• Title/Summary/Keyword: Long-term Time Series

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Long-Term Variations of Water Quality in Jinhae Bay (진해만의 장기 수질변동 특성)

  • Kwon, Jung-No;Lee, Jangho;Kim, Youngsug;Lim, Jae-Hyun;Choi, Tae-Jun;Ye, Mi-Ju;Jun, Ji-Won;Kim, Seulmin
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.17 no.4
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    • pp.324-332
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    • 2014
  • In order to reveal the long-term variations of water quality in Jinhae Bay, water qualities had been monitored at 9 survey stations of Jinhae Bay during 2000~2012. The surface and bottom waters concentrations of chemical oxygen demand (COD), dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and chlorophyll-a (Chl.-a) were higher at the survey stations of Masan Bay than the stations of other Bays. Especially, station 1 which is located at the inner area of Masan Bay had the highest values in the concentrations of COD, DIN, and Chl.-a because there were terrestrial pollutant sources near the station 1 and sea current had not well circulated in the inner area of Masan Bay. In factor analysis, the station 1 also had the highest factor values related to factors which increase organic matters and nutrients in surface and bottom waters of Masan Bay. However, the stations (st.5, st.6, st.7, st.8, and st.9) of other Bays had lower values of the factors. In time series analysis, the COD concentrations of the bottom waters at 8 stations except for station 1 distinctly decreased. However, the COD concentrations of the surface waters showed no distinct decrease trends at all stations. In the concentrations of nutrients (DIN and DIP) of both surface and bottom waters, there were tremendous decrease trends at all stations. Therefore, these distinct decrease trends of the COD in bottom waters and the nutrients in surface and bottom waters of Jinhae Bay could have been associated with water improvement actions such as TPLMS (total pollution load management system).

A Study on Collection and Usage of Panel Data on On-board Job Taking and Separation of Korean Seafarers (한국선원의 승선과 이직에 대한 패널자료 구축과 활용방안)

  • Park, Yong-An
    • Journal of Korea Port Economic Association
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    • v.32 no.4
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    • pp.149-163
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    • 2016
  • Seafarers are an essential resource in maritime industries, which provide navigation skills, vessel maneuvering skills and fishing skills in the fishery industry. They also work as a driving force in pilotage, port operation, vessel traffic service, and marine safety. Other areas in maritime services, which rely on seafarer include safety management of ships, supervisory activities, and maritime accident assessment. In these ways, Korean seafarers have contributed to the growth of Korean economy. However, there have been issues of high separation rate, shortage of supply, multi-nationality, multiplicity of culture caused by employment of foreign seafarers, and aging. The present paper finds that maritime officers and fishery officers demonstrate differences in the statistics of on-board job taking and separation: the separation rate of fishery officers is higher than that of maritime officers. The existing data and statistics by the Korea Seafarer's Welfare & Employment Center could be improved by changing its structure from time series to panel data. The Korea Seafarer's Welfare & Employment Center is the ideal institution for collecting the panel data, as it has already accumulated and published relevant statistics regarding seafarer. The basic design method of the panel data is to adopt and improve it by including the information on ratings of maritime and fishery industries, ranks in a ship, personal information, family life, and career goal. Panel data are useful in short- and long-term forecasts of supply of Korean seafarers; demand evaluation of education, training, and reeducation of the seafarers; demographical dynamic analysis on Korean seafarers; inducement policy of long-term on board job taking in harmony with man-power demands in marine industries such as pilotage service; implementation of job attractiveness policy on Korean seafarers; and employment stabilization of Korean seafarers.

Comparison of Models for Stock Price Prediction Based on Keyword Search Volume According to the Social Acceptance of Artificial Intelligence (인공지능의 사회적 수용도에 따른 키워드 검색량 기반 주가예측모형 비교연구)

  • Cho, Yujung;Sohn, Kwonsang;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.103-128
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    • 2021
  • Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

LSTM Based Prediction of Ocean Mixed Layer Temperature Using Meteorological Data (기상 데이터를 활용한 LSTM 기반의 해양 혼합층 수온 예측)

