• Title/Summary/Keyword: PRICE model

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The Volume and Price Relationship of the Oyster Market in Producing Area (굴 산지시장의 위판량과 가격관계)

  • 강석규
    • The Journal of Fisheries Business Administration
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    • v.32 no.1
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    • pp.1-14
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    • 2001
  • The research on the price-volume relation in the market is very important because it examines into regular phenomenon revealed by market participants including producers and middlemen. The purpose of this study is to investigate the relationship between price and trading volume in the oyster producing market. In order to accomplish the purpose of this study, the contents of empirical analysis include the time series properties of price and trading volume, the short-term and long-term relationships between price and trading volume, and the determinants of trading volume. The data used in this study correspond to daily price and trading volume covering the time period from January 1998 to April 2001. The empirical results can be summarized as follows : First, price and trading volume follow random walks and they are integrated of order 1. The first difference is necessary for satisfying the stationary conditions. Second, price and trading volume are cointegrated. This long-run relationship is stronger from trading volume to price. Third, error correction model suggests that feedback effect exists in the long-run and that price tends to lead trading volume by about five days in the short run, that is, to be required period by digging, conveying, and peeling oystershell for selling oyster. Fourth, price and price volatility is a determinant of trading volume. In particular, trading volume is a negative function of price. It is believed that the conclusion drawn from this study would provide a useful standard for the policy makers in charge of reducing the oyster price volatility risk caused by trading volume(selling quantities).

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HOUSING PRICE MODEL USING GIS IN SEOUL (APPLICATIONS OF STRUCTURAL EQUATION MODELING)

  • Kyong-Hoon Kim;Jae-Jun Kim;Bong-Sik Kim
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.366-375
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    • 2007
  • Our nation has a problem with discrimination of income distribution and inefficient of resources distribution caused by real estate price rising from a sudden economy growth and industrialization. Specially, in recent years, there is a great disparity of condominium price between the north and south of the Han river. Because the housing price is deciede by the immanent value of a house and neighborhood effects of the regional where the house is situated, the housing price is occurred difference. In this study, I analyzed the differences of housing price determinants about condominium developments in the old and new residential areas, and found the important factors that affect the condominium price using Structural Equation Modeling(SEM) The purpose of study is to analyze the influence of various factors of housing price. Also, this study tried to predict real estate market and to establish previous effective real estate policy.

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Price Stabilization Effect of the Fisheries Outlook Project (수산업관측사업의 가격안정화 효과 분석)

  • Sang-Ho Lee;Won-Ho Chung
    • The Journal of Fisheries Business Administration
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    • v.53 no.4
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    • pp.15-26
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    • 2022
  • This paper analyzed the price stabilization before and after the fisheries outlook project for seaweed, flatfish, and abalone. First, the stabilization effect was analyzed through the price variation coefficient before and after the observation project. In terms of the variation coefficient, there was no effect that the price was stabilized through the seaweed outlook project. However, it can be seen that flatfish and abalone have a price-stabilizing effect. Second, as a result of analyzing the price stabilization effect through the improved ARMA-T-GARCH model, it was confirmed that seaweed was not statistically significant while flatfish and abalone had a price stabilization effect by statistically significantly reducing volatility of real prices after the introduction of the fisheries outlook project. Third, as a result of analyzing the factors affecting price stability, it was found that the price of seaweed was stabilized after the WTO, but the Japanese earthquake expanded the price volatility. In the case of flatfish, it was analyzed that the price stabilized after the WTO and the Great Japanese Earthquake. Finally, the price of abalone has stabilized since the WTO and the Great Japanese Earthquake.

