• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.241-254
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• 2020

International payment is an essential part of the economy, which is beneficial to both commercial banks and trading enterprises. Moreover, service quality, which has been a key point of discussion for decades, relates to customer satisfaction. This study aims to investigate the factors influencing international payment service quality at the Join Stock Commercial Bank for Investment and Development of Vietnam (BIDV) from 2015 through 2019. This research deploys both quantitative and qualitative methods to discuss the effects of these components. Statistical data was examined through different tests, including reliability analysis, correlation, and regression analysis by SPSS 16.0. The authors obtain and analyze 157 valid responses from customer surveys, then by applying an integration SERVPERF and PSQM model, identify five main components: Reliability, Tangibles, Assurance, Convenience, and Responsiveness, which explain how the customer perceives the service quality of international payment activities at BIDV. The results show that these five factors have a positive relationship with service quality, in which, Reliability has the most significant impacts on service quality level. Besides, the findings not only contribute to the literature but also give some practical implications for BIDV to improve its international payment service quality and help them to obtain customer satisfaction in the fast-changing environment.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.303-310
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• 2021

A method for developing a visual information concept that analogously compares and analyzes macroscopic data changes in a simple form is needed. The development of the visual information concept requires the selection of visualization form, selection of rhetorical effects, and selection of digital expression elements. Among them, an example of a rhetorical effect selection method for effectively delivering visual information to a user is presented. In this study, metaphorical rhetoric, which allows data comparison and analysis from a macroscopic point of view, was selected for stock price analysis by period and industry. We present a two-dimensional three-stage shape change using a dandelion with spreading cockle hair as a metaphor and a three-dimensional three-stage shape change information expression method using a coral peony flower that changes shape and color according to time as a metaphor. Using this rhetorical metaphor, it is possible to compare macroscopic trading changes and stock prices by industry.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.21-38
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• 2023

An attempt has been made in this article to discuss the fundamentals of technical analysis of the stock market. A retail investor or trader may not have the wherewithal to source that kind of information. Technical analysis requires a candlestick chart only. Most of the brokers in India provide charting solutions as well. Studying the price action of a security or commodity or Forex generally indicates a price pattern. Prices react at certain levels and widely known as support and resistance levels. Since whatever is happening with the price of the security is considered to be a part of a pattern or cycle which has already played out sometime in the past, these studies help a keen technical analyst to identify with certain probability, the future movement of the price. Study of the candlestick patterns, price action, volumes and indicators offer the opportunities to identify a high probability trade with probable target and a stop loss. A trader or investor can take high probability trade or position and control only her losses.

• 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.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.409-415
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• 2011

TV broadcasting platform is evolving to the digital-TV, which is supporting data broadcasting service. Although the data broadcasting services (i.e., games, wether information, stock trading service) provide rich entertainment to viewers, they make the operation manners of digital-TV so complex that some viewers feel difficulty in using their TV sets. The paper tackles the problem by devising a method for constructing viewer-specific EPG configurations based on the viewers' ability of handling IT devices. The paper also propose an environment (e.g., EPG configuration transmitting method, EPG structure) that implements dynamically an EPG configuration based on the viewer's choice of EPG configuration.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.107-117
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• 2014

The main purpose of this study is to propose a portfolio investment strategy based on investor types information. For improvement of investment performance, artificial intelligence techniques are used to construct a portfolio. Among many artificial intelligence techniques, cluster analysis is applied to select securities and genetic algorithm is applied to assign the respective weight within the portfolio. Empirical experiments in the Korean stock market show that proposed portfolio investment strategy is practicable and superior strategy. This result implies that analysis of investor's trading behavior may assist investors to make an investment decision and to get superior performance.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.991-998
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• 2009

This paper deals with directivity forecasting of time series which is useful for futures trading in stock market. Directivity forecasting of time series is to forecast whether a given time series will rise or fall at next observation time point. For directional forecasting, we consider time regression model and ARIMA model. In particular, we study two statistics, intra-model and extra-model deviation and then show usefulness of intra-model deviation.

• 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.

• Journal of Digital Contents Society
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• v.13 no.4
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• pp.539-545
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• 2012

As a representative of the convergence of broadcasting and communication, the data service provide viewers new services such as games, weather services, and stock trading services on TV. The data service, however, has failed to gain the popularity with the viewers due to the short of killer services and the dominating power of TV programs. The paper introduces an MHP-based method for semantically integrate a data service to a TV program by allowing the data service to utilize the content of the TV program, which changes as time goes on.