• Annual Conference of KIPS
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• 2023.05a
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• pp.76-77
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• 2023

가상 화폐가 금융권에 등장한 이후 가상화폐를 얻기 위한 채굴이라는 작업이 각광받기 시작하였다. 하지만 시간이 흐르면서 채굴기를 가동하는데 소모되는 전력보다 채굴에 따른 보상의 양이 적어지면서 수익 구조가 무너지기 시작하였다. 본 논문에서는 태양열 에너지 발전을 통해 가상화폐를 채굴하는 방법을 제안한다. 태양열 발전을 위한 시스템을 설계하고 수익성을 증명하였다. 그 결과 태양열 발전 설비로 생산한 전력을 판매하여 얻는 수익보다 채굴기를 가동하여 얻는 수익이 약 17% 더 많은 것을 알 수 있었다. 채굴 시장의 규모는 블록체인 시장 규모에 비례하여 증가하고 있기 때문에 채굴 시장의 전망도 증가할 것으로 예상된다.

• Vending industry
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• v.3 no.1 s.9
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• pp.64-69
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• 2004

고수익을 미끼로 한 자판기 분양사기가 최근 급증하고 있어 큰 문제가 되고 있다. 무조건 자판기 수익성만을 과대포장하여 투자자들의 `묻지마` 투자를 유도한 후 돈만 챙기고 사업에서 손을 떼어버리는 사기행각은 그 피해대상이 대부분 서민이라는 점에서 문제의 심각성을 더한다. 자판기가 불법 자금 모집을 통해 사기의 대상으로 외부 인식이 악화되어 버린다면 자판기 산업의 입지 역시 크게 좁혀 질 수 밖에 없다. 자판기 품목에 있어서는 불법자금모집의 대표적인 사례가 되는 경우는 확정수익을 보장한다며 투자자를 모집하는 경우이다. 그 후 일정기간동안 수익을 보장하며 투자자를 안심시킨 다음 일순간 돌변하여 자금을 챙겨 잠적을 하는 수순을 밝는다. 선의의 투자자들은 이럴 경우 엄청난 피해를 입게 되는 게 보통이다. 대개의 경우 기계 1~2대의 소량물량이 아닌 5대~l0대 단위의 투자를 유도하기 때문이다. 이제는 자판기 산업에 있어 이러한 악성 불법자금 모집업체들이 근절되어야 한다. 이 불법 사기행각의 대상이 더 이상 자판기 분야에 발을 붙이지 못하도록 하는 제도적 비책이 시급히 강구 되어야 한다. 이러한 가운데 금융감독원 비은행감독국 비제도금융조사팀에서는 올들어 지난 9월말까지 고수익을 미끼로 투자자금을 모집하다가 금감원에 적발된 유사 금융업체 85개사 명단을 사법당국에 통보했다. 불법자금모집 업체들이 투자자들을 유혹하기위해 미끼로 내세운 사업을 종류별로 보면 자판기, 게임기, 컴퓨터단말기 등 특정상품 운영권 제공이 29개사로 가장 많고, 사이버 쇼핑몰 및 인터넷사업(18개사), 납골당 등 부동산 투자(12개사), 영화등 문화 및 레저사업(10개사), 영화문화 및 레저산업(10개사), 벤처투자사(9개사) 등이었다. 자판기 분야에 있어서는 주로 성인용품자판기, 복권자판기 등의 품목이 불법자금 모집의 집중 타킷이 되었다. 금감원은 최근들어 유사 금융업체의 자금모집이 전문가도 속을 정도로 지능화하고 있다며 개인투자자들이 피해를 예방할 수 있는 불법업체 식별법을 금감원 인터넷 사이트(www.fss.or.kr)에 게시했다. 금감원은 특히 사업현황에 대해 지나치게 보안을 유지하는 업체, 1백$\%$이상의 터무니없는 고수익을 보장한다고 광고하는 업체, 제도권 금융회사의 지급보증을 강조하는 업체에 대해서는 투자에 앞서 금감원이나 업종 관련 정부당국에 사실여부를 확인해 보고 투자여부를 결정하라고 통보했다. 아울러 금감원은 금융소비자들이나 자판기 업계에서 불법자금 모집업체를 발견하여 전화(02-3786-8155~9)나 인터넷소비자 보호센터와 경찰에 신고해줄 것을 요청했다. 이제는 산업계도 더 이상 자판기 분야의 불법자금업체를 방치하지 말고 적극적인 금감원 신고를 통해 시장을 정화할 수 있게 해야 한다. 미꾸라지 한두마리가 온 개천 물 다 흐려놓는 이치처럼 자판기불법자금업체들로 인해 전체 산업에 미치는 영향이 실로 심각함을 인식해야 할 때이다. 금호 산업정보에서는 산업계에서 불법자금업체 근절에 많은 관심을 가질 수 있게 하기 위해 금융감독원 비은행감독국 비제도금융조사팀에서 배포한 $\ulcorner$불법자금 모집업체 고수익 보장 유혹에 주의$\lrcorner$ 에 대한 보도자료의 세부내용을 게재한다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.327-335
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• 2016

The People's Republic of China has vigorously been pursuing the internationalization of the Chinese Yuan or Renminbi after the financial crisis of 2008. In this view, an abrupt increase of use of the Chinese Yuan in the onshore and offshore markets are important milestones to be one of important currencies. One of the most frequently used methods to forecast volatility is GARCH model. Since a prediction error of the GARCH model has been reported quite high, a lot of efforts have been made to improve forecasting capability of the GARCH model. In this paper, we have proposed MLP-GARCH and a DL-GARCH by employing Artificial Neural Network to the GARCH. In an application to forecasting Chinese Yuan volatility, we have successfully shown their overall outperformance in forecasting over the GARCH.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.234-237
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• 2003

