• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.207-218
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• 2021

The present research intends to examine the herding aspect during the COVID-19 outbreak. The study is conducted to achieve specific objectives, so the underlying sampling technique is purposive sampling. The considered data source is the Pakistan Stock Exchange (PSX). Daily stock prices of 528 listed companies in PSX have been taken from the official website of PSX from 1998 to 2021. The current study envisions investigating the herding aspects for pre-pandemic and the time covering the pandemic period. The study has also targeted ten sectors of PSX. The present study's motive is to investigate investors' herding prospects before and during the pandemic in the Pakistan Stock Exchange (PSX) and its selected sectors. Daily closing stock prices of listed companies have been collected from the official website of PSX to calculate the stock returns. The Cross-Sectional Absolute Deviation (CSAD) has been used as a herding measure. Findings revealed that herding has not been observed in PSX during both time spans and even not during the bullish and bearish trends. However, robust sectoral evidence has been observed during the pandemic. It implies that investors in PSX tend to follow the crowd irrespective of making their own decisions to avoid further losses.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.485-495
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• 2021

Recently, vegetarian diets have experienced a dramatic increase in popularity. The aim of the study is to explore and test the relationship between the factors influencing consumers' dietary decisions in Ho Chi Minh City, Vietnam. The questionnaire applied a five-point Likert scale to investigate factors that affect Ho Chi Minh City's citizens when they have a vegetarian diet. 497 respondents (68% female; 61.2% aged 18-22; 82.7% had regular vegetarian diets) living in Ho Chi Minh City took part in both online and offline surveys. The results were processed by SPSS 22.0 software. The reliability was checked by Cronbach Alpha and Exploratory factor analysis (EFA) to identify the underlying relationships between measured variables. The Correlation analysis was implemented to show how strong and degree of two variables are related to each other before the multivariate regression equation was analyzed. The result showed the Five factors that were motivating people in Ho Chi Minh City to decide on plant-based diets, such as Animal Welfare, Health, Religion, Mood, and Reference groups. The mood is the most influential variable that significantly influences people's food choices. Attitudes toward vegetarian diets are changing. Therefore, recognizing the trends in food consumption might help companies take advantage of investment opportunities and build their marketing strategies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.685-695
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• 2021

This study explores the impact of stochastic volatility in option pricing. To be more specific, we compare the option pricing performance between stochastic volatility option pricing model, namely, Heston option pricing model and standard Black-Scholes option pricing. Our finding, based on the market price of SET50 index option between May 2011 and September 2020, demonstrates stochastic volatility of underlying asset return for all level of moneyness. We find that both deep in the money and deep out of the money option exhibit higher volatility comparing with out of the money, at the money, and in the money option. Hence, our finding confirms the existence of volatility smile in Thai option markets. Further, based on calibration technique, the Heston option pricing model generates smaller pricing error for all level of moneyness and time to expiration than standard Black-Scholes option pricing model, though both Heston and Black-Scholes generate large pricing error for deep-in-the-money option and option that is far from expiration. Moreover, Heston option pricing model demonstrates a better pricing accuracy for call option than put option for all level and time to expiration. In sum, our finding supports the outperformance of the Heston option pricing model over standard Black-Scholes option pricing model.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.741-749
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• 2021

The research paper endeavors to investigate the presence of seasonal anomalies in the Indian equity market. It also aims to verify the notion that equity markets are for long-term investors. The study employs daily index data of Sensex, Bombay Stock Exchange, to understand its volatility for the period ranging from January 2001 to August 2020. To analyze the seasonal effects in the stock market of India, multiple regression techniques along with descriptive analysis, graphical analysis and various statistical tests are used. The study also employs the rolling returns at different time intervals in order to understand the underlying risks and volatility involved in equity returns. The results from the analysis reveal that daily and monthly seasonality is not present in Sensex returns i.e., investors cannot earn abnormal returns by timing their investment decisions. Hence, the major finding of this study is that the Indian stock market performance is random, and the returns are efficient. The other major conclusion of the research is that the equity returns are profitable in the long run providing investors a hope that they can make gains and compensate for the loss in one period by a superior performance in some other periods.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.45-52
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• 2021

