• Journal of Information Technology Applications and Management
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• v.20 no.3_spc
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• pp.201-217
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• 2013

This paper analyzes the effect of network neutrality regulation on social welfare using the two-sided market under the network congestion. This paper deals with zero price rule regulation which means the price regulation on the side of content. The results are as follows : First, under the monopoly platform, internet use price, contents price, and the number of internet user and content provider are all decreasing as the network congestion increases. Second, under the monopoly platform internet use price, contents price, and the number of internet user and content provider are all increasing as the network capacity increases. Third, the price of internet use and contents internet use which maximize social welfare are increasing and the number of internet user and content provider are decreasing as the network congestion increases. Fourth, optimal network capacity for monopoly platform provider is less than socially optimal network capacity. Fifth, if network neutrality regulation is enforced, the price of internet use is higher than monopoly platform provider and the price of contents is lower than monopoly platform provider. Also, the number of internet user is less than monopoly platform provider and the number of content provider is more than that. By the way, when network congestion increases, internet use price, the number of internet user, and the number of content provider are decreasing. Sixth, network neutrality regulation is more effective for internet user side than contents provider when network congestion is considered. This means that network neutrality regulation is not effective for contents market side when network congestion is seriously large.

• Journal of Platform Technology
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• v.6 no.2
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• pp.10-18
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• 2018

The purpose of this study was to empirically analyze relations between color changes in the product specification and demand changes with price elasticity in the Chinese mobile phone market. In previous studies on price elasticity, the usual analysis units were product categories or SBU within a given product category. Unlike them, the this study set an analysis unit of price elasticity to focus on colors, which are investigated in the research fields of experiential marketing, aesthetic marketing, and cognitive psychology. Actual sales data according to the mobile phone price changes by the color were based on the sales volume of a sales agency at China's largest B2C site. The findings were as follows: first, price elasticity according to the six colors was higher than the absolute value of 1, which means that demands made flexible reactions to price changes. Secondly, there were differences in price elasticity according to the colors. Aroma white color made the smallest increase in sales volume at the same price discount, whereas diamond color made the biggest increase in sales in the same price discount scope. These findings indicate that more profit can be generated in mobile phone sales in China by setting different price discount or increase rates according to colors or producing different amounts of mobile phones according to colors. Distributors or sales agents can have a chance for higher profit by ordering and selling mobile phones in certain colors than others from mobile phone manufacturers. The academic findings indicates that there are differences in preference and price elasticity according to colors under the mobile phone category in the Chinese market, which means that the present study made an academic contribution by proposing a microscopic analysis unit for product price elasticity and expanding its concept.

• Korean Management Science Review
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• v.32 no.3
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• pp.91-103
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• 2015

This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.

• KDI Journal of Economic Policy
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• v.26 no.2
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• pp.281-314
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• 2004

This paper theoretically formulated and empirically explored the relationship between exchange rate pass-through (ERPT) for (average) market price and an individual country's price, using steel products data in the US market, with special reference to two major steel exporting countries, Korea and Japan. It was found that the direction of market ERPT can be different from that of individual ERPT that each exporter experiences, due to strategic interactions among producers and different parameters. Vector error correction (VEC) models and impulse response analysis were used with the statistical inference based on the bootstrap-after- bootstrap of Kilian (1998) for short-run, and the fully modified estimation of Phillips and Hansen (1990) was used for long-run. Empirical results indicate that market ERPT in the US market due to changes in Korea-US exchange rates is different from those due to changes in Japan-US exchange rates. The framework developed in this study indicates that this phenomenon is attributed to either (i) the two countries have individual ERPTs of different magnitudes and directions for the products in the US market, or (ii) the pricing strategies of the other exporters' (to the US steel market) respond differently depending on whether the price of the product from Korea changes or that from Japan does. As each exporter's ERPT can be significantly different, and market response to each country's ERPT can be also different, this study concludes that it is crucial for an exporter to understand how competitors in the market respond to changes in its price, as well as to understand how its price changes when the relevant exchange rate fluctuates.

