본 연구는 국제원유시장과 아시아 주식시장(한국, 중국, 일본, 인도, 인도네시아, 필리핀, 말레이시아, 태국, 대만, 싱가포르, 베트남)간의 상관관계를 국면전환 관점에서 분석한다. 이를 위해 유가와 주가지수 간의 시간가 변 상관계수를 DCC-GARCH(1,1) 모형으로 추정하였고, 비선형 시계열 분석기법인 Smooth Transition Regression(STR) 모형을 활용해 구조적 변화의 비선형 특성과 상관관계의 강도를 파악하였다. 2002년 1월부 터 2016년 3월까지의 자료를 토대로 한 분석 결과, 국제유가와 아시아 주가지수간의 상관관계는 시간의 흐름에 따라 그리고 국가별로 상이한 움직임을 나타냈다. 또한 상관관계의 국면간 전환점과 전환속도를 측정하는 모수가 일부 국가에서 유의하게 추정되었다. 이러한 결과는 원유와 아시아 국가 주식으로 포트폴리오를 구성할 경우 상 관계수의 추정과정에서 비선형성과 강도를 고려해야 할 필요가 있음을 시사한다. 이에 본 논문은 방법론적으로 기존의 국제재무 문헌의 확장에 기여하며 주식시장과 원유시장의 관계자들에게도 포트폴리오 구성 및 시장예측과 관련한 실무적 시사점도 제공한다.

본 논문은 1991년 4월부터 2013년 9월까지의 중국의 상해, 심천 및 홍콩주식시장의 주간 지수자료를 이용하여 중국대륙의 두 시장과 홍콩 시장간 수익률 상호연관성의 정도를 분석하였다. 특히 1997년 7월 1일 에 있었던 홍콩의 중국반환 이전과 이후를 구분하여 비교하였는데, 상 관분석, 그랜저인과분석 및 GARCH(1,1)모형을 이용한 분석결과는 상해 와 심천주식시장은 모든 기간에 걸쳐 상호연관성이 강하게 나타났으며, 홍콩주식시장과 중국본토의 주식시장 간에는 홍콩반환 이전에는 상호연 관성이 없는 움직임을 보였으나 홍콩반환 이후에는 상해주식시장과 심 천주식시장이 홍콩시장에 상당한 영향을 끼쳤으며, 홍콩시장 또한 상해 주식시장과 심천주식시장에 영향을 준 것으로 나타났다. 한편 상해 및 심천주식시장은 홍콩시장에 비해 시장의 충격에 아주 민감하게 반응을 보였으며, 충격 후 회복도 빠른 것으로 나타났다. 결론적으로 홍콩의 반 환이전부터 상당한 상호연관성을 보인 중국본토의 두 주식시장은 반환 이후에는 홍콩주식시장과 동조화현상을 보여주고 있음을 알 수 있다.

The purpose of the article is to evaluate the factors that affect the degree of environmental accounting information disclosure. Data are collected from 87 industry companies listed on the Vietnamese stock market from 2009 to 2019. I focus on the effect of factors such as the Firm size, Profitability, Leverage, Firm age, and Independent auditors. To explain the causal relationship between factors, I construct the regression model and then test it by using different statistical method approaches, including the pooled OLS, the fixed effects model, and the random effects model. Then I conduct testing of model defects: White Test, Wooldridge Test, Hausman Test, and Wald Test. The Feasible Generalized Least Squares (FGLS) method is used to analyze the image factors that affect environmental accounting information disclosure. The results show that the extent of environmental accounting information disclosure is influenced by factors: firm size, uptime and independent audit. These factors positively affect the level of environmental accounting information disclosure; independent audit has the greatest influence. Based on the research results, the author gives recommendations to improve the disclosure of environmental accounting information for industrial enterprises listed on the Vietnamese stock market, increasing the competitiveness of the public company in terms of global integration.

We apply Return Dispersion Model by calculating CSAD (Cross-sectional standard deviation of return) and State Space Model to identify herding behavior in the period of pandemic (H1N1 and COVID-19). Employing data from TEJ and Data Stream, this paper examines whether the herding behavior is existing in Vietnam and Taiwan stock market, especially during pandemic influenza. We compare the differences in herding behavior between frontier and emerging markets by examining different industries across Vietnam and Taiwan stock market approaches. The results indicate solid evidence for investor herd configuration in the various industries of Vietnam and Taiwan. The herding impact in the industries will be greater than with the aggregate market. The different industries respond differently to influenza pandemic panics through uptrend and downtrend demonstrations. Up to 12 industries were found to have herding in Vietnam, while Taiwan had only 5 of 17 industries classified. Taiwan market, an emerging and herding-level market, has changed due to the impact of changing conditions such as epidemics, but not as strongly as in Vietnam. From there, we see that the disease is a factor that, not only creates anxiety from a health perspective, but also causes psychological instability for investors when investing in the market.

