은 회사채수익률 기준 약 11%대로 나타나 소폭의 금리하락 가능성이 있으나 지속적인 경상수지의 불균형 등 금리하락여건은 여의치 않은 것으로 보인다. 이미 자본시장개방이 진전된 OECD 국가들의 실증분석에서도 나타나듯이 금리의 하향안정화는 거시경제의 안정과 금융의 효율성 제고가 동시에 이루어져야만 가능한 것이다. 그러므로 향후 금리정책은 금리의 가격기능을 조속히 회복시켜 자원배분의 효율성을 극대화할 수 있는 시장메커니즘을 활성화하는 방향으로 추진되어야 할 것이다.