• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.109-140
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• 2008

The primary objective of this paper investigates whether asymmetric volatility phenomenon is caused by differences of opinion among investors and analyses information availability has an effect on asymmetric volatility. The empirical test period covers recent 6 years from January 4, 2000 to December 29, 2005. Five portfolios have been formed according to information availability(volume and market value). For the purpose of this study, We use TGARCH model, TGARCH-M model and adjusted model which include trading volume as a proxy differences of opinion among investors. The results are summarized as follows ; First, adjusted model analysis shows that asymmetric volatility phenomenon is disappeared or asymmetric coefficient and ratio is decreased than basis model. Second, portfolio analysis shows that the higher volume and market value, the more prominent asymmetric volatility phenomenon. And adjusted model analysis shows the higher volume and market value, the more decrease asymmetric ratio. Over all, assertion that differences of opinion among investors has caused asymmetric volatility phenomenon is regarded as reasonable. And, We see that information availability have great effect on asymmetric volatility phenomenon. We think that theses results can also occur opinion adjustment of optimistic investors. Namely, asymmetric volatility phenomenon can occur difference of information authenticity.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.381-388
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• 2003

This paper presents a method of giving weights to garbage class clustering and Filler model to improve performance of keyword spotting system and a time-saving method of dialogue speech processing system for keyword spotting by calculating keyword transition probability through speech analysis of task domain users. The point of the method is grouping phonemes with phonetic similarities, which is effective in sensing similar phoneme groups rather than individual phonemes, and the paper aims to suggest five groups of phonemes obtained from the analysis of speech sentences in use in Korean morphology and in stock-trading speech processing system. Besides, task-subject Filler model weights are added to the phoneme groups, and keyword transition probability included in consecutive speech sentences is calculated and applied to the system in order to save time for system processing. To evaluate performance of the suggested system, corpus of 4,970 sentences was built to be used in task domains and a test was conducted with subjects of five people in their twenties and thirties. As a result, FOM with the weights on proposed five phoneme groups accounts for 85%, which has better performance than seven phoneme groups of Yapanel [1] with 88.5% and a little bit poorer performance than LVCSR with 89.8%. Even in calculation time, FOM reaches 0.70 seconds than 0.72 of seven phoneme groups. Lastly, it is also confirmed in a time-saving test that time is saved by 0.04 to 0.07 seconds when keyword transition probability is applied.

• Journal of Distribution Science
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• v.10 no.2
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• pp.7-17
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• 2012

The aim of this study is to empirically explore micro and macroeconomic factors affecting the Pakistani sugar industries and searching the energy potential of this industry, through the survey of literature. The empirical part has been explored by employing Vector Autoregression (VAR), Granger Causality tests and simultaneous equation models through quarterly data for the period of 1991q2-2008q4. The study also aims to devise policies for the development of sugar industries and identify its growing importance for the energy sector of Pakistan. Empirical tests applied on the domestic prices of sugar, domestic interest rates, and exchange rate, productive capacities of sugar mills, per capita income, world sugar prices on cultivable area and sugar production reveal very useful results. Results reveal an improvement of productive capacity of the sugar mills of Pakistan on account of increasing crushing capacity of this sector. Negative effect of rising wholesale prices on the harvesting area was also observed. Profit earnings of the sugar mills significantly increase with the rise of sugar prices but the system does not exist for the farming community to share the rising prices of sugar. The models indicate positive and significant effect of local prices of sugar on its volume of import. Another of the findings of this study positively relates the local sugar markets with the international prices of sugar. Additionally, the causality tests results reveal exchange rate, harvesting area and overall output of sugarcane to have significant effects on the local prices of sugar. Similarly, import of sugar, interest rate, per capita consumption of sugar, per capita national income and the international prices of sugar also significantly affect currency exchange rate of Pakistani rupee in terms of US$. The study also finds sugar as an essential and basic necessity of the Pakistani consumers. That is why there are no significant income and price effects on the per capita consumption of sugar in Pakistan. All the empirical methods reiterate the relationship of variables. Economic policy makers are recommended to improve governance and management in the production, stock taking, internal and external trading and distribution of sugar in Pakistan using bumper crop policies. Macroeconomic variables such as interest rate, exchange rate per capita income and consumption are closely connected with the production and distribution of sugar in Pakistan. The cartelized role of the sugar industries should also be examined by further studies. There is need to further explore sugar sector of Pakistan with the perspective of energy generation through this sector; cartelized sugar markets in Pakistan and many more other dimensions of this sector. Exact appraisal of sugar industries for energy generation can be done appropriately by the experts from applied sciences.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.607-615
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• 2015