• The Journal of Fisheries Business Administration
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• v.45 no.3
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• pp.85-98
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• 2014

This study aimed to segment Chinese fisheries consumer market by means of cluster analysis based on Shanghai region consumers. The survey is conducted to 350 shanghai people on March 17-21 in 2014 and investigate demographic characteristics and consumer's behaviors unique to each segmented market by preference, labelling, quality, price, safety. The result of cluster analysis identified four market segments such as Catering type market, Worth pursuing type market, Substance pursuing type market, Trend pursuing type market. Catering type market is a passive fisheries consumption market and is not high attractive for Korea fisheries export market. Value pursuing type market consider importance to labelling, origin, brand and require high-quality and differentiation strategies. This market's main target species are high price fisheries such as tuna, salmon, crocker. Substance pursuing type market consider fisheries's safety and quality and purchases more popular fisheries such as crocker, hairtail, promfret, mackerel, squid. Trend pursuing type market's consumers prefer to purchase brands and trendy seafood rather than taste.

• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.65-94
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• 2009

The event of change in KOSPI 200 Index composition is one of the main subjects for the test of EMH. According to EMH, when a certain event is not related with firm's fundamental value, stock price should not change after the announcement of news. This hypothesis leads us to the conclusion of horizontal demand curve of stock. This logic was questioned by Shleifer(1986) and argued that downward sloping demand curve hypothesis was supported. But Harris and Gruel(1986) found a different empirical evidence that price reversal occurs in the long run, which is called price pressure hypothesis. They argued that short term price effect by large block trading (price pressure) is offset in the long run because these event is unrelated to fundamental value. Therefor, they argued that EMH can not be rejected in the long run. Until now, there are two empirical studies with Korean market data in this area. Using a data with same time period of $1996{\sim}1999$, Kweon and Park(2000) and Ahn and Park(2005) showed that stock price or beta is not significantly affected by change in index composition. This study retested this event expanding sample period from 1996 to 2006, and analyzed why this event was considered an uninformative events in the preceding studies. We analyzed a market impact by separating samples according to firm size and market condition. In case of newly enlisted firm, we found the evidence supporting price pressure hypothesis on average. However, we found the long run price effect in the sample of large firms under bearish markets. At the same time, we know that the number of samples under the category of large firms under bearish markets is relatively small, which drives the same result of supporting the hypothesis that change in index composition is a non-informative event on average. Also, the long run price effect of large size firms under bearish markets was supported by the analyses using trading volumes. On the other hand, in case of delisting from the index, we found the long run price effect but that was not supported by trading volume analyses.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.245-253
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• 2020

If the conversion rate of jeonse price to monthly rent is the market interest rate or the landlord's expected return, then the conversion rate of jeonse price to monthly rent in the country should be the same. However, the conversion rate of jeonse price to monthly rent has always been higher than the market interest rate. This study identifies the supply cost components of rental housing as a risk premium in the presence of current housing prices, market interest rates, depreciation costs, holding taxes, and leases, and identifies the relationship between the current housing prices and each factor. Housing rent is expressed as the current price. This overcomes the shortcomings that implicitly assume fluctuations in housing prices or do not include current housing prices in the conversion rate of jeonse price to monthly rent. This study found that the conversion rate of jeonse price to monthly rent is the required rate of return or required rate of renter, not market interest rate, by expressing the supply cost of rental housing as a combination of components. This not only explained the fact that the conversion rate of jeonse price to monthly rent was always higher than the market interest rate, but also explained the regional differences. It also explained why the conversion rate of jeonse price to monthly rent varies by type of housing.

• Environmental and Resource Economics Review
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• v.29 no.2
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• pp.145-170
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• 2020

This study analyzes the dependence structure between energy (crude oil, natural gas, coal) prices and economic (real and financial) uncertainty. Summary of the results of the dependence structure between energy prices and economic uncertainty analysis is as follows. First, the results of model selection show that the BB7 copula model for the pair of crude oil price and economic uncertainty, the Joe copula model for the pair of natural gas price and economic uncertainty, and the Clayton copula model for the pair of coal price and economic uncertainty were chosen. Second, looking at the dependency structure, it showed that the pair of energy (crude oil, natural gas, coal) prices and real market uncertainty show positive dependence. Whereas, the only pair of financial market uncertainty-crude oil price shows positive dependency. In particular, crude oil price was found to have the greatest dependence on economic uncertainty. Third, looking at the results of tail dependency, the pair of real market uncertainty-crude oil price and pair of real market uncertainty-natural gas price have an asymmetric relationship with the upper tail dependency. It can be seen that the only pair of financial market uncertainty-crude oil represents asymmetric relationships with the upper tail dependencies. In other words, combinations with asymmetric relationships have shown strong dependence when negative extreme events occur. On the other hand, tail dependence between economic uncertainty and coal price be not found.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.41-79
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• 2007