In financial economics studies, the autoregressive model has been a workhorse for a long time. However, the model has a fixed value on every parameter and requires the stationarity assumptions. Time-varying coefficient autoregressive model that we use in this paper offers some desirable benefits over the traditional model such as the parameters are allowed to be varied over-time and can be applies to nonstationary financial data. This paper provides the Monte Carlo simulation studies which show that the model can capture the dynamic movement of parameters very well, even though, there are some sudden changes or jumps. For the daily data from January 1, 2015 to February 12, 2020, our paper provides the empirical studies that Thailand, Taiwan and Tokyo Stock market Index can be explained very well by the time-varying coefficient autoregressive model with lag order one while South Korea’s stock index can be explained by the model with lag order three. We show that the model can unveil the non-linear shape of the estimated mean. We employ GJR-GARCH in the condition variance equation and found the evidences that the negative shocks have more impact on market’s volatility than the positive shock in the case of South Korea and Tokyo.

The study examines lagged economic effects of research and development (R&D) investment on the market value of manufacturing firms listed on the Shanghai Stock Exchange or the Shenzhen Stock Exchange in China. This study applies panel data analysis methods to address the following issues: 1) There might be an adjustment lag in the impact of R&D investment on corporate market value, and 2) Unobserved firm effects must be taken into account. The balanced panel data includes a total of 1,462 observations with 34 cross-sections of manufacturing firms listed on Chinese stock markets and with 27 time-specific quarterly periods from 2007 to 2017. The results indicate that the R&D investment of Chinese manufacturing firms tends to yield favorable market value of the firm with some adjustments to time. The results show that R&D investment exhibits a strong positive impact on their market value of manufacturing firms in Chinese stock markets. Moreover, R&D investment has a positive time-lag effect on the market value of the firm. Interestingly, the R&D investment of Chinese manufacturing firms generate a relatively constant positive effect on their market value, supporting the notion that the corresponding returns of R&D investment for such firms yield lagged but added market values.

This study aims to investigate the impact of COVID-19 pandemic on the stock markets of sixteen countries. Pooled OLS regression, conventional t-test and Mann-Whitney test are used to estimate the results of the study. We construct a weekly panel data of COVID-19 new cases and stock returns. Pooled OLS estimation result shows that the growth rate of weekly new cases of COVID-19 negatively predicts the return in stock market. Next, the returns on leading stock indices of these countries during the COVID-19 outbreak period are compared with returns during the non-COVID period. We use a t-test and Mann-Whitney test to compare the returns. The results reveal that investors in these countries do not react to the media news of COVID-19 at the early stage of the pandemic. However, once the human-to-human transmissibility had been confirmed, all of the stock market indices negatively reacted to the news in the short- and long-event window. Interestingly, we noticed that the Shanghai Composite Index, which was severely affected during the short-event window, bounced back during the long-event window. This indicates that the Chinese government’s drastic measures to contain the spread of the pandemic regained the confidence of investors in the Shanghai Stock Market.

The study examines the impact of corporate social responsibility (CSR) activity on the firm market value, in particular, market capitalization of tour operators listed on Chinese stock markets. This study employs panel data analysis methods to examine endogeneity concerns in observational data. The balanced panel data includes a total of 1,296 observations with 27 cross-sections of tour operators listed on Chinese stock markets and with 48 time-specific periods from March 2006 to December 2017. The results indicate that CSR activity has a negative impact on the market value of the firm for the concurrent period, but from one-period time lag and afterwards CSR activity has a strong positive impact on the market value and sustains its positive impact on the market value even for a two-period time lag. The findings suggest that the economic effect of CSR activity on the firm market value tends to take some degree of lagged effects to be fully showcased in the market capitalization of tour operators and travel companies listed on Chinese stock markets. The findings suggest that, though CSR activity may carry some financial risk for an immediate short-term, tour operators must put a lot of time and effort into making CSR actions effective.

The research aims to study the relationship between export performance and stock return of Vietnamese fishery companies. To conduct this study, quarterly data was collected for period from 2010-2018 of 13 fishery companies listing in Ho Chi Minh Stock Exchange (HOSE) and Ha Noi Stock Exchange (HNX). The export performance was measured by export intensity, export growth and export market coverage. In addition, interest rate, exchange rate, GDP, firm size, profitability, and financial leverage were considered as the control variables in the research model. Panel data analysis with Generalized Least Squares model was employed to estimate the predictive regression. The findings indicated that export intensity and export growth have a significant and positive relationship with stock returns. However, export market coverage has not a significant relationship with stock return at the 0.05 level. Profitability, financial leverage, and exchange rate have a positive relationship, while interest rate and GDP have no relation to stock return at the 0.05 significance level. The findings imply that investors should consider the export intensity instead of export growth and export market coverage as selecting stock of fishery exports firms to invest; managers should increase export intensity to increase company’s stock price or firm market value.

This paper empirically examines the short-run and long-run causal relationship between stock market prices and exchange rates in Chinese stock markets using monthly data from January 2002 to December 2012 retrieved from the National Bureau of Statistics of the People’s Republic of China. Unit root, cointegration tests, vector error correction estimates, block exogeneity Wald tests, impulse responses, variance decomposition techniques and structural break tests are employed. This study found 1) long-run causality from exchange rates to stock prices in Chinese stock markets and 2) short-run causality from Japanese yen and Korean won exchange rates to stock prices in the Shanghai Stock Exchange strongly prevails while in the Shenzhen Stock Exchange weakly prevails . The impact of the global financial crisis from 2007 to 2009 on Chinese stock markets was insignificant.