• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.127-134
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• 2007

There are many researches about the intelligent stock trading systems with the help of the advance of the artificial intelligence such as machine learning techniques, Though the establishment of the reasonable trading policy plays an important role in the performance of the trading systems most researches focused on the improvement of the predictability. Also some previous works, which treated the trading policy, treated the simplified versions dependent on the predictors in less systematic ways. In this paper, we propose the integrated multiple simulation' as a method of optimizing trading performance of stock trading systems. The propose method is adopted in the NXShell a development environment for neural network based stock trading systems. Under the proposed integrated multiple simulation', we simulate the multiple tradings for all combinations of the neural network's outputs and the trading policy parameters, evaluate the learning performance according to the various metrics and establish the optimal policy for a given prediction module based on the resulting performance. In the experiment, we present the trading policy comparison results using the stock value data from the KOSPI and KOSDAQ.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.71
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• pp.217-243
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• 2016

As the rapid development of IT and the internet changed the trading method from the traditional offline transaction into the online e-Trading, the international documentation standards, the eUCP and the domestic laws and legislations have been established, adapting to the new e-Trading environment. This study was conducted to analyze the factors which affect the use of uTradeHub on the domestic trading companies and trade-related organizations and suggest how to activate e-Trading. To do this, classify the users into the enterprises and the trade-related organizations, set up the hypothesis of the study with the measurement variables of the user convenience, the new service, the system suitability and the legislation environment and carry out a survey targeting the trading companies and the trade-related offices to do an actual proof analysis. The analysis was performed by using the statistical program, SPSS IBM22.0, and the study hypothesis was tested by the multiple regression analysis methodology. The test result showed that the trading companies set a high value on the user convenience, the new service and the legislation environment of uTradeHub, meanwhile the trade-related organizations regarded the system security and reliability, the user convenience and the legislation environment as the major affecting factor on the use of uTradeHub.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.1
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• pp.19-32
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• 2013

As cyber stock trading grows rapidly, stock trading using Home Trading System have been brisk recently. Home Trading System is a heavy-weight in the stock market, and the system has shown 75% and 40% market shares for KOSPI and KOSDAQ, respectively. However, since Home Trading System focuses on the convenience and the availability, it has some security problems. In this paper, we found that the authentication information in memory remains during the stock trading and we proposed its countermeasure through two-channel authentication using a mobile device such as a cell phone.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.301-319
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• 2013

Wireless and mobile communication technologies enable individuals who trade stocks and bonds to use mobile-based trading services. Due to rapidly developing mobile technologies and adoption of the advanced/smart mobile devices such as smart phones and tablets, the use of mobile trading systems (MTS) have increased at an unexpected rate. Although many prior studies measured service quality on various service-related fields, there are few studies that is related to mobile trading systems compared to more traditional PC-based home trading systems. This research searches determinants of service quality for mobile trading systems and examines the effects of these factors on the intention to mobile trading systems' continuous use. Through an extensive literature review, this research finds three dimensions for mobile trading systems : interaction quality, service environment quality, and service outcome quality. The result of analysis shows that personalization, connectivity, ease of use, informativeness, and monetary value enhance the intention to continuous use. Considering environmental conditions such as the high rate of MTS adoption among individual users and stiffer competition among securities firms, these findings may help practically securities firms' shaping MTS system development strategies for individual users' continuous use and for increasing new users adoption.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.85-97
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• 2018

This paper investigates factors underlying a decrease in trading values in KOSPI 200 futures/options market on the basis of the current state of the markets. Among the factors that could affect trading values in KOSPI 200 derivatives market, we focus on the market activity of underlying assets as it has an impact on the trading of financial derivatives. Trading value and volatility are designated as market activity and the empirical results confirm that the market activity of the underlying assets is significant in explaining the decrease in trading values in KOSPI 200 futures/options market. To figure out fundamental reasons of the decrease in trading values in this market, we examine mitigation of home bias and decrease in leverage incentives as they are presumed to have influence on KOSPI 200 index market. As the global and local financial environment is time-varying, the degree of home bias and the leverage demand also changes. It implies that institutional change and/or policy effort to promote the trading of KOSPI 200 financial derivatives should be made taking into account the fact that considerable portion of the change in trading values in financial derivatives market depends on the state of the market.