  • Ko, Kwan-Seob;Kim, Young-Won;Byeon, Seong-Hyeon;Lee, Soo-Jin
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.603-614
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    • 2021
  • Recently, the surface temperature in the seas around Korea has been continuously rising. This temperature rise causes changes in fishery resources and affects leisure activities such as fishing. In particular, high temperatures lead to the occurrence of red tides, causing severe damage to ocean industries such as aquaculture. Meanwhile, changes in sea temperature are closely related to military operation to detect submarines. This is because the degree of diffraction, refraction, or reflection of sound waves used to detect submarines varies depending on the ocean mixed layer. Currently, research on the prediction of changes in sea water temperature is being actively conducted. However, existing research is focused on predicting only the surface temperature of the ocean, so it is difficult to identify fishery resources according to depth and apply them to military operations such as submarine detection. Therefore, in this study, we predicted the temperature of the ocean mixed layer at a depth of 38m by using temperature data for each water depth in the upper mixed layer and meteorological data such as temperature, atmospheric pressure, and sunlight that are related to the surface temperature. The data used are meteorological data and sea temperature data by water depth observed from 2016 to 2020 at the IEODO Ocean Research Station. In order to increase the accuracy and efficiency of prediction, LSTM (Long Short-Term Memory), which is known to be suitable for time series data among deep learning techniques, was used. As a result of the experiment, in the daily prediction, the RMSE (Root Mean Square Error) of the model using temperature, atmospheric pressure, and sunlight data together was 0.473. On the other hand, the RMSE of the model using only the surface temperature was 0.631. These results confirm that the model using meteorological data together shows better performance in predicting the temperature of the upper ocean mixed layer.

Seasonal Variations of Particle Fluxes in the Northeastern Pacific (북동태평양 심해에서 관측된 퇴적물 입자 플럭스의 계절적 변동)

  • Kim, Hyung-Jeek;Kim, Dong-Seon;Hyeong, Ki-Seong;Kim, Kyeong-Hong;Son, Ju-Won;Hwang, Sang-Chu;Chi, Sang-Bum;Kim, Ki-Hyun;Khim, Boo-Keun
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.13 no.3
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    • pp.200-209
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    • 2008
  • Particle fluxes were measured with a time-series sediment trap from July 2003 to June 2005 at the St. KOMO(KOMO; Korea Deep-Sea Environmental Study Long-Term Monitoring Station, $10^{\circ}30'N,\;131^{\circ}20'W$) in the northeastern Pacific. Total mass fluxes at a depth of 4,960 m showed distinct seasonal variations with high values in the winter(December-February) and spring(March-May) and low values in the summer(June-August) and fall(September-November). Biogenic origin fluxes also displayed distinct seasonal variations similar to total mass fluxes. Particularly, calcium carbonate fluxes in winter and spring were more than two times greater than those in summer and fall. The prominent seasonal variations of total mass and biogenic fluxes were closely related with the seasonal changes of primary production in the surface waters; in winter and spring, primary production increased due to the enhanced supply of nutrients below the surface mixed layer by strong wind and less stratification, whereas it decreased as a result of the less supply of nutrient by reduced wind speed and strong stratification in summer and fall. The seasonal variations of total mass and biogenic fluxes in this study were higher than the differences of total mass and biogenic fluxes caused by the environmental changes such as El $Ni\tilde{n}o$ and La $Ni\tilde{n}a$ events in the previous studies. In order to understand the effects of El $Ni\tilde{n}o$ and La $Ni\tilde{n}a$ on the particle flux, therefore, the seasonal variation of particle flux in the northeastern equatorial Pacific needs to be well defined.

Weekly Variation of Phytoplankton Communities in the Inner Bay of Yeong-do, Busan (부산 영도 내만에서 식물플랑크톤 군집의 주간 변동 특성)

  • YANG, WONSEOK;CHOI, DONG HAN;WON, JONGSEOK;KIM, JIHOON;HYUN, MYUNG JIN;LEE, HAEUN;LEE, YEONJUNG;NOH, JAE HOON
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.26 no.4
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    • pp.356-368
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    • 2021
  • To understand the temporal variation of phytoplankton communities in a coastal area, the biomass and diversity were weekly investigated in the inner bay of Yeong-do, Busan. In the study area, chlorophyll a concentration ranged from 0.43~7.58 mg m-3 during the study, indicating the study area was in mesotrophic or eutrophic status. The fractions of chlorophyll a occupied by large phytoplankton (> 3 ㎛ diameter) exhibited an average of 80% of total chlorophyll a in this study. Among the large phytoplankton, while Bacillariophyta was the most dominant in spring and summer, Cryptophyceae prevailed in the fall and winter. On the contrary, in the picophytoplankton community less than 3 ㎛ in diameter, Mamiellophyceae was the most dominant in most seasons, Cryptophyceae was relatively high with an average of 17.7 ± 17.6% throughout the year, but seasonal variations were large. Dinophyceae rarely occupied a higher fraction up to 60.4% of the picophytoplankton community. By weekly monitoring at a coastal station for 13 months, it is suggested that phytoplankton communities in coastal waters could be changed on a short time scale. If data are steadily accumulated at the time-series monitoring site for a long time, these will provide important data for understanding the long-term dynamics of phytoplankton as well as the impact of climate and environmental changes.

