• Smart Media Journal
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• v.11 no.1
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• pp.38-45
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• 2022

A lot of research is being going until this day in order to obtain stable profit in the stock market. Trading algorithms are widely used, accounting for over 80% of the trading volume of the US stock market. Despite a lot of research, there is no trading algorithm that always shows good performance. In other words, there is no guarantee that an algorithm that performed well in the past will perform well in the future. The reason is that there are many factors that affect the stock price and there are uncertainties about the future. Therefore, in this paper, we propose a model using TimeGAN that predicts future returns well and selects algorithms that are expected to have high returns based on past records of the returns of algorithms. We use TimeGAN becasue it is probabilistic, whereas LSTM method predicts future time series data is deterministic. The advantage of TimeGAN probabilistic prediction is that it can reflect uncertainty about the future. As an experimental result, the method proposed in this paper achieves a high return with little volatility and shows superior results compared to many comparison algorithms.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.117-128
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• 2017

The increased national utilization of Bitcoin results in multiple complications. Therefore, there are continuous debates on the subject, the main point being how to characterize Bitcoin's asset nature. The following study bases, focusing on the function value, justifies Bitcoin's asset characterization. Using regression analysis to construct relations between gold and indexes such as CPI, DXY, and S&P500 as well as the relation between Bitcoin and the previously mentioned indexes, the question of whether gold and Bitcoin reacted in a similar fashion to the same indicators was examined. The results conclude that Bitcoin has similarities with gold, showing that it is risk averse and an investable commodity in lieu to profitability when it comes to inflation and currency value. When considered with price volatility, the main force behind the function of investment asset, categorizing Bitcoin as a high-risk financial investment asset rather than as a currency within the system would be more effective for management.

• Journal of Digital Contents Society
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• v.11 no.1
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• pp.91-97
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• 2010

Flash memory has been used by many digital devices for data storage, exploiting the advantages of non-volatility, low power, stability, and so on, with the help of high integrity, large capacity, and low price. As the fast growing popularity of flash memory, the density of it increases so significantly that its entire address mapping table becomes too big to be stored in SRAM. This paper proposes the associated page address cache with an efficient table management scheme for hybrid flash translation layer mapping. For this purpose, all tables are integrated into a map block containing entire physical page tables. Simulation results show that the proposed scheme can save the extra memory areas and decrease the searching time with less 2.5% of miss ratio on PC workload and can decrease the write overhead by performing write operation 33% out of total writes requested.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.369-378
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• 2013

The Korean Won-Dollar exchange markets showed radical price movements in the late 1990s and 2008. Therefore it provides good sources for studying volatility phenomena. Using the GARCH option models, I analysed how the prices of foreign exchange options react volatilities in the foreign exchange spot prices. For this I compared the explanatory power of three option models(Black and Scholes, Duan, Heston and Nandi), using the Won-Dollar OTC option markets data from 2006 to 2013. I estimated the parameters using MLE and calculated the mean square pricing errors. According to the my empirical studies, the pricing errors of Duan, Black and Scholes models are 0.1%. And the pricing errors of the Heston and Nandi model is greatest among the three models. So I would like to recommend using Duan or Black and Scholes model for hedging the foreign exchange risks. Finally, the historical average of spot volatilities is about 14%, so trading the options around 5% may lead to serious losses to sellers.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.49-69
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• 2008

Recently, ubiquitous computing technology becomes available to develop advanced electronic commerce：u-commerce. Hence, it is the very time to perform feasibility analysis in applying ubiquitous computing technology, especially estimating economical value of the on-going technology. Hence, the purpose of this paper is to propose a financial value estimating methodology in performing feasibility test on ubiquitous computing technology. To do so, Black and Scholes model is basically adopted. To show the feasibility if the idea proposed in this paper, actual case study through focused group interview with those who are actually performing on-going ubiquitous computing projects. As the result, we validated the possibility of applying Black-Sholes model to assessing feasibility analysis for ubiquitous technology development with the price of call option, volatility, and the comparison with other similar technologies.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.702-714
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• 2020

Stock investment is a personal investment technique that has gathered tremendous interest since the reduction in interest rates and tax exemption. However, it is risky especially for those who do not have expert knowledge on stock volatility. Therefore, it is well understood that accurate stock trend prediction can greatly help stock investment, giving birth to a volume of research work in the field. In order to compare different research works and to optimize hyper-parameters for prediction models, it is required to have an evaluation standard that can accurately assess performances of prediction models. However, little research has been done in the area, and conventionally used methods have been employed repeatedly without being rigorously validated. For this reason, we first analyze performance evaluation of stock trend prediction with respect to performance metrics and data composition, and propose a fair evaluation method based on prediction disparity ratio.

