• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2933-2940
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• 2018

It is known that fruit is more affected by the weather than other crops. Therefore, in order to create high value for farmers, it is necessary to develop a wholesale price model considering the weather. Peaches produced under relatively limited conditions were chosen as subjects of study. The data were collected from 2015 to 2017 provided by okdab 4.0. The meteorological data used for the analysis were generated by weighting the cultivation area and the variables with high correlation among the weather data were selected from the day before to 7 days before. Randomforest, gradient boosting machine, and XGboost were used for the analysis. As a result of analysis, XGboost showed the best performance in the sense of RMSE and correlation, and price prediction was comparatively well predicted, but the accuracy of the trading volume prediction was not so good enough. The top three weather variables affecting to the peach were minimum temperature, average maximum temperature, and precipitation.

• The Journal of Fisheries Business Administration
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• v.38 no.2
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• pp.63-78
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• 2007

The objective of this study is to examine the speculative efficiency of shrimp futures market. Testing for the speculative efficiency hypothesis is carried out using Johansen's the maximum-likelihood cointegration method and Fama(1984) regressison model. Analysis data are obtained Kansai Commodities Exchange in Osaka and are daily data of frozen shrimp futures and cash prices for all trading days in the time period from September 6, 2002, frozen shrimp futures is introduced, to May 10, 2007. The empirical results are summarized as follows:First, there exists the cointegrating relationship between realized spot India 16/20, Indonesia 16/20, vietnam 16/20 prices and futures prices of the 14 day to maturity. Second, shrimp futures contract prices do not behave as unbiased predictor s of future spot shrimp prices. This indicates that the shrimp futures market is inefficient.

• Korean Management Science Review
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• v.17 no.3
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• pp.147-160
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• 2000

These days, a modeling tool or environment has to know about the others on the market and build bridges to them with which their customers insist on sharing models and data. When it is based on a closed architecture, a tangle of import/export point translators is required. Using an exchange standard, we can design an open architecture for the interchange of models and data. XML(Extensible Markup Language) provides a framework for describing the syntax for creating and exchanging data structures. The explosive growth of XML-based business proposals and standards reflects the urgent requirements and its strength. This paper proposes an XML-based language for sharing decision models within the MSOR/DSS community. The language is able to allow applications and on-line analytic processing tools to models obtained from multiple sources without having to deal with individual differences between those sources. It is expected to be a medium for B2B integration by supporting flexible interchange of decision models.

• Korean Journal of Organic Agriculture
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• v.10 no.4
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• pp.69-78
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• 2002

This experiment was conducted to investigate the changes of sugar contents and chip color during 104days storage after harvesting of five potato varieties. The potato varieties were planted on 1st April in 1999 and harvested on 10. July in 1999. $No_2$ contents in potato petiole tended to decrease repidly at tuber maturing stage. $K^+$ contents in potato petiole tended to in crease at 70 days ofter planting on medium maturing varieties, and at 90 days after planting on late maturing variety. Snowden variety was no desirable cultivar for processing on spring cultivation due to long growth period. Contents of solid and sugar in potatoes affected on potato chip color. Higher contents of solid in potato varieties showed low sugar contents and no change on chip color during storage.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Korean Society of Forest Science
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• v.99 no.4
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• pp.479-486
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• 2010

We analyzed the relationships between the daily yield and quality of pine-mushroom to predict the annual production pattern and unit price of the mushroom with the records of pine-mushroom trade at Yeongdeok forestry cooperative's market for nine years (2000~2008). Although there were some exceptions due to extreme drought or extraordinary temperature, the production ratio of high quality (first and second grade) was more than 50% in early stage and decreased, while that of low quality (pileus opened and defected ones) showed increasing pattern after the production reached in peak. The ratio of high quality and that of low quality were reversed 1~9 days before the mushroom production reached the acme of daily yield, which allowed us to predict that the mushroom production would be decreased when the ratio of low quality overcomes that of high quality. The ratio of high quality preceded about 3~4 days prior to that of daily yield, and the mushroom yield showed significant correlations with the ratio of high quality mushroom prior to 3~4 days of the day with the coefficient larger than 0.5 (r=0.51 for 3 days and r=0.54 for 4 days). Thus, we concluded that the analysis of grade distribution of pine-mushroom at the market may provide a significant clue to predict production pattern of the mushroom. In addition, the price of high quality pine-mushroom showed clear negative correlations with the yield. Thus, the analysis may take a good role for the trading of pine-mushroom with providing information for predicting the price of pine-mushroom.