Time Series Analysis of Park Use Behavior Utilizing Big Data - Targeting Olympic Park - (빅데이터를 활용한 공원 이용행태의 시계열분석 - 올림픽공원을 대상으로 -)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.46 no.2
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    • pp.27-36
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    • 2018
  • This study suggests the necessity of behavior analysis as changes to a park environment to reflect user desires can be implemented only by grasping the needs of park users. Online data (blog) were defined as the basic data of the study. After collecting data by 5 - year units, data mining was used to derive the characteristics of the time series behavior while the significance of the online data was verified through social network analysis. The results of the text mining analysis are as follows. First, primary results included 'walking', 'photography', 'riding bicycles'(inline, kickboard, etc.), and 'eating'. Second, in the early days of the collected data, active physical activity such as exercise was the main factor, but recent passive behavior such as eating, using a mobile phone, games, food and drinking coffee also appeared as a new behavior characteristic in parks. Third, the factors affecting the behavior of park users are the changes of various conditions of society such as internet development and a culture of expressing unique personalities and styles. Fourth, the special behaviors appearing at Olympic Park were derived from educational activities such as cultural activities including watching performances and history lessons. In conclusion, it has been shown that people's lifestyle changes and the behavior of a park are influenced by the changes of the various times rather than the original purpose that was intended during park planning and design. Therefore, it is necessary to create an environment tailored to users by considering the main behaviors and influencing factors of Olympic Park. Text mining used as an analytical method has the merit that past data can be collected. Therefore, it is possible to form analysis from a long-term viewpoint of behavior analysis as well as to measure new behavior and value with derived keywords. In addition, the validity of online data was verified through social network analysis to increase the legitimacy of research results. Research on more comprehensive behavior analysis should be carried out by diversifying the types of data collected later, and various methods for verifying the accuracy and reliability of large-volume data will be needed.

Field Studios of In-situ Aerobic Cometabolism of Chlorinated Aliphatic Hydrocarbons