Mosts user of internet and smart phone has certificate, and uses it when money transfer, stock trading, on-line shopping, etc. Mosts user stores certificate in a hard disk drive of PC, or the external storage medium. In particular, the certification agencies are encouraged for user to store certificate in external storage media such as USB memory rather than a hard disk drive. User think that the external storage medium is safe, but when it is connect to a PC, certificate may be copied easily, and can be exposed to hackers through malware or pharming site. Moreover, if a hacker knows the user's password, he can use user's certificate without restrictions. In this paper, we suggest secure management scheme of the private key file using a password of the encrypted private key file, and a USB Memory's hardware information. The private key file is protected safely even if the encrypted private key file is copied or exposed by a hacker. Also, if the password of the private key file is exposed, USB Memory's container ID, additional authentication factor keeps the private key file safe. Therefore, suggested scheme can improve the security of the external storage media for certificate.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.85-98
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• 2016

This study makes an empirical comparison of various realized volatilities (RVs) in terms of overnight returns. In financial asset markets, during overnight or holidays, no or few trading data are available causing a difficulty in computing RVs for a whole span of a day. A review will be made on several RVs reflecting overnight return variations. The comparison is made for forecast accuracies of several RVs for some financial assets: the US S&P500 index, the US NASDAQ index, the KOSPI (Korean Stock Price Index), and the foreign exchange rate of the Korea won relative to the US dollar. The RV of a day is compared with the square of the next day log-return, which is a proxy for the integrated volatility of the day. The comparison is made by investigating the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE). Statistical inference of MAE and RMSE is made by applying the model confidence set (MCS) approach and the Diebold-Mariano test. For the three index data, a specific RV emerges as the best one, which addresses overnight return variations by inflating daytime RV.

• Environmental and Resource Economics Review
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• v.29 no.2
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• pp.219-246
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• 2020

From the Phase II (2018~2020) of K-ETS, the offset credit from 'CDM projects that domestic companies and others have carried out in foreign countries' can be used in the K-ETS. As a result, stakeholders in the K-ETS market are actively developing overseas CDM projects, such as the 'high-efficiency cook stove project'. which can secure a large amount of credits while marginal cost is relatively low. This paper develops the investment decision-making model of offset project for the 'high-efficiency cook stove project' using the real option approach. Under the uncertainty of the emission allowance price, the optimal investment threshold (p^⁎) is derived and sensitivity analysis is conducted. As a result, in the standard scenario (PoA-S), the optimal investment threshold is 29,054won/ton, which is lower than the stock price (p^⁎_spot). However, allocation entities are not only economics in the CDM project, but also CDM risk factors such as non-renewable biomass ratio, cook stove replacement ratio, equity ratio with host country, investment period and submission limitation of emission allowance. In addition, offset project developers will be able to derive the optimal investment threshold for each business stage and use it for economic feasibility checks.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.697-703
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• 2022

