• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.191-212
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• 2003

Recently, there is a growing body of literature that suggests that information inefficiency is one of the causes of the asymmetric volatility. If this explanation for the asymmetric volatility is appropriate, then innovations, such as the introduction of futures, may be expected to impact the asymmetric volatility of stock market. As transaction costs and margin requirements in the futures market are lower than those in the spot market, new information is transmitted to futures prices more quickly and affects spot prices through arbitrage trading with spots. Also, the merit of the futures market may attract noise traders away from the spot market to the futures market. This study examines the impact of futures on the asymmetry of stock market volatility. If the asymmetric volatility is significant lower post-futures and exist in the futures market, it has validity that the asymmetric volatility is caused by information inefficiency in the spot market. The data examined are daily logarithmic returns on KOSPI 200 stock price index from January 4, 1993 to December 26, 2000. To examine the existence of the asymmetric volatility in the futures market, logarithmic returns on KOSPI 200 futures are used from May 4, 1996 to December 26, 2000. We used a conditional mode of TGARCH(threshold GARCH) of Glosten, Jagannathan and Runkel(1993). Pre-futures the spot market exhibits significant asymmetric responses of volatility to news and post-futures asymmetries are significantly lower, irrespective of bear market and bull market. The results suggest that the introduction of stock index futures has an effect on the asymmetric volatility of the spot market and are inconsistent with leverage being the sole explanation of asymmetry. However, it is found that the volatility of futures is not so asymmetric as expected.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.271-274
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• 2005

Under competitive power markets, various long-term and short-term contracts based on spot price are used by producers and consumers. So an accurate forecasting for spot price allow market participants to develop bidding strategies in order to maximize their benefit. Artificial Neural Network is a powerful method in forecasting problem. In this paper we used Radial Basis Function(RBF) network to forecast spot price. To learn ANN, in addition to price history, we used some other effective inputs such as load level, fuel price, generation and transmission facilities situation. Results indicate that this forecasting method is accurate and useful.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.3
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• pp.259-266
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• 2015

Among many energy resources, natural gas has recently received a remarkable amount of attention, particularly from the electrical generation industry. This is in part due to increasing shale gas production, providing an environment-friendly fossil fuel, and high risk of nuclear power. Because South Korea, the world's second largest LNG importing nation after Japan, has no international natural gas pipelines and relies on imports in the form of LNG, the natural gas has been traditionally procured by long term LNG contracts at relatively high price. Thus, there is a need of developing an Asian LNG trading hub, where LNG can be traded at more competitive spot prices. In a natural gas spot market, the amount of natural gas to be bought should be carefully determined considering a limited storage capacity and future pricing dynamics. In this work, the problem to find the optimal amount of natural gas in a spot market is formulated as a Markov decision process (MDP) in risk neutral environment and the optimal base stock policy which depends on a stage and price is established. Taking into account price and demand uncertainties, the basestock target levels are simply approximated from dynamic programming. The simulation results show that the basestock policy can be one of effective ways for procurement of LNG in a spot market.

• Environmental and Resource Economics Review
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• v.29 no.1
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• pp.91-111
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• 2020

While the renewable energy portfolio standard (RPS) is in place to expand the scale of renewable energy generation, the power producer can obtain the renewable energy credit (REC) and use it as an incentive to operate the facility. RECs secured by solar power generation can be traded through spot market or fixed price contracts, and, in the spot market trading, power producers are exposed to the uncertainty of REC spot price. In this study, real option analysis is conducted to analyze the optimal threshold of REC spot price for the conversion of REC trading method by power producer considering the uncertainty of REC spot price. We calculated the optimal threshold of REC spot price that can convert the trading method of REC from spot market to fixed price contract. In conclusion, the spot market trading is a rational trading method when considering the uncertainty of REC price, but the fixed price bidding is a rational trading method when not considering the uncertainty of REC price.

• 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.

• 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.

• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.1-7
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• 2006

In an electricity market, the spot market is normally integrated with a forward or future market. The advantage of the forward market is to allow the market participants to deal in a part or the whole trading portfolio at a fix price in advance and to avoid risk associated to the uncertain price of the spot market. Japan has introduced a continuous auction base forward market from April 2005. This paper analyzes the Japanese forward market rules and operations, and introduces a new algorithm that may improve the efficiency of the market itself. The proposed algorithm enables us to give consideration to the specific characteristics of the power system and to integrate them in the auction mechanism. The benefits of the proposed algorithm are verified on an electronic simulation platform and the results described in this paper.

• The Journal of Fisheries Business Administration
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• v.40 no.1
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• pp.51-74
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• 2009

The purpose of this study is to ascertain that how the futures market of the Japanese frozen shrimp that is the only fisheries asset all over the world can be efficient. Accordingly, this paper examines efficiency and information flow of the Japanese frozen shrimp market using data from Kansai Commodities Exchange frozen shrimp futures closing prices and spot prices. And then this paper estimates a forward price model using that data. From the model, risk premium is estimated and we could also analyse the future information flow into the futures market which reveals future spot prices. This thesis reached to conclusions as follows: First, the null of zero risk premium is rejected and the value of that is negative. Second, the time pattern of information flow into the futures market is that most of the information on future price arrives within a week and for the last week, most of relevant information is already incorporated. The result of this study contrasts with that of Stockman(1978) about currency futures market of U.S.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1480-1491
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• 2015

In new deregulated electricity market, short-term price forecasting is key information for all market players. A better forecast of market-clearing price (MCP) helps market participants to strategically set up their bidding strategies for energy markets in the short-term. This paper presents a new prediction strategy to improve the need for more accurate short-term price forecasting tool at spot market using an artificial neural networks (ANNs). To build the forecasting ANN model, a three-layered feedforward neural network trained by the improved Levenberg-marquardt (LM) algorithm is used to forecast the locational marginal prices (LMPs). To accurately predict LMPs, actual power generation and load are considered as the input sets, and then the difference is used to predict price differences in the spot market. The proposed ANN model generalizes the relationship between the LMP in each area and the unconstrained MCP during the same period of time. The LMP calculation is iterated so that the capacity between the areas is maximized and the mechanism itself helps to relieve grid congestion. The addition of flow between the areas gives the LMPs a new equilibrium point, which is balanced when taking the transfer capacity into account, LMP forecasting is then possible. The proposed forecasting strategy is tested on the spot market of the Nord Pool. The validity, the efficiency, and effectiveness of the proposed approach are shown by comparing with time-series models

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.94-96
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• 2004

This paper discusses the development of the educational simulator for the electricity spot market in korea. The interaction between lectures and users can be much enhanced via the web-based programs which result in the student's teaming effectiveness on an electricity spot market. However the difficulties for developing web-based application programs are that there can be the numerous unspecified users to access the application programs. To overcome the aforementioned multi-users problem and to develope the educational simulator, we have revised the system architecture, the modeling of application programs, and database which efficiently and effectively manages the complex data sets related to an electricity spot market. The developed application program is composed of the physical three tiers where the middle tier is logically divided into two kinds of application programs. The divided application programs are interconnected by using the Web-service based on XML (Extended Markup Technology) and HTTP (Hyper Text Transfer Protocol) which make it possible the distributed computing technology.