• Resources Recycling
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• v.32 no.6
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• pp.67-78
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• 2023

The rare metals used as raw materials in high-tech industries undergo changes in demand structures and supply chains following domestic industrial structural shifts and technological advancements, exhibiting high price volatility. Therefore, it is necessary to periodically analyze changes in the demand structures of rare metals. Since domestic demand for most rare metals relies on imports in Korea, the changes in domestic demand for rare metals can be identified by analyzing changes in their trade structure. In the present study, we analyze the changes in trade volume, trade growth rate, trade rankings, and trading countries from 2000 to 2022 for 35 rare metals, categorized into five types-ores, metals, alloys, compounds, and scrap. The trade of the raw materials of rare metals in Korea has generally increased since the 2000s, except for a significant decline in 2009 and 2016. The total trade volume, encompassing both exports and imports, has increased by approximately tenfold in 2022 compared to 2001. Until the mid-2010s, the trade of the raw materials of rare metals was primarily focused on those used in steel-manufacturing such as silicon, nickel, chrome, molybdenum, manganese, and others. However, after that period, there has been an increase in the trade of platinum group metals like palladium, rhodium, platinum, and the raw materials of rare metals for secondary battery-manufacturing such as lithium and cobalt. Particularly in 2022, lithium has become the largest share in trade of the raw materials of rare metals in Korea, due to the price surge and increase in demand.

• Food Science and Industry
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• v.51 no.4
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• pp.270-277
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• 2018

The rising global demand for food and beverages with higher protein content provides manufacturers with great opportunities for innovation and premium positioning of their products as healthy choices. However, the market price volatility and supply risks associated with animal-based proteins can quickly erode margins and profitability. A diversified protein strategy that includes plant-based soy protein greatly improves your ability to predict profitability over time, while maintaining or even improving product quality.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.133-145
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• 2023

This paper examines whether investors have adapted to the venture capital(VC) investment style. VC firms invest in privately held companies and generate returns by selling them after the lock-up period expires. We analyze the impact on stock prices before and after the lock-up period expiration, and compare the Cumulative Abnormal Return(CAR) between the past period(2015-2017) and the recent period(2020-2022) to investigate the effect of the second venture boom. The main findings are as follows. First, unlike in the past, stock price returns around the lock-up period expiration have been lower than the KOSDAQ index in recent years. Second, the impact on stock prices is significant for both 1-month and 12-month lock-up periods. Specifically, it is confirmed that stocks held by venture capital and professional investors with a 1-month lock-up period respond in advance to their information after the second venture boom. Finally, we find that there is a difference in CAR depending on whether or not the company received VC investment after the second venture boom. Based on our findings, we suggest that VC firms need to revise their exit strategies to improve performance. This includes finding ways to reduce information asymmetry and fees, as well as developing strategies to mitigate market volatility. Additionally, the current lock-up period for VCs should be reconsidered as it may increase the risk of stock price decline. We recommend that the government revise the scope and duration of lock-up periods to protect investors after IPO.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.273-284
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• 2024

This study investigates the impact of international oil price fluctuations on overseas construction orders secured by domestic and foreign companies. The analysis employs statistical data spanning the past 20 years, encompassing international oil prices, overseas construction orders from domestic firms, and new overseas construction orders from the top 250 global construction companies. The correlation between these variables is assessed using correlation coefficients(R), determination coefficients(R²), and p-values. The results indicate a strong positive correlation between international oil prices and overseas construction orders. The correlation coefficient between domestic overseas construction orders and oil prices is found to be 0.8 or higher, signifying a significant influence. Similarly, a high correlation coefficient of 0.76 is observed between oil prices and new orders from leading global construction companies. Further analysis reveals a particularly strong correlation between oil prices and overseas construction orders in Asia and the Middle East, potentially due to the prevalence of oil-related projects in these regions. Additionally, a high correlation is observed between oil prices and orders for industrial facilities compared to architectural projects. This suggests an increase in plant construction volumes driven by fluctuations in oil prices. Based on these findings, the study proposes an entry strategy for navigating oil price volatility and maintaining competitiveness in the overseas construction market. Key recommendations include diversifying project locations and supplier bases; utilizing hedging techniques for exchange rate risk management, adapting to local infrastructure and market conditions, establishing local partnerships and securing skilled local labor, implementing technological innovations and digitization at construction sites to enhance productivity and cost reduction The insights gained from this study, coupled with the proposed overseas expansion strategies, offer valuable guidance for mitigating risks in the global construction market and fostering resilience in response to international oil price fluctuations. This approach is expected to strengthen the competitiveness of domestic and foreign construction firms seeking success in the international arena.