• Korean Business Review
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• v.21 no.2
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• pp.1-16
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• 2008

This paper investigate the volume-volatility and volume-return relationship in the Korean Treasury Bond futures market using daily price and volume data categorized by three trader type i.e. individual investor, institutional investor and foreign investor over the period of October 1999 through December 2005. Major results are summarized as follows: (i) The effect of volume on return was not different across the trader type. (ii) The effect of volume on volatility was not unidirectional across the type of investor. While unexpected sell of individual investor has positive effects on volatility, negative effects in the case of institutional investor. (iii) We cannot find the evidence of asymmetric response of volatility to shock in trading volume or net position. This result differs from that of Korean Stock Price Index 200 futures market which showed strong positive asymmetry. Finally, some limitations of this paper and direction for further research were suggested.

• Information Systems Review
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• v.23 no.1
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• pp.23-43
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• 2021

Recently, many studies have been conducted to increase the accuracy of stock price prediction by analyzing candlestick charts using artificial intelligence techniques. However, these studies failed to consider the time-series characteristics of candlestick charts and to take into account the emotional state of market participants in data learning for stock price prediction. In order to overcome these limitations, this study produced input data by combining volatility index and candlestick charts to consider the emotional state of market participants, and used the data as input for a new method proposed on the basis of combining variantion autoencoder (VAE) and attention mechanisms for considering the time-series characteristics of candlestick chart. Fifty firms were randomly selected from the S&P 500 index and their stock prices were predicted to evaluate the performance of the method compared with existing ones such as convolutional neural network (CNN) or long-short term memory (LSTM). The results indicated the method proposed in this study showed superior performance compared to the existing ones. This study implied that the accuracy of stock price prediction could be improved by considering the emotional state of market participants and the time-series characteristics of the candlestick chart.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.235-261
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• 2003

We examine the relationship between the trading activities of Korea Stock Price Index (KOSPI) 200 futures contract and its underlying stock market volatility for about six years from May 1996 when the futures contract was introduced. The trading activities of the futures contracts are proxied by the volume and open interest, which are divided into expected and unexpected portions by using the previous data. The daily, intradilay, and overnight cash volatility is estimated by the GJR-GARCH model. We find a positive contemporaneous relationship between the intradaily stock market volatility and the unexpected futures volume while the relationship between the volatility and expected futures volume is weakly negative or non-existent. We also find that the unexpected futures volume strongly causes intradaily cash volatility. On the other hand, the overnight cash volatility causes the unexpected futures volume. The impulse responses between these variables are all positive. The result implies that during a trading time futures trading tends to increase the cash volatility while the unexpected overnight changes in cash volatility tends to increase the futures trading activities. We, however, find no association between the cash volatility and futures maturities.

• The Journal of Fisheries Business Administration
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• v.47 no.1
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• pp.1-20
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• 2016

The purpose of this study is to assess the effects of outlook project for olive flounder, from the view point of price stabilization, market efficiency, and causality of the prices in different distribution channels. Analytical results show that the volatility of producer price of olive flounder has been significantly mitigated after the implementation of the outlook project. The market efficiency is estimated to be improved after implementing the outlook project although there is an inefficiency on price determination process in some producing regions. The causality test on the producer and wholesale price shows that producing stage leads the wholesale stage in forming the prices. It is found that Jeju leads the flounder price on the size of 500g and 2kg, while Wando leads the price of 1kg size. These estimation result as whole indicate that outlook project for olive flounder has accomplished the intended goals.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.143-160
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• 2017

Since officially assessed land price system was introduced, it has functioned as the criterion for establishing and implementing real estate policies. However, there is a controversial issue about the adequacy of the officially assessed land price system. The problem is that it is difficult to establish a statistical model due to too many land characteristics. Also, local economy, macroeconomic environments and development plans are not reflected in the land price evaluation model. Considering longitudinal and cross-sectional variables, a two-way error component panel model was used in this study. This analysis model includes variables reflecting land characteristics, macroeconomic volatility, and development project. The Paju LCD Industrial Complex was selected as a analysis area and an empirical analysis was performed. According to the analysis, the number of significant land characteristic variables were 14(31%) under 5% significance level. Macroeconomic volatility has had an influence on the land price and year variable reflecting development project has consistently been significant since the industrial complex was designated. Therefore, this study suggests that the land price evaluation model should be improved by simplifying land characteristic variables and including macroeconomic and regional economic variables.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.645-668
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• 2022

