• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.296-309
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• 2022

Timer options are one of the contingent claims that, for given the variance budget, its payoff depends on a random maturity in terms of the realized variance unlike the standard European vanilla option with a fixed time maturity. Since it was first launched by Société Générale Corporate and Investment Banking in 2007, the valuation of the timer options under several stochastic environment for the volatility has been conducted by many researches. In this study, we propose the pricing of timer power options combined with standard timer options and the index of the power to the underlying asset for the investors to actualize lower risks and higher returns at the same time under the uncertain markets. By using the asymptotic analysis, we obtain the first-order approximation of timer power options. Moreover, we demonstrate that our solution has been derived accurately by comparing it with the solution from the Monte-Carlo method. Finally, we analyze the impact of the stochastic volatility with regards to various parameters on the timer power options numerically.

• Journal of Electrochemical Science and Technology
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• v.12 no.4
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• pp.453-457
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• 2021

Lithium-sulfur (Li-S) batteries are one of attractive energy conversion and storage system based on high theoretical specific capacity and energy density with low costs. However, volatile nature of elemental sulfur is one of critical problem for their practical acceptance in industry because it considerably affects electrode uniformity during electrode manufacturing. In this work, polymeric sulfur composite consisting of ionic liquid (IL) are suggested to reduce volatility nature of elemental sulfur, resulting in better processibility of the Li-S cell. According to systematic spectroscopic analysis, it is found that polymeric sulfur is consisting of repeating units combining with elemental sulfur and volatility of them is negligible even at high temperature. In addition, the IL-embedded polymeric sulfur shows moderate cycle performance compared to the cell with elemental sulfur. From these results, it is found that the IL-embedded polymeric sulfur composite is applicable cathode candidate for the Li-S cell based on their excellent non-volatility as well as their superior electrochemical performance.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.17-24
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• 2021

The use of renewable energy sources for power generation has been steadily increasing. Power generation using renewable energy has the advantage of not generating carbon but has the disadvantage of high volatility depending on the weather. This volatility makes stable power supply difficult. Curtailment is occurring to address volatility. Various facilities are operated together to solve the loss caused by the curtailment. The existing SCADA must be modified for turbine control reflecting the conditions of various facilities. However, since it is difficult to modify SCADA, a modular control system is required. In this study, we propose Modular Control System Based on Closed-Loop Control for Wind Farms. Since the control logic can be changed without modifying SCADA, it is easy to respond to changes. The developed modular control system was evaluated as a lab test and confirmed to operate smoothly. Through future research, the experiment will be conducted by applying a modular control system to the actual wind farm.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.217-227
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• 2022

Predicting return and volatility in the global Capital Market during a pandemic is challenging, and it is more difficult for a specific sector, particularly if that sector has a positive outlook. The goal of this research is to look at the impact of COVID-19 on the mean and volatility of the Information Technology Indexes of the best nine technology-driven countries based on return performance using an econometric GARCH model that is widely used. The daily returns of information technology indexes are evaluated for the same from November 2018 to February 2021. Data is taken from Yahoo Finance for CAC Tech (France), DAX Tech (Germany), FTSE All Tech (UK), KOPSI 200 IT (Korea), NIFTY IT (India), S&P 500 IT (US), S&P TSX (Canada), SSE_IT (China) and TOPIX17 (Japan). The results show daily positive mean returns for 8 countries' IT Indices and further, an uptrend in mean daily returns is observed in the crisis period for 6 countries' IT Indices. The exogenous variable COVID-19 which was taken as a regressor for the GARCH model was found to be positively significant for IT indices of all the countries. The overall results confirm the presence of the mean-reverting phenomenon for IT indices of all the countries.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.203-215
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• 2022

Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan's emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.437-437
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• 2022

The prediction of dam inflow rate is crucial for the management of the largest multi-purpose dam in South Korea, the Soyang Dam. The main issue associated with the management of water resources is the stochastic nature of the reservoir inflow leading to an increase in uncertainty associated with the inflow prediction. The Autoregressive (AR) model is commonly used to provide the simulation and forecast of hydrometeorological data. However, because its estimation is based solely on the time-series data, it has the disadvantage of being unable to account for external variables such as climate information. This study proposes the use of the Autoregressive Exogenous Stochastic Volatility (ARXSV) model within a Bayesian modeling framework for increased predictability of the monthly dam inflow by addressing the exogenous and stochastic factors. This study analyzes 45 years of hydrological input data of the Soyang Dam from the year 1974 to 2019. The result of this study will be beneficial to strengthen the potential use of data-driven models for accurate inflow predictions and better reservoir management.

• Economic Analysis
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• v.25 no.3
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• pp.70-99
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• 2019

Using a stochastic volatility-in-mean VAR model consisting of the KOSPI index, the foreign exchange rate, the government bond rate, and the credit spread, this study investigates the effects of financial market uncertainty on financial markets. We find that higher uncertainty has recessionary effects on financial markets. The effects are especially stronger in equity markets and in won-dollar exchange markets. We also find that the effects of uncertainty become stronger during times of financial market stress compared to normal times. Finally, the results imply that financial market uncertainty may potentially affect the real sector, too.

• Korean small business review
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• v.40 no.1
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• pp.67-83
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• 2018

This study investigates the effects of the dynamics of the firm's reputation on performance. Particularly, we argued that not only the level of reputation but also the trend and volatility of reputation plays an important role in formulating the stakeholders' perception about the firm. From our empirical analysis of the U.S. venture capital firms between 1990 and 2010, we found that the level and trend of reputation are positively related to performance and that these relationships are weakened when the volatility of reputation increases. This paper discusses the theoretical contributions and practical implications of these findings.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.179-192
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• 2024

macOS presents challenges for memory data acquisition due to its proprietary system architecture, closed-source kernel, and security features such as System Integrity Protection (SIP), which are exclusive to Apple's product line. Consequently, conventional memory acquisition tools are often ineffective or require system rebooting. This paper analyzes the status and limitations of existing memory forensics research and tools related to macOS. We investigate methods for memory acquisition and analysis across various macOS versions. Our findings include the development of a practical memory acquisition and analysis process for digital forensic investigations utilizing OSXPmem and dd tools for memory acquisition without system rebooting, and Volatility 2, 3 for memory data analysis.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.37-48
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• 2023

Purpose - This study aims to explore the influence of emotional discrepancies among investors on the cryptocurrency market. It focuses on how varying emotions affect market dynamics such as volatility and trading volume in the context of Bitcoin trading. Design/methodology/approach - This study involves analyzing data from Bitcointalk.org, consisting of 57,963 posts and 2,215,776 responses from November 22, 2009, to December 31, 2022. Tools used include the Linguistic Inquiry and Word Count (LIWC) software for classifying emotional content and the Python Pattern library for sentiment analysis. Findings - The results show that heterogeneous emotional feedback, whether positive or negative, significantly influences Bitcoin's intraday volatility, skewness, and trading volume. These findings are more pronounced when the underlying emotion in the feedback is amplified. Research implications or Originality - This study underscores the significance of emotional factors in financial decision-making, especially within the realm of social media. It suggests that investors and market strategists should consider the emotional landscape of online forums when making investment choices or formulating market strategies. The research also paves the way for future studies regarding the behavioral impact of emotions on the cryptocurrency market.