Stock price fluctuations affect investor returns, particularly, in this pandemic situation that has triggered stock market shocks. As a result of this situation, investors prefer to move their money into a safer portfolio. Therefore, in this study, we approach an efficient portfolio model using smart beta and combining others to obtain a fast method to predict investment stock returns. Smart beta is a method to selects stocks that will enter a portfolio quickly and concisely by considering the level of return and risk that has been set according to the ability of investors. A smart beta portfolio is efficient because it tracks with an underlying index and is optimized using the same techniques that active portfolio managers utilize. Using the logistic regression method and the data of 100 low volatility stocks listed on the Indonesia stock exchange from 2009-2019, an efficient portfolio model was made. It can be concluded that an efficient portfolio is formed by a group of stocks that are aggressive and actively traded to produce optimal returns at a certain level of risk in the long-term period. And also, the portfolio selection model generated using the smart beta, beta, alpha, and stock variants is a simple and fast model in predicting the rate of return with an adjusted risk level so that investors can anticipate risks and minimize errors in stock selection.

• Journal of Ginseng Research
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• v.46 no.2
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• pp.206-213
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• 2022

Ginsenoside Rb2 is an active protopanaxadiol-type saponin, widely existing in the stem and leave of ginseng. Rb2 has recently been the focus of studies for pharmaceutical properties. This paper provides an overview of the preclinical and clinical pharmacokinetics for Rb2, which exhibit poor absorption, rapid tissue distribution and slow excretion through urine. Pharmacological studies indicate a beneficial role of Rb2 in the prevention and treatment of diabetes, obesity, tumor, photoaging, virus infection and cardiovascular problems. The underlying mechanism is involved in an inhibition of oxidative stress, ROS generation, inflammation and apoptosis via regulation of various cellular signaling pathways and molecules, including AKT/SHP, MAPK, EGFR/SOX2, TGF-β1/Smad, SIRT1, GPR120/AMPK/HO-1 and NF-κB. This work would provide a new insight into the understanding and application of Rb2. However, its therapeutic effects have not been clinically evaluated. Further studies should be aimed at the clinical treatment of Rb2.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.75.4-75.4
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• 2019

We present a quantitative analysis of the relationship between the gas dynamics and star formation history of DDO 210 which is an irregular dwarf galaxy in the local Universe. We perform profile analysis of an high-resolution neutral hydrogen (HI) data cube of the galaxy taken with the large Very Large Array (VLA) survey, LITTLE THINGS using newly developed algorithm based on a Bayesian Markov Chain Monte Carlo (MCMC) technique. The complex HI structure and kinematics of the galaxy are decomposed into multiple kinematic components in a quantitative way like 1) bulk motions which are most likely to follow the underlying circular rotation of the disk, 2) non-circular motions deviating from the bulk motions, and 3) kinematically cold and warm components with narrower and wider velocity dispersion. The decomposed kinematic components are then spatially correlated with the distribution of stellar populations obtained from the color-magnitude diagram (CMD) fitting method. The cold and warm gas components show negative and positive correlations between their velocity dispersions and the surface star formation rates of the populations with ages of < 40 Myr and 100~400 Myr, respectively. The cold gas is most likely to be associated with the young stellar populations. Then the stellar feedback of the young populations could influence the warm gas. The age difference between the populations which show the correlations indicates the time delay of the stellar feedback.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.589-603
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• 2023