A Study on Asymmetry Effect and Price Volatility Spillover between Wholesale and Retail Markets of Fresh squid (신선 물오징어의 도·소매시장 간 가격 변동성의 전이 및 비대칭성 분석에 관한 연구)

  • Kim, Cheolhyun;Nam, Jongoh
    • The Journal of Fisheries Business Administration
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    • v.49 no.2
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    • pp.21-35
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    • 2018
  • Squid is a popular seafood in Korea. However, since the 2000s, the squid production has been declining. The unstable supply of the squid products may cause price fluctuations of fresh and chilled squid. These price fluctuations may be relatively more severe than them of other commodities, because the fresh and chilled squid can not be stored for a long period of time. Thus, this study analyzes the structural characteristics of price volatility and price asymmetry of fresh squid based on off-diagonal GARCH model. Data used to analysis of this study are daily wholesale and retail prices of fresh squid from January 1, 2006 to December 31, 2016 provided in the KAMIS. As theoretical approaches of this study, first of all, the stability of the time series is confirmed by the unit root test. Secondly, the causality between distribution channels is checked by the Granger causality test. Thirdly, the VAR model and the off-diagonal GARCH model are adopted to estimate asymmetry effect and price volatility spillover between distribution channels. Finally, the stability of the model is confirmed by multivariate Q-statistic and ARCH-LM test. In conclusion, fresh squid is found to have shock and volatility spillover between wholesale and retail prices as well as its own price. Also, volatility asymmetry effect is shown in own wholesale or retail price of fresh squid. Finally, this study shows that the decrease in the fresh squid retail price of t-1 period than the increase in the t-1 period has a greater impact on the volatility of the fresh squid wholesale price in t period.

A Dynamic Causality Analysis of Oliver Flounder Producer Price by Region using the Panel VAR Model (패널 VAR 모형을 이용한 지역별 양식넙치 산지가격의 동태적 인과관계 분석)

  • Jeon, Yong-Han;Nam, Jong-Oh
    • The Journal of Fisheries Business Administration
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    • v.52 no.1
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    • pp.47-63
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    • 2021
  • The purpose of this study is to identify the leading price between Jeju and Wando's oliver flounder producer price and to analyze the dynamic effect of the regional producer price using the panel VAR model. In the process of analysis, it was confirmed that there are unit roots in the monthly data of Jeju and Wando's oliver flounder producer price. So, in order to avoid spurious regression, the rate change of producer price which carries out log difference was used in the analysis. As a result of the analysis, first, the panel Granger causality test showed that the influence of the change rate of producer price in oliver flounder in Jeju was slightly larger than that in Wando, but it was found that each region all leads the change rate of the producer price in oliver flounder. Second, the panel VAR estimation showed that the rate change of producer price in Jeju and Wando a month ago had a statistically significant effect on the change rate of producer price of each region. Third, the impulse response analysis indicated that other regions are affected a little more than the same region in case of the occurrence of the impact on the error terms of the change rate of produce price in Jeju and Wando oliver flounder. Fourth, the variance decomposition analysis showed that the change rate of producer price in the two regions was higher explained by Jeju compared to Wando. In conclusion, it is expected that the above results can not only be useful as basic data for the stabilization of oliver flounder producer price and the establishment of policies for easing volatility but can also help the oliver flounder industry operate its business.

Neural Network Forecasting Using Data Mining Classifiers Based on Structural Change: Application to Stock Price Index

  • Oh, Kyong-Joo;Han, Ingoo
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.543-556
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    • 2001
  • This study suggests integrated neural network modes for he stock price index forecasting using change-point detection. The basic concept of this proposed model is to obtain significant intervals occurred by change points, identify them as change-point groups, and reflect them in stock price index forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in stock price index dataset. The second phase is to forecast change-point group with various data mining classifiers. The final phase is to forecast the stock price index with backpropagation neural networks. The proposed model is applied to the stock price index forecasting. This study then examines the predictability of integrated neural network models and compares the performance of data mining classifiers.