The Korean housing supply have been provided by the Pre-construction sales system. The Pre-construction sales system contributed to large housing supply. But it followed by the market anomaly. Along the housing market is changing to tile market for consumers, it requires new policy and regulations. This market changes and needs to modify the policy make a discussion about introducing the Post-construction sales system. it concerns to change the time to sale. This paper analyzes the present feasibility study and makes a tool to predict construction cashflow considering changed sales point. The sales timing leads to decide the amount of financial costs in the construction project and that cost affects to the feasibility. The accurate cashflow prediction is required for a successful apartment construction delivery.

• Korean Journal of Construction Engineering and Management
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• v.11 no.5
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• pp.32-40
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• 2010

Recent periodical boom and burst of house price have made mortgage lending issues become the main public interest in Korean real estate market. However, because mortgage-lending issues had not been discussed until then, housing market forecasting associated with mortgage lending has been difficult while using an empirical approach. Thus, comprehensive and systematic approach is required as well as validity of mortgage lending policies should be evaluated. In this regard, this research conducts a sensitivity analysis to validate the proposed policies and estimates the effects of current policies on LTV and DTI ratios with a comparison of another policies scenario. A causal loop and sensitivity analysis using system dynamics confirmed that LTV and DTI regulation is strong clout to housing market. However, to prevent transfer of potential mortgage borrowers to nonmonetary institutions, regulations in loans of nonmonetary institutions should be practiced in accompaniment with regulations of primary lending agencies.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.213-231
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• 2003

This paper uses the Efficient Method of Moments(EMM) of Gallant and Tauchen to estimate continuous-time stochastic volatility diffusion model for the Korean Composite Stock Price Index, sampled daily over $1995\sim2002$. The estimates display non-normality of stock index return, leptokurtic distribution, and stochastic volatility. Funker, this study suggests that two factor stochastic volatility model will be more desirable than one factor stochastic volatility model to estimate daily Korean stock return and also suggests that the stochastic volatility diffusions should allow for Poisson jumps of time-varying intensity.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.2
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• pp.275-292
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• 2013

This paper aims at analyzing the use REITs for improving housing welfare, especially focusing on affordable housing. To do this, firstly, current state and main problems of domestic housing welfare are analyzed, secondly, housing welfare system involving capital market and case study of affordable housing REITs in United State are examined. and thirdly, utilization schemes of REITs for improving affordable housing are analyzed. In the process of executing housing welfare, various systemic bases for attracting capital market are constructed. Under these systemic basis, affordable housing REITs such as Community Development Trust are operated. This scheme also can be applied in Korea. In the context, the structures of using management on commition REITs and the structure of using real estate fund are proposed.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.411-420
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• 2015

With the rapid increase in the price of house lease, a unique housing form in Korea, a serious social issue has been raised as to the use value of house lease and residence stability of the ordinary people. This study thus aimed to analyze the direct factors that affect lease guaranteed loan and market volatility in order to explore the right direction of financial policy to reduce housing burdens. To this end, the direct variables affecting house lease guaranteed loan, including lease price, transaction price and lending rate, were defined. Vector Error Correction Model (VECM), a time series analysis, was employed to dynamically explain the data. Based on the house lease prices and bank data on loans between January 2010 and December 2014, it was found that the increase in lease price was the direct result of the increase in lease guaranteed loan, not that of the decrease in lending rate or increase in housing transaction price.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.181-190
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• 2019

The purpose of this study is to help the understanding of the housing market through the influence of consumer choice attributes and financial policy on home buyer behavior. The key issue in the analysis is to take into account moderate effect of housing investment demand between different types of housing attribute choice and financial policy. The results of the study are as follows. First, convenience, education location, and neighborhood level have a significant effect on the purchase intention of the housing. Second, government policy have no significant influence on the purchase intention of the house. Third, the moderating effects of real estate investment outlook are that the neighbors level and interaction variables have a statistically significant effect on the purchase intention of the house. Since the government's financial policies do not affect the decision to buy a house, in reality, excessive regulation may reduce the quality of housing welfare for the first time home buyers. As a result of this study, the financial policy of the government does not affect the decision of the purchase of the house. In reality, the excessive regulation may reduce the quality of the housing welfare for the first time home buyer. Only an analysis which combines these aspects of consumer's choice can adequately describe and explain the actual change in demand in the residential market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.123-130
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• 2021

With the recent developments in computer technology, there has been an increasing interest in the field of machine learning. This also has led to a significant increase in real business cases of machine learning theory in various sectors. In finance, it has been a major challenge to predict the future value of financial products. Since the 1980s, the finance industry has relied on technical and fundamental analysis for this prediction. For future value prediction models using machine learning, model design is of paramount importance to respond to market variables. Therefore, this paper quantitatively predicts the stock price movements of individual stocks listed on the KOSPI market using machine learning techniques; specifically, the reinforcement learning model. The DQN and A2C algorithms proposed by Google Deep Mind in 2013 are used for the reinforcement learning and they are applied to the stock trading strategies. In addition, through experiments, an input value to increase the cumulative profit is selected and its superiority is verified by comparison with comparative algorithms.