• Management & Information Systems Review
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• v.33 no.3
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• pp.93-104
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• 2014

This study investigates price discovery between BlueNext spot and futures in EU ETS carbon emission markets using vector error correction model, GG and Hasbruck information ratio. Especially EUA is European Union Allowances traded on the Emissions Trading Scheme. This emission asset attracts and increasing attention among operators, investors and brokers on emission markets. In this study, we found BlueNext spot and EUA futures market are cointegrated. Following the preceding studies, we judged that EUA futures market contribute to the price discovery process than BlueNext spot market when this GG and Hasbrouck information ratio for BlueNext market are larger than 0.5. In other words, the futures market of EUA plays a more dominant role in price discovery than the spot market.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.582-583
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.584-585
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Journal of Korea Trade
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• v.27 no.5
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• pp.167-198
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• 2023

Purpose - This paper aims to compare and analyze the co-movements and information spillover effects between the international commodity futures markets and the South Korean stock markets during the COVID-19 and the 2008 financial crises. Design/methodology - The DCC-GARCH model is used in the co-movements analysis. In contrast, the BEKK-GARCH model is used to evaluate information spillover effects. The statistical data used is from January 1, 2005, to December 31, 2022. It comprises the Korea Composite Stock Price Index data and daily international commodity futures prices of natural gas, West Texas Intermediate crude oil, gold, silver, copper, nickel, soybean, and wheat. Findings - The results of the co-movement analysis were as follows: First, it was shown that the co-movements between the international commodity futures markets and the South Korean stock markets were temporarily strengthened when the COVID-19 and 2008 financial crises occurred. Second, the South Korean stock markets were shown to have high correlations with the copper, nickel, and crude oil futures markets. The results of the information spillover effects analysis are as follows: First, before the 2008 financial crisis, four commodity futures markets (natural gas, gold, copper, and wheat) were shown to be in two-way leading relationships with the South Korean stock markets. In contrast, seven commodity futures markets, except for the natural gas futures market, were shown to be in two-way leading relationships with the South Korean stock markets after the financial crisis. Second, before the COVID-19 crisis, most international commodity futures markets, excluding natural gas and crude oil future markets, were shown to have led the South Korean stock markets in one direction. Third, it was revealed that after the COVID-19 crisis, the connections between the South Korean stock markets and the international commodity futures markets, except for natural gas, crude oil, and gold, were completely severed. Originality/value - Useful information for portfolio strategy establishment can be provided to investors through the results of this study. In addition, it is judged that financial policy authorities can utilize the results as data for efficient regulation of the financial market and policy establishment.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.3
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• pp.79-91
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• 2016

This paper is the first of its kind using a non-linear approach based on cross-correlation function (CCF) to investigate the information arrival hypothesis in crude palm oil (CPO) futures market. Based on daily data from 1986 to 2010, our empirical results reveal that: First, the volume of volatility is not a proxy of information flow. Second, dependence causality running from current return to future volume in conditional variance exhibit an asymmetric pattern of time span with different signs of correlation between price and volume series. This finding indicates the presence of noise traders' hypothesis of price-volume interaction in CPO futures market. Both findings suggest that this futures market is weak-form inefficiency. In terms of investors' behavior, they tend to change their expectations on current return based on errors made in previous trade in generating abnormal volume in the subsequent period. As implied, it is advisable for the investors devise their future trading strategies according to time span and changes of return.

• Korean Business Review
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• v.9
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• pp.24-41
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• 1996

• The Journal of Fisheries Business Administration
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• v.37 no.1 s.70
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• pp.95-110
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• 2006

Japan's frozen shrimp future market is the only fisheries future commodity market in the world. This empirical study examines the lead and lag relationship between Japan frozen shrimp spot and future markets using the daily prices from August 1, 2002 to December 31, 2005. Frozen shrimp future contract is listed on Japan Kansai Commodities Exchange. Japan imports approximately 250,000 tons of frozen shrimp annually, of which just under 70,000 tons, nearly 30%, are black tiger shrimp. Approximately 90% of black tiger shrimp are caught in Indonesia, India, Thailand and Vietnam, and the two largest consumers of these shrimp are Japan and the U.S.A. Kansai Commodities Exchange adopts the India black tiger shrimp as standard future commodity. We use unit root test, Johansen cointegration test, Granger causality test, Vector autoregressive analysis and Impulse response analysis. However, considering the long - term relationships between the level variables of frozen shrimp spot and futures, we introduced Vector Error Correction Model. We find that the price change of frozen shrimp futures with next 1, 2, 3, 4, 5 month maturity have a strong predictive power to the change of frozen shrimp spot and the change of frozen shrimp spot also have a predictive power to the change of frozen shrimp with next 1, 2, 3 month maturity. But, the explanatory power of the frozen shrimp futures is relatively greater than that of frozen shrimp spot.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.105-108
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• 1997

Previous studies in stock market predictions using artificial intelligence techniques such as artificial neural networks and case-based reasoning, have focused mainly on spot market prediction. Korea launched trading in index futures market (KOSPI 200) on May 3, 1996, then more people became attracted to this market. Thus, this research intends to predict the daily up/down fluctuant direction of the price for KOSPI 200 index futures to meet this recent surge of interest. The forecasting methodologies employed in this research are the integration of genetic algorithm and artificial neural network (GAANN) and the integration of genetic algorithm and case-based reasoning (GACBR). Genetic algorithm was mainly used to select relevant input variables. This study adopts the categorical data preprocessing based on expert's knowledge as well as traditional data preprocessing. The experimental results of each forecasting method with each data preprocessing method are compared and statistically tested. Artificial neural network and case-based reasoning methods with best performance are integrated. Out-of-the Model Integration and In-Model Integration are presented as the integration methodology. The research outcomes are as follows; First, genetic algorithms are useful and effective method to select input variables for Al techniques. Second, the results of the experiment with categorical data preprocessing significantly outperform that with traditional data preprocessing in forecasting up/down fluctuant direction of index futures price. Third, the integration of genetic algorithm and case-based reasoning (GACBR) outperforms the integration of genetic algorithm and artificial neural network (GAANN). Forth, the integration of genetic algorithm, case-based reasoning and artificial neural network (GAANN-GACBR, GACBRNN and GANNCBR) provide worse results than GACBR.

• International Area Studies Review
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• v.14 no.2
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• pp.25-40
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• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.