• International Journal of Precision Engineering and Manufacturing-Green Technology
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• v.5 no.5
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• pp.623-630
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• 2018

The renewable energy systems have been in the spotlight as an alternative for environmental issues. Therefore, the governmental policies are being implemented to spread of promote power generation system using renewable energy in various countries around the world. In addition, Korea has also developed a policy called the power trading contract which can profit from electricity produced from renewable power generation system through Korea Electric Power Corporation (KEPCO) and Korea Power Exchange (KPX). As a result, the power trading contracts can trade power after self-consuming in-house by using small-scale renewable power system for residential customers as well as electricity retailers. The power trading contracts applicable as a small-scale power system have a 'Net metering (NM)' and a 'Power Purchase Agreement (PPA)', and these two types of power trading contracts trade surplus power, but payment method of each power trading is different. The microgrid proposed in this paper is based on grid connected microgrid using Photovoltaic (PV) system and Energy Storage System (ESS), that supplied power to residential demand, we evaluate the operation cost of microgrid by power demand in each power trading contracts and propose the appropriate power trading contracts according to electricity demand.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.383-391
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• 2021

This study examines the connectedness between the number of COVID-19 cases in Thailand and trading value among investors in the Stock Exchange of Thailand. Daily data of COVID-19 cases and trading value were sourced from the Thailand ministry of public health and the Stock Exchange of Thailand, from January 12, 2020 to May 11, 2021. This study applies a multiple linear regression analysis to explain the relationship between variables. Empirical evidence clearly shows that the volatility of trading value was affected by COVID-19's new, confirmed, and deaths cases within the first pandemic period more than during the second pandemic period. Nevertheless, during the third pandemic period there is no evidence that the new, confirmed, and deaths cases significantly influenced trading value. Furthermore, the results show that COVID-19's new and deaths cases have a negative coefficient that indicated the trading value-buy/sell decreased in response to COVID-19's new and deaths cases, whereas the confirmed COVID-19 cases have a positive coefficient that indicated the trading value-buy/sell increased in response to COVID's confirmed cases. In summary, this study suggests that the number of COVID-19 cases have a significant impact on the trading value in the short term more than in the intermediate and long term.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.113-129
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• 2023

Purpose - The purpose of this study is to examine whether trading volume amplifies the extent to which lottery-type stocks are overpriced, and whether economic sentiment index explains time-variation in the magnitude of the volume amplification effect. Design/methodology/approach - We examine monthly returns on 5x5 monthly bivariate portfolios formed by lottery characteristics (measured by maximum daily return) and trading volume. In addition, we perform time-series regression tests to examine how the volume amplification effect changes in high and low economic sentiment periods, after controlling for Fama-French three factors. Findings - Our bivariate portfolio analysis shows that the overpricing of lottery-type stocks are mostly pronounced among high trading volume stocks. In contrast, for low trading volume stocks, overpricing of lottery-type stocks appears to vanish. Furthermore, the amplification effect of trading volume on overpricing of lottery-type stock is concentrated in high economic sentiment periods. Research implications or Originality - This study is the first attempt to examine whether trading volume drives lottery-type stocks' overpricing in the Korean stock market. Furthermore, our analysis unveils the time-varying nature of volume amplification effect. The results suggest that trading volume might play a important hidden role in asset pricing, opening a new line of researches in the future.

• Korea Trade Review
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• v.47 no.1
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• pp.99-114
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• 2022

This paper analyzed the dynamic conditional correlation between the carbon emission trading prices of Korea, China, EU, New Zealand. This paper was analyzed using the daily data of carbon emission trading prices of each country from January 12, 2015 to January 13, 2021 using the DCC-GARCH model. Summarizing the research results, first, the dynamic conditional correlation between carbon emission trading prices in the EU, Korea, and China, excluding New Zealand, was strong, indicating that there was a co-movement phenomenon. Second, it was found that carbon emission trading prices in major countries have a stronger tendency to co-movement due to global shocks. Third, it appears that the dynamic conditional correlation between the carbon emission trading prices of Korea and China is gradually strengthening. This study confirmed that the co-movement between carbon emission trading prices in Korea and other countries gradually intensified as time passed. In particular, it is meaningful in suggesting the implication that the phenomenon of co-movement between carbon emission trading prices in Korea and China is gradually intensifying.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.