• Economic and Environmental Geology
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• v.42 no.2
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• pp.143-152
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• 2009

Recent raw material prices fluctuation has been unexpectedly high and that made Korean economic activities to be depressed. Because most raw material supply in Korea depends upon oversea imports, unexpected raw material price fluctuation affects Korean industrial economies through macroeconomic variables. So Korean government enforces some political measures such as demand management and the supply-security assurance as long-range policies, and reservation and general early warning system as short-range policies. In short-range policies, it is necessary to be expected short term fluctuation. Up to recently, there have been many researches and most of those researches use parametric methods or time series analyses. Because those methods and analyses often generate inadequate relations among variables, it is possible that some consistent variables are left out or the results are misunderstood. This study, therefore, is aim to mitigate those methodological problems and find the relatively appropriate model for economic explanation. So that, in this paper, by using non-parametric signal approach method mitigating some shortages of previous researches and forecasting properly short-range prices fluctuation of non-ferrous materials are presented empirically.

• International Area Studies Review
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• v.14 no.1
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• pp.77-97
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• 2010

Recently, countries on the Caspian Sea were had heavily interested due to instability of international resource market. These countries having been developed basing on energy exports, especially Kazakhstan have drastically grown during a decades. However economy, heavily relied on the exports of energy, is influenced on fluctuation in the international energy price as well as sometimes exposed at Dutch disease. These days, Kazakhstan, increased trade and investment with Korea, has been on the rise as new supplier for energy. Therefore, economic change in Kazakhstan can be an important issue. In this paper, we analyze relations among oil price, interest rate, and real exchange rate during sample period from January 1999 to December 2008 expanding Balasa-Samuelson model. Empirical results present that oil price, interest rate, and real exchange rate mutually keep their balance. Eventually, we find out Kazakhstan has exposed at Dutch disease since oil price and interest rate have negative impacts on real exchange rate respectively.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.448-459
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• 2021

In this paper, we propose a method of predicting the next-day stock price fluctuations of 10 KOSDAQ-listed companies in 5G, autonomous driving, and electricity sectors by training SVM, XGBoost, and LightGBM models from macroeconomic·financial market indicators, technical indicators, social interest indicators, and daily positive indices extracted from online news. In the three experiments to find out the usefulness of social interest indicators and daily positive indices, the average accuracy improved when each indicator and index was added to the models. In addition, when feature selection was performed to analyze the superiority of the extracted features, the average importance ranking of the social interest indicator and daily positive index was 5.45 and 1.08, respectively, it showed higher importance than the macroeconomic financial market indicators and technical indicators. With the results of these experiments, we confirmed the effectiveness of the social interest indicators as alternative data and the daily positive index for predicting stock price fluctuation.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.19 no.2
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• pp.12-22
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• 1991

The purpose of this study is to identify demand and methods of projection, including to prove the variables affecting the fluctuation of visitors and to analyze the relationship between these variables in National Park. Statistical analysis method (Multiple Linear Regression Analysis, ANOVA, and Model diagnostics) was carried out by computer program SAS/pc. 13 variables (1. Total Population, 2. Per Capita PDI, 3. Employment Ratio of S.O.C. & others, 4. NO. of Passenger Car, 5. Length of Roads, 6. Leisure Expenditure of Farm Household, 7. Leisure Expenditure of Urban Household, 8. Price Index, 9. NO. of Bus, 10. Exchange on Dollars, 11. Export, 12. Import, and 13. Visitors in National Park) had been used to this study. The scope of time period is during the last 17 years (1970-1986). The results were as follows; 1) Participation depends only on the specific characteristics of the economic factors (Price Index and Leisure Expenditure of Urban Household). These factors are the importance factors directly affecting the participation of visitors. The statistical Model for projecting the visitors in National Parks is the function of "Visitors in National Parks (thousand)=14915+0.210311*Leisure Expenditure of Urband Household (won)-157.835619*Price Index(1985=100)" 2) The external factors affecting the participation depends upon the interelated features of availability and accessibility (NO. of Passenger Car, Length of Roads, and NO. of Bus) of recreation resources or sites, and the economic factors (Per Capita PDI, Export, and Import). These factors are the factors indirectly affecting the participation of visitors. 3) The participation depends on the specific characteristics of demographic factors (Total Population and Employment Ratio of S.O.C. & others). These factors are the factors indirectly affecting the participation of visitors. 4) The unexpected fluctuation of yearly visitors depends on oil shock or inflation (1971, 1973-1974, 1979-1980), promulgation of national emergency decrees (1971-1972, 1974-1975, 1979-1980), and national events (assassination of president Park's wife, Madame Yuk in 1974 and president Park I 1979).