Deep generative models target to infer the underlying true data distribution, and it leads to a huge success in generating fake-but-realistic data. Regarding such a perspective, the data attributes can be a crucial factor in the data generation process since non-existent counterfactual samples can be generated by altering certain factors. For example, we can generate new portrait images by flipping the gender attribute or altering the hair color attributes. This paper proposes counterfactual disentangled variational autoencoder generative adversarial networks (CDVAE-GAN), specialized for data attribute level counterfactual data generation. The structure of the proposed CDVAE-GAN consists of variational autoencoders and generative adversarial networks. Specifically, we adopt a Gaussian variational autoencoder to extract low-dimensional disentangled data features and auxiliary Bernoulli latent variables to model the data attributes separately. Also, we utilize a generative adversarial network to generate data with high fidelity. By enjoying the benefits of the variational autoencoder with the additional Bernoulli latent variables and the generative adversarial network, the proposed CDVAE-GAN can control the data attributes, and it enables producing counterfactual data. Our experimental result on the CelebA dataset qualitatively shows that the generated samples from CDVAE-GAN are realistic. Also, the quantitative results support that the proposed model can produce data that can deceive other machine learning classifiers with the altered data attributes.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.46-58
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• 2023

Deterministic safety analysis is a crucial part of safety assessment, particularly when it comes to demonstrating the safety of nuclear power plant designs. The traditional approach to deterministic safety analysis models is to model the nuclear core using point kinetics. However, this simplified approach does not fully reflect the real core behavior with proper moderator and fuel reactivity feedbacks during the transient. The use of Multi-Physics approach allows more precise simulation reflecting the inherent three-dimensionality (3D) of the problem by representing the detailed 3D core, with instantaneous updates of feedback mechanisms due to changes of important reactivity parameters like fuel temperature coefficient (FTC) and moderator temperature coefficient (MTC). This paper addresses a CEA ejection accident at hot full power (HFP), in which the underlying strong and un-symmetric feedback between thermal-hydraulics and reactor kinetics exist. For this purpose, a multi-physics analysis tool has been selected with the nodal kinetics code, 3DKIN, implicitly coupled to the thermal-hydraulic code, RELAP5, for real-time communication and data exchange. This coupled approach enables high fidelity three-dimensional simulation and is therefore especially relevant to reactivity initiated accident (RIA) scenarios and power distribution anomalies with strong feedback mechanisms and/or un-symmetrical characteristics as in the CEA ejection accident. The Systems Engineering approach is employed to provide guidance in developing the work in a systematic and efficient fashion.

• Korean Circulation Journal
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• v.52 no.4
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• pp.251-264
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• 2022

Heart failure with preserved ejection fraction (HFpEF) accounts for approximately half of all heart failure (HF) cases. The prevalence of HFpEF is increasing due to an aging population with hypertension, diabetes mellitus, and obesity. HFpEF remains a challenging clinical entity due to a lack of effective treatment options. Traditional HF medications have not been shown to reduce mortality of patients with HFpEF, and an implantable cardioverter-defibrillator is not indicated due to normal ejection fraction. Sudden death is the most common mode of death in patients with HFpEF; however, the underlying mechanisms of sudden death are not fully elucidated. Although ventricular arrhythmias are responsible for the majority of sudden deaths in general, their contribution to sudden deaths in HFpEF patients is likely less significant. The mechanisms of ventricular arrhythmias in HFpEF are 1) reduced conduction velocity due to ventricular hypertrophy, 2) delayed repolarization due to potassium current down-regulation, 3) calcium leakage due to altered excitation-contraction coupling, and 4) increased ventricular fibrosis caused by systemic inflammation. Hypertension and subsequent ventricular hypertrophy reduce the conduction velocity in HFpEF hearts via heterogeneous distribution of connexin 43. Delayed repolarization caused by potassium current down-regulation in HFpEF hearts provides a window for early afterdepolarization to trigger ventricular arrhythmias. Altered excitation-contraction coupling in HFpEF can cause calcium to leak and trigger delayed afterdepolarization. Increased systemic inflammation and subsequent ventricular fibrosis provide substrates for re-entry. Further research is warranted to investigate the detailed mechanisms of ventricular arrhythmias in HFpEF.