  • Semprini, Lewts
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2004.04a
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    • pp.3-4
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    • 2004
  • Results will be presented from two field studies that evaluated the in-situ treatment of chlorinated aliphatic hydrocarbons (CAHs) using aerobic cometabolism. In the first study, a cometabolic air sparging (CAS) demonstration was conducted at McClellan Air Force Base (AFB), California, to treat chlorinated aliphatic hydrocarbons (CAHs) in groundwater using propane as the cometabolic substrate. A propane-biostimulated zone was sparged with a propane/air mixture and a control zone was sparged with air alone. Propane-utilizers were effectively stimulated in the saturated zone with repeated intermediate sparging of propane and air. Propane delivery, however, was not uniform, with propane mainly observed in down-gradient observation wells. Trichloroethene (TCE), cis-1, 2-dichloroethene (c-DCE), and dissolved oxygen (DO) concentration levels decreased in proportion with propane usage, with c-DCE decreasing more rapidly than TCE. The more rapid removal of c-DCE indicated biotransformation and not just physical removal by stripping. Propane utilization rates and rates of CAH removal slowed after three to four months of repeated propane additions, which coincided with tile depletion of nitrogen (as nitrate). Ammonia was then added to the propane/air mixture as a nitrogen source. After a six-month period between propane additions, rapid propane-utilization was observed. Nitrate was present due to groundwater flow into the treatment zone and/or by the oxidation of tile previously injected ammonia. In the propane-stimulated zone, c-DCE concentrations decreased below tile detection limit (1 $\mu$g/L), and TCE concentrations ranged from less than 5 $\mu$g/L to 30 $\mu$g/L, representing removals of 90 to 97%. In the air sparged control zone, TCE was removed at only two monitoring locations nearest the sparge-well, to concentrations of 15 $\mu$g/L and 60 $\mu$g/L. The responses indicate that stripping as well as biological treatment were responsible for the removal of contaminants in the biostimulated zone, with biostimulation enhancing removals to lower contaminant levels. As part of that study bacterial population shifts that occurred in the groundwater during CAS and air sparging control were evaluated by length heterogeneity polymerase chain reaction (LH-PCR) fragment analysis. The results showed that an organism(5) that had a fragment size of 385 base pairs (385 bp) was positively correlated with propane removal rates. The 385 bp fragment consisted of up to 83% of the total fragments in the analysis when propane removal rates peaked. A 16S rRNA clone library made from the bacteria sampled in propane sparged groundwater included clones of a TM7 division bacterium that had a 385bp LH-PCR fragment; no other bacterial species with this fragment size were detected. Both propane removal rates and the 385bp LH-PCR fragment decreased as nitrate levels in the groundwater decreased. In the second study the potential for bioaugmentation of a butane culture was evaluated in a series of field tests conducted at the Moffett Field Air Station in California. A butane-utilizing mixed culture that was effective in transforming 1, 1-dichloroethene (1, 1-DCE), 1, 1, 1-trichloroethane (1, 1, 1-TCA), and 1, 1-dichloroethane (1, 1-DCA) was added to the saturated zone at the test site. This mixture of contaminants was evaluated since they are often present as together as the result of 1, 1, 1-TCA contamination and the abiotic and biotic transformation of 1, 1, 1-TCA to 1, 1-DCE and 1, 1-DCA. Model simulations were performed prior to the initiation of the field study. The simulations were performed with a transport code that included processes for in-situ cometabolism, including microbial growth and decay, substrate and oxygen utilization, and the cometabolism of dual contaminants (1, 1-DCE and 1, 1, 1-TCA). Based on the results of detailed kinetic studies with the culture, cometabolic transformation kinetics were incorporated that butane mixed-inhibition on 1, 1-DCE and 1, 1, 1-TCA transformation, and competitive inhibition of 1, 1-DCE and 1, 1, 1-TCA on butane utilization. A transformation capacity term was also included in the model formation that results in cell loss due to contaminant transformation. Parameters for the model simulations were determined independently in kinetic studies with the butane-utilizing culture and through batch microcosm tests with groundwater and aquifer solids from the field test zone with the butane-utilizing culture added. In microcosm tests, the model simulated well the repetitive utilization of butane and cometabolism of 1.1, 1-TCA and 1, 1-DCE, as well as the transformation of 1, 1-DCE as it was repeatedly transformed at increased aqueous concentrations. Model simulations were then performed under the transport conditions of the field test to explore the effects of the bioaugmentation dose and the response of the system to tile biostimulation with alternating pulses of dissolved butane and oxygen in the presence of 1, 1-DCE (50 $\mu$g/L) and 1, 1, 1-TCA (250 $\mu$g/L). A uniform aquifer bioaugmentation dose of 0.5 mg/L of cells resulted in complete utilization of the butane 2-meters downgradient of the injection well within 200-hrs of bioaugmentation and butane addition. 1, 1-DCE was much more rapidly transformed than 1, 1, 1-TCA, and efficient 1, 1, 1-TCA removal occurred only after 1, 1-DCE and butane were decreased in concentration. The simulations demonstrated the strong inhibition of both 1, 1-DCE and butane on 1, 1, 1-TCA transformation, and the more rapid 1, 1-DCE transformation kinetics. Results of tile field demonstration indicated that bioaugmentation was successfully implemented; however it was difficult to maintain effective treatment for long periods of time (50 days or more). The demonstration showed that the bioaugmented experimental leg effectively transformed 1, 1-DCE and 1, 1-DCA, and was somewhat effective in transforming 1, 1, 1-TCA. The indigenous experimental leg treated in the same way as the bioaugmented leg was much less effective in treating the contaminant mixture. The best operating performance was achieved in the bioaugmented leg with about over 90%, 80%, 60 % removal for 1, 1-DCE, 1, 1-DCA, and 1, 1, 1-TCA, respectively. Molecular methods were used to track and enumerate the bioaugmented culture in the test zone. Real Time PCR analysis was used to on enumerate the bioaugmented culture. The results show higher numbers of the bioaugmented microorganisms were present in the treatment zone groundwater when the contaminants were being effective transformed. A decrease in these numbers was associated with a reduction in treatment performance. The results of the field tests indicated that although bioaugmentation can be successfully implemented, competition for the growth substrate (butane) by the indigenous microorganisms likely lead to the decrease in long-term performance.

