• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.523-531
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• 2021

Vietnam's Oil and gas industry make a significant contribution to the Gross Domestic Product of Vietnam. The ongoing COVID-19 pandemic has hit every industry hard, but perhaps the one industry which has taken the biggest hit is the global oil and gas industry. The purpose of this article is to examine how the COVID-19 pandemic affects the share price of the Vietnam Oil and Gas industry. The event study method applied to Oil and Gas industry index data around three event days includes: (i) The date Vietnam recognized the first patient to be COVID-19 positive was January 23, 2020; (ii) The second outbreak of COVID-19 infection in the community began on March 6, 2020; (iii) The date (30/3/2020) when Vietnam announced the COVID-19 epidemic in the whole territory. This study found that the share price of the Vietnam Oil and Gas industry responded positively after the event (iii) which is manifested by the cumulative abnormal return of CAR (0; 3] = 3.8% and statistically significant at 5 %. In the study, event (ii) has the most negative and strong impact on Oil and Gas stock prices. Events (i) favor negative effects, events (iii) favor positive effects, but abnormal return change sign quickly from positive to negative after the event date and statistically significant shows the change on investors' psychology.

• The Journal of Asian Finance, Economics and Business
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• 제8권4호
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• pp.601-611
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• 2021

There are many asset prices which are interlinked and have a bearing on the stock market index. Studies have shown that the interrelationship among these asset prices vary and are inconsistent. The ultimate aim of this study is to examine the dynamic relationship between gold price, oil price, exchange rate and stock index. Monthly time series data has been utilized by the researcher to examine the interrelationship between four variables. The relationship among stock exchange rate index, oil price and gold price have been undertaken using regression and granger causality test. The results indicate that the exchange rate and oil price have an indirect influence on NIFTY; whereas gold price had a direct impact on NIFTY. It is evident from the results that volatility in the price of gold is mainly dependent on the exchange rate and vice versa. All the variables affect NIFTY in some way or the other. However, gold has a direct and vital relationship. From the study findings, it can be concluded that macroeconomic variables like commodity prices and foreign exchange rate, gold and oil, have a strong relationship on the return on securities at the national stock exchange of India.

• The Journal of Asian Finance, Economics and Business
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• 제8권12호
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• pp.1-7
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• 2021

The study examines the influence of COVID-19 on the stock market returns of Saudi Arabia. The data was analyzed through event study methodology using daily price data of Tadawul All Share Index (TASI). The study examines the behavior pattern of the Saudi Arabian stock market in different phases during the event period by selecting six-event windows with a range of 10 days. The results report a negative Abnormal Return (AR) of -0.003 on the event date, while the abnormal returns reversed the next day to 0.005 positively. The result of Cumulative Abnormal Return (CAR) is negative and significant at the 1 percent level in all the six-event windows starting from the event date to day 59 after the event for the TASI index. Even though the influence of the COVID-19 pandemic decreased after 30 days of the event date, it increased during the last ten days of the event window. The stock market volatility of Saudi Arabia increased during the post-event period compared to the pre-event period with a negative mean return of -0.326 and a greater standard deviation. In a conclusion, the study found a significant influence of the COVID-19 pandemic on the stock market returns of TASI.

• 재무관리연구
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• 제24권4호
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• pp.75-106
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• 2007

본 연구는 유가요인이 업종별 주식수익률 결정요인으로 작용하는 지 여부와 유가요인과의 공분산 리스크가 업종별로 차이가 나는 원인에 관해서 분석하였다. 첫째, 업종별로 주식의 기대수익률이 유가요인에 대한 리스크프리미엄의 함수로 결정되는 지 여부를 분석하기 위한 검증모형으로 시장 포트폴리오, 국제유가요인으로 구성된 Two-factor APT를 사용하였다. 또한, 베타리스크에 영향을 주는 유가변동률 분산의 주식 수익률로의 전이현상도 함께 살펴보았다. 유가변동성의 비대칭성을 감안하여 GJR을 해당분석의 검증모형으로 사용하였다. 분석결과 전기 전자업종에서 유가요인은 독립적인 가격결정요인임이 입증되었고, 동업종에서만 유가변동성의 주식수익률로의 전이효과가 통계적으로 유의한 것으로 나타났다. 둘째, 유가요인과의 공분산 리스크가 업종별로 차이가 나는 원인을 분석하기 위해 두가지 분석과정이 고려되었다. 첫 번째로 규모 및 유동성을 나타내는 대리변수를 통제변수로 고려하여 업종별로 유가요인에 대한 베타리스크 존재여부를 확인하였다. 두 번째로 유동성 및 규모의 차이와 유가요인에 대한 베타와의 관계를 체계적으로 규명하고자 시계열로 구성된 횡단면 자료간의 관련성을 효율적으로 분석할 수 있는 Panel-data model을 이용하였다. 분석결과 시가총액 비중이 큰 전기 전자업종에서만 유가요인이 독립적 가격결정요인임이 확인되었고, 여타 업종에서 유가요인에 대한 베타리스크는 규모에 영향을 받는 것으로 나타났다. 또한, 패널분석결과 전체 포트폴리오에서 차지하는 업종별 시가총액의 비중이 클수록 유가요인에 대한 베타는 증가하는 것으로 나타나 첫 번째 분석과정의 결과를 지지하였다. 결론적으로 국내주식시장에서 전기 전자업의 기대수익률은 시장포트폴리오와 국제유가요인에 대한 리스크프리미엄의 함수로 결정되고 있으며, 유가요인에 대한 베타리스크 수준이 업종별로 차이가 나는 원인은 규모의 차이에 기인하는 것으로 분석된다.