Hydrogen energy is emerging as an important means of carbon neutrality in the various sectors including power, transportation, storage, and industrial processes. Fuel cell power plants are the fastest spreading in the hydrogen ecosystem and are one of the key power sources among means of implementing carbon neutrality in 2050. However, high volatility in system marginal price (SMP) and renewable energy certificate (REC) prices, which affect the profits of fuel cell power plants, delay the investment timing and deployment. This study applied the real option methodology to analyze how the dual uncertainties in both SMP and REC prices affect the investment trigger price level in the irreversible investment decision of fuel cell power plants. The analysis is summarized into the following three. First, under the current Renewable Portfolio Standard (RPS), dual price uncertainties passed on to plant owners has significantly increased the investment trigger price relative to one under the deterministic price case. Second, reducing the volatility of REC price by half of the current level caused a significant drop in investment trigger prices and its investment trigger price is similar to one caused by offering one additional REC multiplier. Third, investment trigger price based on gray hydrogen and green hydrogen were analyzed along with the existing byproduct hydrogen-based fuel cells, and in the case of gray hydrogen, economic feasibility were narrowed significantly with green hydrogen when carbon costs were applied. The results of this study suggest that the current RPS system works as an obstacle to the deployment of fuel cell power plants, and policy that provides more stable revenue to plants is needed to build a more cost-effective and stable hydrogen ecosystem.

• Korean System Dynamics Review
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• v.12 no.4
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• pp.93-124
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• 2011

The introduction of competition in the generation of electricity has raised the fundamental question of whether markets provide the right incentives for the provision of the capacity needed to maintain system reliability. Capacity mechanisms are adopted around the world to guarantee appropriate level of investment in electricity generation capacity. In this study, we discuss these approaches and analyze the capacity pricing mechanisms from the adequacy perspective. We conclude that the design of capacity mechanism is very important to decrease electricity spot price and increase total electric capacity. Specifically, the constant of capacity pricing mechanism made a difference to the performance of electricity market. However, the slope of capacity price mechanism is better than the constant of that in improving performance of electricity market.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.163-190
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• 2003

This study tests the hypothesis of market efficiency through the information spillover effects over price and volatility across countries by using open-to-close(daytime) returns and close-to-open(overnight) returns of NASDAQ, KOSDAQ and JASDAQ data from January 3, 1997 to December 21, 2000. Based on Granger-causality and time-varying AR(1)-GARCH(1, 1)-M models we document that the evidence of statistically significant conditional mean and volatility spillovers effects from the daytime returns and volatility of NASDAQ to the overnight returns and volatility of KOSDAQ is observed both before and after the IMF foreign currency crisis but not to the close-to-open return before the IMF foreign currency crisis. We can understand the information spillover effect from NASDAQ to KOSDAQ on the overnight rather than the daytime grows more significantly after the IMF foreign currency crisis. We also find the interactive information spillover effect between NASDAQ and JASDAQ both before and after the IMF financial crisis, in particular, to close-to-open return. In addition, the market efficiency between KOSDAQ and NASDAQ is on an increasing trend through IMF foreign currency crisis.

• Management & Information Systems Review
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• v.30 no.2
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• pp.237-255
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• 2011

This empirical study is focused on practical application of Range-Based Volatility which is estimated by opening, high, low, closing price of overall asset. Especially proper forecasting period is what I want to know. There is four useful Range-Based Volatility(RV) such as Parkinson(1980; PK), Garman and Klass(1980; GK) Rogers and Satchell(1991; RS), Yang and Zhang(2008; YZ). So, four RV of KOPSI 200 index during 2000.5.22-2009.9.18 was used for empirical test. The emprirical result as follows. First, the best RV which shows the best forecasting performance is PK volatility among PK, GK, RS, YZ volatility. According to estimating period forcasting performance of RV shows delicate difference. PK has better performance in the period with financial crisis of sub-prime mortgage loan. if not, RS is better. Second, almost result shows better performance on forecasting volatility without sub-prime mortgage loan period. so we can say that forecasting performance is lower when historical volatiltiy is comparatively high. Finally, I find that longer estimating period in AR(1) and MA(1) model can reduce forecasting error. More interesting point is that the result shows rapid decrease form 60 days to 90 days and there is no more after 90 days. So, if we forecast the volatility using Range-Based volaility it is better to estimate with 90 trading period or over 90 days.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1-10
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• 2020

This study investigates the problem of outlier detection based on discrete wavelet transform in the context of time series data where the identification and treatment of outliers constitute an important component. An outlier is defined as a data point that deviates so much from the rest of observations within a data sample. In this work we focus on the application of the traditional method suggested by Tukey (1977) for detecting outliers in the closed price series of the Saudi Arabia stock market (Tadawul) between Oct. 2011 and Dec. 2019. The method is applied to the details obtained from the MODWT (Maximal-Overlap Discrete Wavelet Transform) of the original series. The result show that the suggested methodology was successful in detecting all of the outliers in the series. The findings of this study suggest that we can model and forecast the volatility of returns from the reconstructed series without outliers using GARCH models. The estimated GARCH volatility model was compared to other asymmetric GARCH models using standard forecast error metrics. It is found that the performance of the standard GARCH model were as good as that of the gjrGARCH model over the out-of-sample forecasts for returns among other GARCH specifications.