• Journal of the Korea Safety Management & Science
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• v.10 no.2
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• pp.163-168
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• 2008

These days, international air-logistics demand is getting bigger and bigger by increasing in trading volumes of export and import of Asia. It makes the air logistics of stakeholder to invest in air logistics facilities and information systems for meeting the growth of air transportation. However there are some problems that the efficiency of investment is not good by duplicately investing in information systems and moreover not compatible with each other because the stakeholder is investing in individual information system and air logistics facilities instead of constructing the integrated infrastructure. In this paper, we investigated the export, import, and transshipment process of air logistics to simplify air logistics process through the RFID(Radio Frequency Identification) application and the 4PL system.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.555-564
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• 2020

The purpose of this study is to analyze the efficiency of research institutes of futures companies, and to promote the development of futures market and real economy. This study employs DEA-solver software to conduct super-efficiency data envelopment analysis (SE-DEA), and also selects 40 representative futures research institutes in China as decision-making units (DMUs). For data of input and output indicators, we collect from the China Futures Association, Futures Daily, Hexun.com and Webstock.com respectively, and the time duration is the 103 trading days between from October 2019 to February 2020. Then the indicator for the strategy accuracy rate is calculated separately by analyzing the strategies published by each DMUs in public media. In conclusions, most institutes have excessive investment in human resources, and also have insufficient strategy accuracy rate and insufficient published research reports. The findings of this study suggest that Chinese futures companies need to improve the efficiency of research institutes, and better meet the demand of the financial market. In fact, the analysis of the efficiency of the futures company research institute has not been found in the literature worldwide, Application of DEA model in efficiency analysis of securities and futures research institutions and establishment of indicators are the innovations of this paper.

• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.221-263
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• 2009

This paper studies the behaviour of stock prices on the ex-dividend day in the Korean stock market. Since a majority of listed Korean firms are December firms whose fiscal year end in December and whose ex-dividend day falls on the same calendar day in the year, we use stock prices of Non-December firms to estimate the general stock price movements not related to cash dividends. We estimate excess returns on days around the ex-dividend day. Our major findings are (a) there is no tax clientele effect in Korea, (b) the opening price stock prices fell by the amount of the current cash dividend per share until 2001, but it does not fall as much as the current dividend per share since 2001. Furthermore, in contrast to the U.S. and the Japanese findings, (c) stocks earned negative excess returns on the ex-dividend day until 2001, after which all stocks are earning positive excess returns on the ex-dividend day, and (d) the closing stock price on the ex-dividend day that used to be even higher than the cum-dividend price until 2001 is lower than the opening stock price since 2001. The evidence suggests a structural break has happened around the year 2001.

• Management & Information Systems Review
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• v.26
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• pp.293-309
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• 2008

This study examined the market efficiency of korea stock market by comparing variance ratios(VR) of stock groups which is sorted by market capitalization. We compute variance ratios of KOSPI large capitalization, midium capitalization, and small capitalization for 546 trading days from 2006/01/02 to 2008/04/15. For our study, we also use high frequency data that is; intra-day 1 minute data. The characteristics of variance ratios of stock groups by market capitalization as follows: From 1 to 5 minute interval, variance ratios of three stock group increase far from zero(0). The longer time interval, the more variance ratios decrease, but only large capitalization converge on around zero. This means that the market of large capitalization is more efficient compare to other stock groups. The entire sample period can be divided two sub-period because the impact of sub prime crisis arised from U.S.A. influences Korea stock market. Before sub prime crisis, the VRs of mid cap and small cap do not converge on around zero except large cap although the time interval is longer. After sub prime crisis, the VRs of three stock groups decrease when time interval is longer, but only large cap converge on around zero. We conclude that large cap is more efficient than other stock groups in Korea Stock Market.