• 국제지역연구
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• 제20권3호
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• pp.123-144
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• 2016

This paper investigates the linkages between returns both in foreign exchange and stock markets, and uncertainties in two markets using daily data for the period of 16 July 2004 to 30 June 2014 in Nepalese economy. Four hypotheses are tested about how uncertainty influences the stock index and exchange rates. From the empirical results, a bivariate EGARCH-M model is the best to explain the volatility in the two markets. There is a negative relationship from the exchange rates return to stock price return. Empirical results do provide strong empirical confirmation that negative effect of stock index uncertainty and positive effect of exchange rates uncertainty on average stock index. GARCH-in-mean variables in AR modeling are significant and shows that there is positive effect of exchange rates uncertainty and negative effect of stock index uncertainty on average exchange rates. Stock index shocks have longer lived effects on uncertainty in the stock market than exchange rates shock have on uncertainly in the foreign exchange market. The effect of the last period's shock, volatility is more sensitive to its own lagged values.

• 아태비즈니스연구
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• 제11권2호
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• pp.189-206
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• 2020

Purpose - The purpose of this study is to clarify the mediating effect of profitability and activity in the relationship between productivity and stock return, assuming that the productivity of the company will affect share prices with the parameters of profitability and activity. Design/methodology/approach - The study extracted productivity indicators, profitability indicators, activity indicators, and share price-related indicators from 1999 to 2018 of non-financial enterprises listed on the securities market, and then classified them into three factors: productivity (labor productivity LP, capital productivity CP), activity (TT), and profitability (net profit rate NI, operating profit ratio OI) through the factor analysis method, and analyzed the impact of each factor on the stock return through steps 1 to 3. Findings - The regression analysis shows that productivity has a significant positive effect on the stock return through the full mediating effect of profitability and activity. Research implications or Originality - In a situation where the relationship between productivity and profitability is not clear, this study is meaningful in that it has empirically analyzed that productivity has a positive effect on the stock return by mediating effects of profitability and activity.

• The Journal of Asian Finance, Economics and Business
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• 제9권1호
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• pp.143-152
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• 2022

This paper examines the relationship between investor sentiment and the risk of a stock price crash at the firm level. Our dataset includes 131 firms listed on the Saudi stock exchange (Tadawul) from 2011 to 2019, as well as 953 firm-year observations. To evaluate crash risk, we employ two distinct proxies and propose an index for measuring firm-level sentiment which we use for the first time in our study. The average turnover rate, price-earnings ratio, and overnight return are the three sentiment proxies we utilize in our index. Our findings show that high levels of investor emotion increase managers' proclivity to withhold unfavorable news from investors, which aggravates the risk of a stock price crash. We undertake cross-sectional regressions by sector to ensure the robustness of our findings, and our findings are confirmed. After accounting for any endogeneity issues with the GMM technique, the results remain the same. Furthermore, we analyze the liquidity effect by dividing our sample into subsamples with better and worse liquidity and find that firms with worse liquidity have a considerably greater positive impact of investor mood. Overall, our findings help investors and regulators recognize the significance of this downside risk and how to manage it in the stock market.

• Asia pacific journal of information systems
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• 제30권1호
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• Asian Journal of Business Environment
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• 제11권4호
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• pp.17-29
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• 2021

Purpose: The aim of this study is to explore the dynamic linkage between conditional stock market volatility and macroeconomic uncertainty of Bangladesh. Research design, data, and methodology: This study uses monthly data covering the time period from January 2005 to December 2018. A comprehensive set of macroeconomic variables, namely industrial production index (IP), consumer price index (CPI), broad money supply (M2), 91-day treasury bill rate (TB), treasury bond yield (GB), exchange rate (EX), inflow of foreign remittance (RT) and stock market index of DSEX are used for analysis. Symmetric and asymmetric univariate GARCH family of models and multivariate VAR model, along with block exogeneity and impulse response functions, are implemented on conditional volatility series to discover the possible interactions and causal relations between macroeconomic forces and stock return. Results: The analysis of the study exhibits time-varying volatility and volatility persistence in all the variables of interest. Moreover, the asymmetric effect is found significant in the stock return and most of the growth series of macroeconomic fundamentals. Results from the multivariate VAR model indicate that only short-term interest rate significantly influence the stock market volatility, while conditional stock return volatility is significant in explaining the volatility of industrial production, inflation, and treasury bill rate. Conclusion: The findings suggest an increasing interdependence between the money market and equity market as well as the macroeconomic fundamentals of Bangladesh.

• 한국전자거래학회지
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• 제22권2호
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• pp.153-168
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• 2017

최근 주식의 수익률과 거래량을 설명하는 요인 중 하나로 투자자들의 관심이나 주식관련 정보 전파의 효율성 등이 중요하게 인식되고 있다. 또한 기업관련 정보가 투자자들에게 투명하게 전파되지 않을 때 기업 주가의 급락(crash) 위험을 증가시킨다는 연구 결과들이 축적되고 있다. 본 연구에서는 네이버 트렌드를 이용하여 포털에서의 검색 강도가 증가하는 것이 주식 수익률의 급락에 어떤 영향을 미치는지를 분석하였다. 다양한 주가급락 위험의 측정변수와 검색 강도 측정치를 이용한 분석에서 포털 검색강도가 상대적으로 높은 기업-연도에서 주가 급락의 위험이 감소하는 것으로 관찰되었다. 이러한 결과는 기업 관련 정보 전파가 투자자들에게 효율적으로 이루어지지 않을 때 미래의 주가급락을 초래한다는 논의와 일치하는 결과이다. 또한 이러한 결과는 분석에 발생가능한 내생성을 통제한 후에도 유의하게 성립하는 것으로 관찰되었다.