• Management Science and Financial Engineering
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• v.20 no.1
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• pp.11-16
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• 2014

Extending from Grossman and Stiglitz (1980), we provide an asset pricing model of a synchronously traded cross-listed pair under information asymmetry. Following Garbade and Silber (1983), the model further embraces multi-market price discovery in a dynamic framework. The implications are as follows: The price sensitivity of holdings is higher for informed traders than for uninformed traders; the largest cross-border price spread occurs in the absence of arbitrageurs; price discovery is more likely in markets with a larger population of informed traders; and parity convergence accelerates with a higher price elasticity of demand of arbitrageurs.

• Culinary science and hospitality research
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• v.23 no.2
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• pp.126-134
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• 2017

The purpose of this paper was to examine the dynamics of the price discovery function between lean hog futures and spot markets using the vector error correction model (VECM). The researcher also investigated the existence of the long-run equilibrium relationship between the lean hog futures and spot markets. Daily time series data of lean hog futures and spot observed in the Korean market during the period from 5 Jan. 2011 to 28 Dec. 2012 were analyzed. To examine the price discovery, this study employed the Gonzalo and Granger's (1995) information ratio and Hasbrock's (1995) information ratio measurement method. The significant findings of the study are summarized as follows. First, lean hog futures and spot market are significantly correlated. Secondly, the lean hog future market plays a more dominant role in price discovery than the spot market. Finally, price discovery measures based on the VECM suggested that the lean hog future market plays a more dominant role in price discovery than the lean hog spot market. This is the important systematic empirical work to find the relationship between the lean hog future and spot market.

• Management & Information Systems Review
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• v.32 no.5
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• pp.287-300
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• 2013

In this paper, price discovery between spot and futures in crude oil markets investigated using the Gonzalo and Granger and Hasbrouck common-factor models. The main findings are as follows. 1) Crude oil futures and spot market are cointegrated. 2) Following the preceding studies, we judged that Dubai(WTI) futures markets contribute to the price discovery process than Dubai(WTI) spot market when this Gonzalo-Granger and Hasbrouck information ratio for Dubai(WTI) market are larger than 0.5. In other words, the futures markets of Dubai and WTI plays a more dominant role in price discovery than the spot market. 3) But Brent futures market does not contribute to the price discovery process.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.799-826
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• 2006

Combining recent advances in causal flows with time series analysis, relationships among eight North American natural gas spot market prices are examined. Results indicate that price discovery tends to occur in excess demand regions and move to excess supply regions. Across North America, the U.S. Midwest region represented by Chicago spot market is the most important market for price discovery. The Ellisburg-Leidy Hub in Pennsylvania is important in price discovery, especially for markets in the eastern two-thirds of the U.S. Malin Hub in Oregon is important for the western markets including the AECO Hub in Alberta, Canada.

• Management & Information Systems Review
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• v.32 no.3
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• pp.285-297
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• 2013

In this study, price discovery among the KOSPI200 markets(KOSPI200 spot, KOSPI200 Futures and The ETFs) is investigated using the vector error correction model(VECM). The main findings are as follows. KODEX200(KOSEF200), KOSPI200 spot and Futures are cointegrated in most cases. Daily data from KODEX200(KOSEF200), KOSPI200 spot and KOSPI200 futures show that the movements of the three markets are interrelated. Specially, KODEX200 contains the most information, followed by the KOSPI200 spot and futures markets. KODEX200 contribute to the price discovery process. Namely KODEX200 plays a more dominant role in price discovery than the KOSPI200 spot and futures.

• 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.

• Management & Information Systems Review
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• v.38 no.1
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• pp.141-153
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• 2019

This study attempts to analyze the role of price discovery and the dynamic interdependence between KOSPI200 Index and KODEX Leverage(KODEX inverse), which are Korea's representative ETFs, using the vector error correction model. For the empirical analysis, one minute data of KODEX leverage, KODEX inverse and KOSPI200 index from April 10, 2018 to July 10, 2018 were used. The main results of the empirical analysis are as follows. First, between KODEX Leverage and KOSPI200 index, we found evidence that KODEX leverage plays a dominant role in price discovery. In addition, the KOSPI200 index is superior to price discovery between KODEX inverse and KOSPI200 index. Second, the KOSPI200 index has a relatively strong dependence on KODEX leverage, which is consistent with the KODEX leverage index playing a dominant role in price discovery compared to the KOSPI200 index. On the other hand, KOSPI200 index has a dependency on KODEX inverse index, but it is weaker than KODEX leverage index. These results are expected to be useful information for investors in capital markets.

• Environmental and Resource Economics Review
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• v.15 no.3
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• pp.479-504
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• 2006

This paper analyzes a price discovery process for international crude oils including the WTI, Brent and Dubai. Error correction model is employed considering non-stationarity property of crude oil price and the contemporaneous causality is constructed by graph theory to analyze the short-term causality. The empirical analysis for January 4., 1999 to July 15., 2005 reveals that the Brent price interconnects between the WTI price and the Dubai price. This result implies the substantial influence of the Brent price as a marker oil.

• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.493-517
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• 2012

This paper analyzes a price discovery process for gasoline among branded and independent stations in Korea using a vector error correction model (VECM) and directed acyclic graphs (DAG). Two data sets for daily prices of medium level gasoline running from April 15, 2008 to May 31, 2009 and from January 1, 2011 to December 31, 2011 are used for empirical analysis. Empirical results show that S-OIL has an exogeneity and played a important role in the flow of price information in the market in the first period. In the second period, SK energy played a key role in price discovery process in the market. The price of NH-OIL stations do not cause the price of any other stations, which implies that the entrance of new branded stations with lower gasoline price to market has no influence on gasoline prices of retail markets.

• Management & Information Systems Review
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• v.35 no.2
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• pp.1-12
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• 2016

In this study, price discovery between the KOSPI200 spot, and leveraged ETFs(Leveraged KODEX, Leveraged TIGER, Leveraged KStar) is investigated using the vector error correction model(VECM). The main findings are as follows. Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot are cointegrated in most cases. There is no interrelations between the movement of Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot markets in case of daily data. Namely, in daily data, Leveraged KODEX(Leveraged TIGER, Leveraged KStar) doesn't plays more dominant role in price discovery than the KOSPI200 spot.