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Real Options Analysis of Groundwater Extraction and Management with Water Price Uncertainty

  • Lee, Jaehyung
    • Environmental and Resource Economics Review
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    • v.27 no.4
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    • pp.639-666
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    • 2018
  • This paper analyses the investment options of groundwater development project under water price uncertainty. The optimal investment threshold price which trigger the investment are calibrated base on monopolistic real options model. Stochastic dynamic model is set to reflect the uncertainty of water price which follows the GBM (Geometric Brownian Motion) process. Our finding from non-cooperative investment decision model is that uncertainty of water price could deter the groundwater investment by considering the existence of option values. For policy markers, it is easy to manage 'charges for utilization of groundwater' rather than 'performance guarantee ratio' when managing groundwater investment with pricing policy. And it is necessary to make comprehensive and well-designed policies considering the characteristics of regional groundwater reservoir and groundwater developers.

A Study on the Selection of Pricing Factors for Used Bulk Carriers (중고 벌크선의 가격결정요인 선정에 관한 연구)

  • Yang, Yun-Ok
    • Journal of Navigation and Port Research
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    • v.41 no.4
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    • pp.181-188
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    • 2017
  • In the existing ship sales market, prices determined based on the prices of similar ship types that recently traded. ince the 2008 financial crisis, ship prices have fluctuated, and ship price criteria have become ever more necessary to the imminent value of the ship. Therefore, this research used the hedonic price model to estimate imminent values of ships. In this study, the influence on ship prices was analyzed by the value of each characteristic and an estimated functional formula was. Out of the four models suggested by the hedonic price model, an optimal model was selected with variance inflation factors and a stepwise selection. For this, the influence of determinants of ship prices was analyzed based on actually traded ships and characteristic data. The selected model s the Log-Line model; as a result of regression analysis, eight variables, including DWT, Age, Market Value, Short-Term Charter, Long-Term Charter, Enbloc, Special Survey Due and Builder were to affect the ship price model. This model is expected to be useful for objective and balanced ship price evaluation.

Prediction Model of Real Estate Transaction Price with the LSTM Model based on AI and Bigdata

  • Lee, Jeong-hyun;Kim, Hoo-bin;Shim, Gyo-eon
    • International Journal of Advanced Culture Technology
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    • v.10 no.1
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    • pp.274-283
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    • 2022
  • Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

The Effects of the Price Difference Ratios between Preferred and Common Stocks on Preferred Stocks: Evidence from Dynamic Panel Models (우선주-보통주 괴리율이 우선주 수익률 및 종가에 미치는 영향: 동태적 패널 분석)

  • Sujung Choi
    • Asia-Pacific Journal of Business
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    • v.15 no.2
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    • pp.207-222
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    • 2024
  • Purpose - This study investigates whether the lagged price difference ratio between preferred and common stocks is related to the return and closing price of the preferred stock using three panel models. Design/methodology/approach - As a first step, we use a two-way fixed effect panel model with stationary preferred stock returns as a dependent variable. For robustness, we then apply the autoregressive distributed lag model (ARDL) and error correction model (ECM) with nonstationary closing prices of the preferred stocks as a dependent variable and compare the results of each model. The ARDL and ECM models provide an advantage of estimating a long-run equilibrium equation together if a long-run relationship exists between the two time-series variables compared to the fixed effect model. Findings - Our sample consists of 107 preferred stocks with at least four years of daily observations as of the end of December 2023. The coefficients of the error correction terms in the ARDL and ECM models are highly statistically significant, approximately -0.08. This indicates that the disequilibrium between the closing prices of common and preferred stocks adjusts by about 8% per day toward equilibrium. In all three models, the price difference ratio on day t-1 was statistically significant in explaining the preferred stock returns or closing prices on day t, implying that trading based on the previous day's price difference ratio is effective for one day. Research implications or Originality - Furthermore, the returns on preferred stocks are higher for firms with a lower proportion of foreign investors or a lower foreign market capitalization of preferred stocks. This suggests that foreign investors with informational advantages do not actively engage in profit-taking by trading preferred stocks, thus not narrowing the price difference. In summary, the recent surge in preferred stock prices is likely driven mainly by the irrational behavior of retail investors.