• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.135-164
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• 2005

We analyze trade and balance records of 10,000 stock investment accounts of individual investors for the period of 1998 to 2003. Individual investors em an annual gross return of 12.3% while the KOSPI and the value weighted composite including KOSDAQ stocks yield 13.6% and 9.7% respectively during the same period. Net return performance is 8.3%, a drop of 5.3% mainly due to heavy trading. Individual investors' annual turnover amounts to over 270 percent. In an analysis of groups formed on the month's end position value, the performance of the top quintile is found comparable to the market while the rest yield significantly lower risk-adjusted returns than the market. We also find evidence rejecting the rational expectation model while supporting the overconfidence hypothesis which states overconfidence leads to a higher level of trading, resulting in poor performance. Individuals tilt their stock investment toward high-beta, small, and value stocks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.123-130
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• 2021

With the recent developments in computer technology, there has been an increasing interest in the field of machine learning. This also has led to a significant increase in real business cases of machine learning theory in various sectors. In finance, it has been a major challenge to predict the future value of financial products. Since the 1980s, the finance industry has relied on technical and fundamental analysis for this prediction. For future value prediction models using machine learning, model design is of paramount importance to respond to market variables. Therefore, this paper quantitatively predicts the stock price movements of individual stocks listed on the KOSPI market using machine learning techniques; specifically, the reinforcement learning model. The DQN and A2C algorithms proposed by Google Deep Mind in 2013 are used for the reinforcement learning and they are applied to the stock trading strategies. In addition, through experiments, an input value to increase the cumulative profit is selected and its superiority is verified by comparison with comparative algorithms.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.301-322
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• 2004

The current petroleum stockpiling by Korean government is based on the static concept of dead-stock. However, the recent changes in economic environment is requiring a transition to the dynamic concept of flow-stock. This study suggested selective trading strategies using basis of changing oil prices as an option for improving the economics of domestic strategic petroleum reserve (SPR), and quantitatively analyzed their effects. For this purpose, we tested the validity of selective trading strategies using the weekly spot and forwards prices of WTI for the period of October 1997 to August 2002. Summarizing the simulation results, the selective trading strategies would increase the expected values of profits and decrease their volatilities compared to those of traditional routine strategies. And, the adoption of trigger value could increase the improvements by the selective trading strategies. Based on the results, we suggest that, in order to improve the economics of domestic petroleum stockpiling, it is necessary to actively utilize the reserve facilities and the reserved petroleum with proper derivatives position.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.359-364
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• 2021

Recently, research on predictive systems using deep learning and machine learning of artificial intelligence is being actively conducted. Due to the development of artificial intelligence, the role of the investment manager is being replaced by artificial intelligence, and due to the higher rate of return than the investment manager, algorithmic trading using artificial intelligence is becoming more common. Algorithmic trading excludes human emotions and trades mechanically according to conditions, so it comes out higher than human trading yields when approached in the long term. The deep learning technique of artificial intelligence learns past time series data and predicts the future, so it learns like a human and can respond to changing strategies. In particular, the LSTM technique is used to predict the future by increasing the weight of recent data by remembering or forgetting part of past data. fbprophet, an artificial intelligence algorithm recently developed by Facebook, boasts high prediction accuracy and is used to predict stock prices and cryptocurrency prices. Therefore, this study intends to establish a sound investment culture by providing a new algorithm for automatic cryptocurrency trading by analyzing the actual value and difference using fbprophet and presenting conditions for accurate prediction.

• The Korean Journal of Financial Management
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• v.26 no.4
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• pp.165-189
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• 2009

According to disclosure regulation, insider can hide their trading until disclosure day, because there be interval between trading time and disclosure time. To accommodate strategic trade, they have an incentive to be brought disclosure interval as long as possible. This research investigate whether strategical behaviour of informed traders using disclosure intervals exists in domestic stock market.ls xt, we aney he whether they can get abnormal return through stealth strategy after announcement date. We also evaluate the effect of mimicking trading on price impact with the assumption of existence of mimicking trading. Our major research results are as follows: In case of main shareholder without having no prompt disclosure duty, the frequency of trading started at the beginning of month is shown significantly higher than others. This result shows a direct evidence that informed traders buy or sell their equity strategically using disclosure intervals. Also, we find the result that the coefficient of strategic variables has highest value in middle size information. However, the empirical evidence that informed trader get abnormal return through strategic trading was not shown in this study. Meanwhile, stock price over-reacts for selling transaction on trading point and is recovered after disclosure date., so we assume possibility of mimicking trading exists in domestic stock market.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.27
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• pp.69-95
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• 2005