Due to the recent economic downturn caused by Covid-19 and the unstable international situation, many investors are choosing the derivatives market as a means of investment. However, the derivatives market has a greater risk than the stock market, and research on the market of market participants is insufficient. Recently, with the development of artificial intelligence, machine learning has been widely used in the derivatives market. In this paper, reinforcement learning, one of the machine learning techniques, is applied to analyze the scalping technique that trades futures in minutes. The data set consists of 21 attributes using the closing price, moving average line, and Bollinger band indicators of 1 minute and 3 minute data for 6 months by selecting 4 products among futures products traded at trading firm. In the experiment, DNN artificial neural network model and three reinforcement learning algorithms, namely, DQN (Deep Q-Network), A2C (Advantage Actor Critic), and A3C (Asynchronous A2C) were used, and they were trained and verified through learning data set and test data set. For scalping, the agent chooses one of the actions of buying and selling, and the ratio of the portfolio value according to the action result is rewarded. Experiment results show that the energy sector products such as Heating Oil and Crude Oil yield relatively high cumulative returns compared to the index sector products such as Mini Russell 2000 and Hang Seng Index.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.151-159
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• 2010

Currently, by using the Internet, We can do varius things such as Web surfing, email, on-line shopping, stock trading on your home or office. However, as being out of the concept of security from the beginning, it is the big social issues that malicious user intrudes into the system through the network, on purpose to steal personal information or to paralyze system. In addition, network intrusion by ordinary people using network attack tools is bringing about big worries, so that the need for effective and powerful intrusion detection system becomes very important issue in our Internet environment. However, it is very difficult to prevent this attack perfectly. In this paper we proposed the algorithm for the detection of DoS attacks, and developed attack detection tools. Through learning in a normal state on Step 1, we calculate thresholds, the number of packets that are coming to each port, the median and the average utilization of each port on Step 2. And we propose values to determine how to attack detection on Step 3. By programing proposed attack detection algorithm and by testing the results, we can see that the difference between the median of packet mounts for unit interval and the average utilization of each port number is effective in detecting attacks. Also, without the need to look into the network data, we can easily be implemented by only using the number of packets to detect attacks.

• Knowledge Management Research
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• v.24 no.3
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• pp.73-94
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• 2023

With the virtual asset market's rapid growth, government regulations on listing and trading procedures are expected. However, specific measures are currently lacking. To ensure stable inclusion in the institutional framework, precise regulations are needed for market development and investor protection. This study compares self-regulatory guidelines of the top domestic virtual asset exchanges with Korea Exchange's Preliminary Listing Examination Standards (2022) to enhance timeliness and relevance. It defines IEO, IPO, and ICO concepts and addresses conflicts of interest in IEO. Analyzing delisted virtual assets, it categorizes issues and classifies listing examination guidelines into formal and qualitative requirements. The study examines self-regulatory guidelines based on continuity, transparency, stability, corporate characteristics, and investor protection criteria, along with five special requirements for virtual assets. Improvement measures include regular disclosures of governance structure, circulation volume, and the establishment of independent audit institutions. This research further analyzes delisting cases, classifies issues, and proposes solutions. Considering stock market similarities, it offers measures based on the institutional framework.

• Korean Journal of Culture and Social Issue
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• v.13 no.3
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• pp.89-109
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• 2007

This study is an exploratory study on stock investment behaviors of individual investors in psychological perspective. The study is based on many behavioral finance studies which overconfidence of individual investors has an effect on irrational investment decision making and investment behaviors such as excessive trading. Accordingly, this study was to investigate the factors of self-enhancement perception on confidence of investment of individual investors and to find whether these psychological biases lead to irrational investment behaviors. The results indicated that there were sex differences in the factors of self-enhancement perception on individual investors' confidence of investment. In case of male investors, they were confident of their ability of investment but in case of female investors, they were confident of optimistic expectation of return. Also, male investors were more confident of investment than female investors. In addition, the result showed that risky investment behaviors of individual investors were influenced by psychological factors such as favorable self-evaluation, confidence of self-controllability, optimistic expectation of return and confidence of investment in part. This study suggests that further researches need to search after other variables which can mediate between psychological factors and investment behaviors of individual investors.