• Journal of Navigation and Port Research
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• v.35 no.9
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• pp.765-776
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• 2011

For container shipping company, fuel oil prise is a considerable expense. Since 2008, fuel oil prises have risen dramatically. An increasing fuel oil price in container shipping, in the short term, is only partially compensated through surcharges and may affect earnings negatively. This study discusses the impact of an increasing fuel oil price and capital costs for vessels on the Asia-Europe trade of 'H' Shipping Company. According to the result of 'H' carrier's operation in 2008, there were no cost differences between 8 and 9 vessels operations in case of fuel oil price with USD 169/tons while adopting USD 31,818 as a fixed cost. We can expect that the fuel oil price will not go lower than USD 200/Ton on the basis of current high oil price phenomenon. When the fuel oil price is over USD 200/ton, 9 vessel operation is more economic than 8 vessel operation even if the fixed cost is over USD 35,000.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.13-22
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• 2020

This research explores the appropriate rubber pricing model and the consistent empirical evidence. This model has been derived from the utility function and firm profit-maximization model of commodity goods. The finding shows that the period t - 1 affects expected commodity price and expected profit of commodity production. In fact, a change in the world price of rubber in the past period led to a change in the expected price of rubber in the short run which influenced the expected rubber profit. As a result, the past-period free on board price has an entirety effect on expected farm price of rubber given an exchange rate. In addition, the rubber pricing model indicates that the profit of local farmer on rubber plant depends solely on the world price of rubber in the short run in case of Thailand. In an empirical study, it was found that a change in the price of ribbed smoke sheet 3 in Singapore Commodity Exchange significantly and positively determined the fluctuation of rubber price at the farm gate in Thailand which was consistent with the behavior of the Thai farmers. Both prices are also cointegrated in the long run. That is, the result states that the VECM is an appropriated pricing model for forecasting the farm price in Thailand.

• Korean Journal of Construction Engineering and Management
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• v.13 no.1
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• pp.67-76
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• 2012

There are index adjustment method and item adjustment method in estimation methods for price fluctuation rate of public constructions. A relevant regulation has put item adjustment method as a principle, but in most construction, contract sum adjustment has been made by index adjustment method. Hence, this study, by figuring out width and causes of the gap between index adjustment method and item adjustment method through direct comparative analysis, solved inequality caused by difference between them and suggested a rational way against irrationality of each method. For building operations of public housing construction, a detailed fluctuation rate by index adjustment method and item adjustment method of construction cost elements of the same construction, that is, direct material cost, direct labor cost and historical construction cost was estimated to analyze difference between two adjustments and establish its cause. Across the analysis, it was found that fluctuation rate by item adjustment method was estimated lower than that by index adjustment method and difference between methods for estimating fluctuation rate of quotation unit price and application of index unrelated to construction type and construction nature are main causes of the difference. This study has a significance in that, for smooth contract sum adjustment between contracting parties, it practically proved the real difference between adjustment methods by conducting comparative analysis of the difference in direct correspondence way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3923-3942
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• 2022

Environment, price, regulation, and other factors influence the price of agricultural products, which is a social signal of product supply and demand. The price of many agricultural products fluctuates greatly due to the asymmetry between production and marketing details. Horticultural goods are particularly price sensitive because they cannot be stored for long periods of time. It is very important and helpful to forecast the price of horticultural products which is crucial in designing a cropping plan. The proposed method guides the farmers in agricultural product production and harvesting plans. Farmers can benefit from long-term forecasting since it helps them plan their planting and harvesting schedules. Customers can also profit from daily average price estimates for the short term. This paper study the time series models such as ARIMA, SARIMA, and neural network models such as BPN, LSTM and are used for wheat cost prediction in India. A large scale available data set is collected and tested. The results shows that since ARIMA and SARIMA models are well suited for small-scale, continuous, and periodic data, the BPN and LSTM provide more accurate and faster results for predicting well weekly and monthly trends of price fluctuation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.149-151
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• 2012

Changes in the price of materials in construction projects is one of the important variables. Therefore, measures are necessary to respond to the demand and supply of materials and price instability. In previous studies, mainly of ready-mix concrete and steel beam analysis was carried out. However, a study of non-ferrous material prices are still insufficient. So, in this study, the researcher identified the causal relationship between the construction cost and non-ferrous materials prices. Construction Cost Index was selected as a proxy variable of construction cost.