East Asia has played an important role in the economic and social development in the Asian pacific region and in the global arena. In the region the impact of companies centralizing their logistics activities around a few distribution centers has already led some leading ports such as Singapore, Hong Kong to transform and expand their functions and business activities to provide port users with value added logistics services. Other ports in the region also have an important part to play in the total logistics Chain. In these environments, the maritime activities of Jang BoGo, who was the maritime king of the commercial maritime empire in East Asia in the 9th century, give many implications to the international logistics network strategy that Korea has to take in order to become a power of International Logistics. Though the trading and economic environments at that time may be quite different from today, the super-national maritime management pattern that Jang Bo-go, founder of the Northeast Asian maritime trading kingdom devised, gives us many implications in the global trading and economic environments, in the respects of overseas direct investment and international logistics. Accordingly, the paper aims to examine the establishment of hub port in Northeast Asia, modelled after the maritime network management strategy of Jang BoGo.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.179-206
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• 2011

Masan Port, which is a main entrance to Korea, has undergone the tough time these days. Many problems are mainly due to the deterioration of harbor facilities, the shortage of waterfront area and the decrease of the trading volumes. Especially the trading volumes are seriously affected by the Busan New Port, which was not only very close to the Masan Port but constructed in a large scale. For the Masan Port to develop continuously, therefore, it is vital to modernize harbor facilities, redevelop the old harbor, expand its waterfront, construct green port and develop harbor for sightseeing. At the same time, Masan port should be ready to develop a higher value added port. To vitalize Masan port's economy, we have to push forward a differentiation strategy that makes Masan port specialized harbor for distributing goods like hard and heavy cargo.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.127-137
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• 2021

Mainland China area has been a long-term, major trade rival and partner of Taiwan, accounting for more than 40% of Taiwan's total annual trade exports, and so Sino-US trade friction is expected to have a significant impact on Taiwan's economy in the future. This study focuses on major bad news of Sino-US trade frictions and how it generates short-term shocks for Taiwan's equity market and fear sentiment. It further explores the mutual interpretation relationship between price changes such as VIX, Taiwan's stock market index, and the VIX ETF to identify which factors have information leadership as leading indicators. The study period covers 750 trading days from 2017/1/3 to 2020/1/31. This study finds that, when a policy news is announced, the stock market index falls significantly, the change in the trading price (net value) of the VIX ETF rises significantly, and the overprice rate significantly drops, but VIX does not, showing that fear sentiment exists in the Taiwan's market. The net value of the VIX ETF shows an information advantage as a leading indicator. This study suggests that, when the world's two largest economies clash over trade, the impact on Taiwan's equity market is inevitable, and that short-term fear effects will arise.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.6
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• pp.692-698
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• 2022

With the expansion of domestic hydrogen fuelling station infrastructure, it is necessary to secure reliability among hydrogen traders, and for this, technology to accurately measure hydrogen is important. In this study, 4 types of hydrogen trading volume calculation models (model 1-4) were presented to improve the accuracy of the hydrogen trading volume. In order to obtain the reference value of model 4, and experiment was conducted using a flow rate measurement equipment, and the error rate of the calculated value for each model was compared and analyzed. As a result, model 1 had the lowest metering accuracy, model 2 had the second highest metering accuracy and model 3 had the highest metering accuracy until a certain point. But after the point, model 2 had the highest metering accuracy and model 3 had the second metering accuracy.

• The Korean Journal of Financial Studies
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• v.2 no.2
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• pp.315-344
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• 1995

The relationship of information flow and market price formation are central to the basic tenets of financial economics. Whereas information is usually treated as being either public or private(monopolistic), most empirical studies focus on the price effects of public announcements. More recent research has centered more on the role of private information, such as insider trading, in efficient pricing and whether such trading increases investor welfare. Typically, 'insider trading' refers to an officer that trades in his/her company's shares. Insider trading, however, also refers to anyone who generates private, albeit costly, information concerning a stock's fundamental value. Normally, such insider activity is more difficult to ascertain. One way in which negative information is revealed is through short-selling activity, especially the monthly short-interest positions reported by the national stock exchanges. Diamond and Verrecchia(1987) provide a theoretical paradigm that predicts a negative price adjustment upon announcement of n company's monthly short interest, if the short interest displays an unusual increase and is correlated with negative information that is not yet public. Empirical studies of the short-run, negative price effect predicted by Diamond and Verrecchia find mixed results. One explanation is that the time period studied is too short for the market to absorb the informational content of these announcements. One reason is that these announcements are an ambiguous signal that requires more individuals and time to collect and act on the same information before full revelation occurs or before the implicit information becomes publicly known. This 'long delayed reaction' also serves as a motivation for related research on the wealth effect of mergers, share repurchases, and initial equity offerings in which long-run performance differs from the initial, short-run reaction to such announcements or offerings.