• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.682-691
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• 2016

The purpose of this study is to explore the causal and precedence relationships between the housing sub-market and the results of a consumer sentiment survey about the housing market. This study investigates the relationships between the survey results and an apartment deal price index by size and bidding price rate in apartment auctions by extending research related to consumer sentiment surveys. We surveyed the Seoul Metropolitan Area and analyzed the results using a unit root test, cointegration test, Granger causality test, and cross-correlation test. It was confirmed that causality exists between the survey results and apartment deal price index by size and bidding price rate, and it was also confirmed that there are correlation and precedence relationships between them.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.113-118
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• 2023

This study analyzed the effects of macroeconomic variables, including housing affordability, and bank loan-related variables on variation in housing prices using multiple regression models. As a result of the analysis, consumer price growth rate, the total currency growth rate, and the housing affordability growth rate had a significant positive effect on changes in housing prices. As a result of analyzing the period of rising and falling housing prices, consumer price growth rate and the total currency growth rate during the period of rising housing prices had a significant positive effect on housing prices. Unlike the period of rising housing prices, the growth rate of household loans was found to have a significant positive effect on changes in housing prices. On the other hand, unlike the period of rising housing prices, the growth rater of mortgage loans was found to have a significant negative effect on changes in housing prices. The growth rate of housing affordability index did not have a significant positive effect on changes in housing prices during a falling housing prices. The determinants of housing prices showed different patterns during the period of rising housing prices and falling housing prices.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.377-386
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• 2014

This study analyzed how alternative investment goods would affect a market in a neighboring shopping area in order to provide parties involved in the investment market of this neighboring shopping area with standards which would help them when they try to make a reasonable determination. The study estimated forms and explanation power of the effects of a bid rate of a neighboring shopping area, and came up with those results as follows. Increases in the representative macro economic indicators, the composite stock price index and the fluctuation rate of land price, including the real estate business would have a positive influence on the market of the neighboring shopping area as playing a circumstantial evidence of market recovery and yet, the increase in interest rate, the alternative investment goods, would reduce the relative price-earnings ratio which would, eventually, negatively affect the charm of the investment in the market of the neighboring shopping area. The study, now, understands that housing with a feature of consumers' goods and neighboring shopping area with a feature of investment goods would not have great concern with each other as they are observed to be two different markets from an aspect of interactionism.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.43-49
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• 2020

The purpose of this study was to analyze factors affecting the housing market by setting household loans and M2, which are liquidity indicators, and the industrial production index reflecting economic fluctuations, as variables, and to determine the effect of expected housing prices. An empirical analysis was conducted based on the data from January 2005 to May 2020, and the HP filter was applied to the real house price as the expected house price variable. As a result of the analysis, it was found that real household loans, real M2, and so on, had an effect on house prices, and expectations for past house prices and house prices increased the house prices in the present period. These results show that even though the liquidity expansion is aimed at revitalizing the economy, it can affect housing prices as well.

• Convergence Security Journal
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• v.15 no.3_2
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• pp.83-93
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• 2015

In this research, we used KOSPI, KOSDAQ and a stock price of Information Security related Company - S1, Ahnlab, Suprema, Raonscure and Igloosecurity. From August 2010 to July 2014, that is during 208 weeks(4 years), we had grasped index and stock price trend. Also we had attempted various Empirical analysis - Basic statistics of Security related Stock, Analysis of variance, Correlation analysis and Weekly Rate of Rise trends. The first purpose of this research is to see correlation between Security related Company and KOSPI, KOSDAQ. The second purpose of this research is to analyze whether stock items have investment value or not while watching features of flow of stock price per item. We expect possibility and merit of investment when we suppose Security industry's high potential to grow. It seems that Security related Company deserves to be invested. We expect investment for Security related Company that has high possibility of growing will create high yields compared to Market yields.

• Journal of Korean Society of Forest Science
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• v.107 no.3
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• pp.305-315
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• 2018

This study conducted to estimate the influences of policy which prohibits illegal logging trade. Before analyzing of the economic effects for this policy, scenario methods were selected to inflect economic circumstance by implementing it. In order to do, the policy experiments were carried out using equilibrium displacement equation model. Results show that change ratio of log price was increased 0.066%~0.071%. Since the primary import country of log is New zealand which is high CPI score rather than Republic of Korea so that imported quantity of log was decreased thinly. Because imported log price is worked as a cost in the lumber market, if the imported log price was increased, supply of lumber has to be decreased. So that, not the change ratio of domestic lumber price was increased 0.885%~4.179% but supply of domestic lumber was increased 5.367% respectively along the goods features as a heterogeneity or homogeneity on the market.

• Environmental and Resource Economics Review
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• v.25 no.4
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• pp.545-564
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• 2016

Recently as fine and ultra fine particles become major environmental issues in Korea, it is very important to develop effective solutions to air pollution. Accordingly this study aims at detecting causes of air pollution by using models and examining if diesel price increases contribute to reduction of diesel consumption and air pollution. TSP, PM10, $NO_X$, $SO_X$, CO, and VOC are included as major air pollutants. As a result, we found invert U shape curve between pollution and income for all air pollutants except CO. Consumer price index, coal power capacity, diesel consumption, frequency of yellow dust, number of natural gas buses, number of transport business, annual average temperature, number of manufacturing businesses are also influential in explaining causes of air pollution. As diesel price increases by 1%, air pollutants decline between 0.07~0.12% in the short run. Simultaneously, the additional revenue from increases in diesel prices might be transferred to support expansion of biofuel market. Also, stronger policy should be developed to mitigate the current air pollution problem.

• International Area Studies Review
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• v.20 no.2
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• pp.47-62
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• 2016

This paper is to set up the empirical model in order to estimate industrial markup and to analyze the determinants for industrial markup by estimating the factor price elasticities of markup in the Korean manufacturing industries using the autoregressive distributed model. The import price elasticities of markup were estimated to be -1.025, -0.176, and -0.260 respectively in Machinery products, Chemical products, and Metallics which proved to have higher ratios of imported intermediate goods to industrial output. The interest elasticities of markup were also estimated to be -0.165, -0.147, and -0.210 respectively in Chemical products, Metallics, and Machinery products which are capital-intensive industries. Thus, the paper suggests that both import price index and interest rate have had more decisive effects on the changes in industrial markup in the Korean manufacturing industries, in particular, since the foreign currency crisis beginning in late 1997.

• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.535-555
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• 2021

This study empirically analyzes the effects of international oil prices on domestic stock market volatility. The data used for the analysis are 10-minute high-frequency data of the KOSPI index and WTI futures price from January 2, 2015, to July 30, 2021. For using the high-frequency data, a heterogeneous autoregression (HAR) model is employed. The analysis model utilizes the advantages of high frequency data to observe the impact of international oil prices through realized volatility, realized skewness, and kurtosis as well as oil price return. In the estimation, the Box-Cox transformation is applied in consideration of the distribution of realized volatility with high skewness. As a result, it finds that the daily return fluctuation of the WTI price has a statistically significant positive (+) effect on the volatility of the KOSPI return. However, the volatility, skewness, and kurtosis of the WTI return do not appear to affect the volatility of the KOSPI return. This result is believed to be because the volatility of the KOSPI return reflects the daily change in the WTI return, but does not reflect the intraday trading behavior of investors.

• 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.