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Report about First Repeated Sectional Measurements of Water Property in the East Sea using Underwater Glider (수중글라이더를 활용한 동해 최초 연속 물성 단면 관측 보고)

  • GYUCHANG LIM;JONGJIN PARK
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.29 no.1
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    • pp.56-76
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    • 2024
  • We for the first time made a successful longest continuous sectional observation in the East Sea by an underwater glider during 95 days from September 18 to December 21 2020 in the Korea along the 106 Line (129.1 °E ~ 131.5 °E at 37.9 °N) of the regular shipboard measurements by the National Institute of Fishery Science (NIFS) and obtained twelve hydrographic sections with high spatiotemporal resolution. The glider was deployed at 129.1 °E in September 18 and conducted 88-days flight from September 19 to December 15 2020, yielding twelve hydrographic sections, and then recovered at 129.2 °E in December 21 after the last 6 days virtual mooring operation. During the total traveled distance of 2550 km, the estimated deviation from the predetermined zonal path had an average RMS distance of 262 m. Based on these high-resolution long-term glider measurements, we conducted a comparative study with the bi-monthly NIFS measurements in terms of spatial and temporal resolutions, and found distinguished features. One is that spatial features of sub-mesoscale such as sub-mesoscale frontal structure and intensified thermocline were detected only in the glider measurements, mainly due to glider's high spatial resolution. The other is the detection of intramonthly variations from the weekly time series of temperature and salinity, which were extracted from glider's continuous sections. Lastly, there were deviations and bias in measurements from both platforms. We argued these deviations in terms of the time scale of variation, the spatial scale of fixed-point observation, and the calibration status of CTD devices of both platforms.

Price Volatility, Seasonality and Day-of-the Week Effect for Aquacultural Fishes in Korean Fishery Markets (수산물 시장에서의 양식 어류 가격변동성.계절성.요일효과에 관한 연구 - 노량진수산시장의 넙치와 조피볼락을 중심으로 -)

  • Ko, Bong-Hyun
    • The Journal of Fisheries Business Administration
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    • v.40 no.2
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    • pp.49-70
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    • 2009
  • This study proviedes GARCH model(Bollerslev, 1986) to analyze the structural characteristics of price volatility in domestic aquacultural fish market of Korea. As a case study, flatfish and rock-fish are analyzed as major species with relatively high portion in an aspect of production volume among fish captured in Korea. For analyzing, this study uses daily market data (dating from Jan 1 2000 to June 30, 2008) published by the Noryangjin Fisheries Wholesale Market which is located in Seoul of Korea. This study performs normality test on trading volume and price volatility of flatfish and rock-fish as an advanced empirical approach. The normality test adopted is Jarque-Bera test statistic. As a result, first, a null hypothesis that "an empirical distribution follows normal distribution" was rejected in both fishes. The distribution of daily market data of them were not only biased toward positive(+) direction in terms of kurtosis and skewness, but also characterized by leptokurtic distribution with long right tail. Secondly, serial correlations were found in data on market trading volume and price volatility of two species during very long period. Thirdly, the results of unit root test and ARCH-LM test showed that all data of time series were very stationary and demonstrated effects of ARCH. These statistical characteristics can be explained as a reasonable ground for supporting the fitness of GARCH model in order to estimate conditional variances that reveal price volatility in empirical analysis. From empirical data analysis above, this study drew the following conclusions. First of all, from an empirical analysis on potential effects of seasonality and the day of week on price volatility of aquacultural fish, Monday effects were found in both species and Thursday and Friday effects were also found in flatfish. This indicates that Monday is effective in expanding price volatility of aquacultural fish market and also Monday has higher effects upon the price volatility of fish than other days of week have since it has more new information for weekend. Secondly, the empirical analysis led to a common conclusion that there was very high price volatility of flatfish and rock-fish. This points out that the persistency parameter($\lambda$), an index of possibility for current volatility to sustain similarly in the future, was higher than 0.8-equivalently nearly to 1-in both flatfish and rock-fish, which presents volatility clustering. Also, this study estimated and compared and model that hypothesized normal distributions in order to determine fitness of respective models. As a result, the fitness of GARCH(1, 1)-t model was better than model where the distribution of error term was hypothesized through-distribution due to characteristics of fat-tailed distribution, was also better than model, as described in the results of basic statistic analysis. In conclusion, this study has an important mean in that it was introduced firstly in Korea to investigate in price volatility of Korean aquacultural fishery products, although there was partially a limited of official statistic data. Therefore, it is expected that the results of this study will be useful as a reference material for making and assessing governmental policies. Also, it is looked forward that the results will be helpful to build a fishery business plan as and aspect of producer, and also to take timely measures to potential price fluctuations of fishery products in market. Hence, it is advisable that further studies related to such price volatility in fishery market will extend and evolve into a wider variety of articles and issues in near future.

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