• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.271-280
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• 2017

Real-estate values and related economics are often the first read newspaper category. We are concerned about the opinions of experts on the forecast for real estate prices. The Box-Jenkins ARIMA model is a commonly used statistical method to predict housing prices. In this article, we tried to predict housing prices by combining independent component analysis (ICA) in multivariate data analysis and the Box-Jenkins ARIMA model. The two independent components for both the selling price index and the long-term rental price index were extracted and used to predict the future values of both indices. In conclusion, it has been shown that the actual indices and the forecast indices using ICA are more comparable to the forecasts of the ARIMA model alone.

• Korean Journal of Construction Engineering and Management
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• v.6 no.6 s.28
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• pp.98-106
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• 2005

The construction cost index and the forecasting model of apartment house can be efficient for evaluating the validness of the fluctuating price, and for making guidelines for construction firms when calculating their profit. In this study the previous construction cost index of apartment house was improved, and the forecasting model based on X-12 ARIMA was developed. According to the result, during the last five years the construction cost, excluding labor expense, has risen approximately to 22.7%. And during next three years, additional 16.8% rise of construction cost is expected. Those quantitative results can be utilized for evaluating the apartment house's selling price in an indirection, and be helpful to understand the variation pattern of the price.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.629-639
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• 2020

The current study explains how corruption, terrorism, political stability and oil price has an effect on on the Iraq stock exchange utilizing corruption perception index as a proxy of corruption, global terrorism index as proxy for terrorism, political stability and oil price with ISX60 index as proxy of stock market for the period (2005-2019) using Ordinary Least Square method. The results show that the level of corruption, terrorism activities and political stability coefficient is significantly positive with Iraq stock exchange. In contrast, the oil price coefficient is significantly negative with Iraq stock exchange, which means that lower levels of corruption, less terrorism activities and more stability in political system have strong influence on stock market development in Iraq. The study concludes that the explanatory variables are important for Iraq stock exchange. Hence, the study suggests the policy makers to develop stock market by implementing policies and strategies to overcome high level of corruption, terrorism activities especially after ISIS/ISIL announcement has been made public. There is a need for transparency and creating stable political environment through good governance practices in order to attract more foreign investment and promote economic development. Factors like terrorism and corruption make economic and political systems unstable and has an adverse effect on on Iraq's stock exchange performance.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.1
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• pp.1-14
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• 2003

In this study, to take the object of this thesis on understanding the characteristics on marketing structure and marketing distribution of landscape materials after consideration in the side of prices trends which is important factors for analysis in understanding the market of landscape materials. To do this, Analysis is divided into the prices trends. The investigation of prices trends and marketing distribution are to collect data refer to purchases and sales reports, these results are used to analyzed the operative factor of forming market structure. The periodic range of this thesis is limited from 1996 to 2000 and analytic articles is limited on 609 landscape materials(planting materials : 567 articles, facility materials : 7 articles, the other : 35 articles). The results of the whole prices trends and marketing distribution survey can be summarized as follows : 1. Prices trends of showing 3 types of landscape materials : In cases of planting, facility and the others materials, the annual average increasing rate of the index number of price was 3.1%, 3.4%, 3.1% while the KPRC(Korea Price Research Center) price was 3.98% for the past five years. 2. GSP(Government Specified Prices) Prices trends of showing 3 types of landscape materials : In cases of planting, facility and the others materials, the annual average increasing rate of the index number of price was 3.7%, 1.2%, 2.6% while the KPRC(Korea Price Research Center) price was 3.98% for the past five years. This increase indicates a small price margin, particularly, the GSP price of planting materials should be adjusted to a realistic level. 3. Native and exotic product Prices trends of showing 3. types of landscape materials : In cases of Native planting, facility and the others materials, the annual average increasing rate of the index number of price was 3.2%, 3.2%, 3.6% while cases of exotic was 3.1%, 1.0%, 5.8% for the past five years. The index number increase of prices of exotic landscape materials were fluctuated more than those the native landscape materials.

• Journal of the Korean housing association
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• v.18 no.3
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• pp.63-72
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• 2007

The purpose of this study is to identify the impact of the building, site, and region characteristic factors on the annual average price rising rate of apartment housing in Seoul. The data were consisted of 272 apartment units in Seoul. A survey included checking the drawing documents and interview with apartment maintenance staffs and real estate agencies from October 2006 to February 2007. Data were analyzed with descriptives, frequency, crosstabs, and linear regression by SPSS/PC for Window. The linear regression model was employed to evaluate the price rising rate in apartment housing. Following results were obtained. The price rising rate for pyeong ($3.3m^2$) of apartment housing was determinated by the district zone, the construction company's brand name, the building age, the building stories, the floor space index, the building-to-land ratio, the green space rate, and the distance from the downtown. Especially, the district zone was the most important factor that affected the price rising of apartment housing in Seoul. Therefore, the policy has to focus to solve the imbalance between autonomous districts with the collaborated tax.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.87-93
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• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2038-2045
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• 2010

Households' monthly average income is composed of various factors. This study paper studies focuses on estimating the determinants of a households' monthly average income. The region for analysis consist of three groups, that is, the whole country, a metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 57 time points(2005. 01~2009. 09). In this paper the dependent variable setting up the households' monthly average income, explanatory (independent) variables are composed of the consumer price index, employment to population ratio, Index of housing sale price, the preceding composite index, loans of housing mortgage, spending rate for care medical expense and the composite stock price index. In looking at the factors which determine the monthly average income, evidence was produced supporting the hypothesis that there is a significant positive relationship between the composite index and housing loans. The study also produced evidence supporting the view that there is a significant negative relationship between employment ratios, the house sale pricing index and spending rates for care or medical needs. The study found that the consumer price index and composite stock price index were not significant variables. The implications of these findings are discussed for further research.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.05a
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• pp.226-227
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• 2019

The basic type construction cost which is the base of the building cost estimation is being adjusted according to the price changes by utilizing the apartment construction cost index in order to flexibly operate it. In this study, we analyzed the change trends and characteristics of the housing cost index for the basic type building cost model project operated from September, 2012 to March, 2018. As a result, the increase in material costs is slight while the share of the labor cost increased in the construction cost due to the rise of labor unit price, leading to a perceived increase in sensitivity of labor costs. We should be careful to keep the sensitivity of the material cost and the labor cost to an appropriate level so that the index may not be distorted.

• Architectural research
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• v.8 no.1
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• pp.69-76
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• 2006

The purpose of this study is to suggest policies to improve the price escalation system in a construction contract through a Policy Delphi technique. The Delphi, including two times questionnaires and a group discussion, was conducted by joining 14 experts. Also, the escalation provisions of various countries were examined. Results of the Delphi showed that the minimum fluctuation rate for price escalation was desirable at a level of 3%. To compute the fluctuation rate, calculating the price fluctuation of overall articles was more desirable than using price indices. A bidding date was more reasonable as the initial date of change in price. Losses caused by price change should be shared between contractor and owner; therefore a deduction rate should be introduced in price escalation. Meanwhile, overhead and profit should be adjusted in proportion to the fluctuation rate; but advance payment or the delayed construction amount should be deducted from the adjusted amount.