This study examines the expiration-day effects of stock index futures and options in the Korean stock market. The so-called 'expiration-day effects', which are the abnormal stock price movements on derivatives expiration days, arise mainly from cash settlement. Index arbitragers have to bear the risk of their positions unless they liquidate their index stocks on the expiration day. If many arbitragers execute large buy or sell orders on the expiration day, abnormal trading volumes are likely to be observed. If a lot of arbitragers unwind positions in the same direction, temporary trading imbalances induce abnormal stock market volatility. By contrast, if some information arrives at market, the abnormal trading activity must be considered a normal process of price discovery. Stoll and Whaley(1987) investigated the aggregate price and volume effects of the S&P 500 index on the expiration day. In a related study, Stoll and Whaley(1990) found a similarity between the price behavior of stocks that are subject to program trading and of the stocks that are not. Thus far, there have been few studies about the expiration-day effects in the Korean stock market. While previous Korean studies use the KOSPI 200 index data, we analyze the price and trading volume behavior of individual stocks as well as the index. Analyzing individual stocks is important for two reasons. First, stock index is a market average. Consequently, it cannot reflect the behavior of many individual stocks. For example, if the expiration-day effects are mainly related to a specific group, it cannot be said that the expiration of derivatives itself destabilizes the stock market. Analyzing individual stocks enables us to investigate the scope of the expiration-day effects. Second, we can find the relationship between the firm characteristics and the expiration-day effects. For example, if the expiration-day effects exist in large stocks not belonging to the KOSPI 200 index, program trading may not be related to the expiration-day effects. The examination of individual stocks has led us to the cause of the expiration-day effects. Using the intraday data during the period May 3, 1996 through December 30, 2003, we first examine the price and volume effects of the KOSPI 200 and NON-KOSPI 200 index following the Stoll and Whaley(1987) methodology. We calculate the NON-KOSPI 200 index by using the returns and market capitalization of the KOSPI and KOSPI 200 index. In individual stocks, we divide KOSPI 200 stocks by size into three groups and match NON-KOSPI 200 stocks with KOSPI 200 stocks having the closest firm characteristics. We compare KOSPI 200 stocks with NON-KOSPI 200 stocks. To test whether the expiration-day effects are related to order imbalances or new information, we check price reversals on the next day. Finally, we perform a cross-sectional regression analysis to elaborate on the impact of the firm characteristics on price reversals. The main results seem to support the expiration-day effects, especially on stock index futures expiration days. The price behavior of stocks that are subject to program trading is shown to have price effects, abnormal return volatility, and large volumes during the last half hour of trading on the expiration day. Return reversals are also found in the KOSPI 200 index and stocks. However, there is no evidence of abnormal trading volume, or price reversals in the NON-KOSPI 200 index and stocks. The expiration-day effects are proportional to the size of stocks and the nearness to the settlement time. Since program trading is often said to be concentrated in high capitalization stocks, these results imply that the expiration-day effects seem to be associated with program trading and the settlement price determination procedure. In summary, the expiration-day effects in the Korean stock market do not exist in all stocks, but in large capitalization stocks belonging to the KOSPI 200 index. Additionally, the expiration-day effects in the Korean stock market are generally due, not to information, but to trading imbalances.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.19-26
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• 2019

The paper aims to measure stock price volatility on Ho Chi Minh stock exchange (HSX). We apply symmetric models (GARCH, GARCH-M) and asymmetry (EGARCH and TGARCH) to measure stock price volatility on HSX. We used time series data including the daily closed price of VN-Index during 1/03/2001-1/03/2019 with 4375 observations. The results show that GARCH (1,1) and EGARCH (1,1) models are the most suitable models to measure both symmetry and asymmetry volatility level of VN-Index. The study also provides evidence for the existence of asymmetric effects (leverage) through the parameters of TGARCH model (1,1), showing that positive shocks have a significant effect on the conditional variance (volatility). This result implies that the volatility of stock returns has a big impact on future market movements under the impact of shocks, while asymmetric volatility increase market risk, thus increase the attractiveness of the stock market. The research results are useful reference information to help investors in forecasting the expected profit rate of the HSX, and also the risks along with market fluctuations in order to take appropriate adjust to the portfolios. From this study's results, we can see risk prediction models such as GARCH can be better used in risk forecasting especially.