• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.15-22
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• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.165-176
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• 2021

The paper has used the Solow-Swan growth model to analyze the long-term impact of credit market development and stock market development on economic growth in Asia from 2000 to 2019. The empirical model is performed with panel cointegration analysis by Common Correlated Effects (CCE) method with cross-sectional dependencies. The results find that there exists a cointegration relationship among stock market, credit market development, and economic growth. These results also show that financial structure improves the exact impact of financial development on economic growth, namely the opposite effect of stock market development and credit market development. Moreover, the Granger causality test reveals a bi-directional relationship between credit market development and economic growth, while only unidirectional causality from stock market development to economic growth for the whole group panel. And it is different for a specific country, according to Kónya's test. The view of the new structuralism does not apply in the Asian financial system when we estimate the Nonlinear Autoregressive Distributed Lag model (NARDL) to analyze the asymmetric relationship between financial structure and economic growth. On the whole, policymakers can draw on the findings to provide policy implications to improve their country's financial system as well as pursue the goal of sustainable economic growth.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.759-770
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• 2021

Using a DCC - GARCH model analysis, this paper examines the existence of financial contagion from the U.S. stock market to the Vietnamese and the Philippine stock markets during the global financial crisis and the COVID-19 pandemic crisis. We use daily data from the S&P 500 (U.S.), VN-Index (Vietnam), and the PSEi (the Philippines). As a result, there is no evidence of contagion from the U.S stock market to the Philippine stock market that can be found during global financial crisis, while the Vietnamese market is influenced by this effect. Besides, both these developing stock markets (the Vietnamese and Philippine stock markets) are influenced by the contagion effect in COVID-19 pandemic crisis. Another finding is that the contagion effect during the coronavirus pandemic crisis in Vietnam is smaller than that during the global financial crisis, however, the opposite is the case for the Philippines. It is noticed that the Philippines seems to be more affected by the contagion effect from the COVID-19 pandemic than Vietnam at the time of this study. Because financial contagion is important for monetary policy, asset pricing, risk measurement, and portfolio allocation, the findings in this paper may give some useful information for policymakers and investors.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.125-134
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• 2020

This study examines the nominal price anomaly in the Vietnamese stock market, that is, whether stocks with low nominal price outperform stocks with high nominal price. Using a sample of all 351 companies listed on the Ho Chi Minh Stock Exchange (HOSE) from June 2009 to March 2018, we confirm our hypothesis and document that cheaper stocks yield higher subsequent abnormal returns. The results are robust after controlling for various stock characteristics that have been documented to be value-relevant in prior literature, including firm size, book-to-market ratio, intermediate-term momentum, short-term reversal, skewness, market risk, idiosyncratic risk, illiquidity and extreme daily returns, using both the portfolio analysis and the Fama-MacBeth cross-sectional regression. The negative effect persists in the long term (i.e., after up to 12 months), implying a slow adjustment of stock prices to their intrinsic value. Further analysis show that the observed nominal price anomaly is mainly driven by mispricing but not a latent risk factor proxied by stock price, thus the observed anomaly reflects a mispricing but not a fundamental risk. The study highlights the irrational behaviour of investors and market inefficiency in the Vietnamese stock market and provides important implication for investors in the market.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.185-197
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• 2018

Measuring market fear is an important way of understanding fundamental economic phenomena related to financial crises. There have been several approaches to measure market fear or panic level in a financial market. Recently, herd behavior has gained its popularity as important economic phenomena explaining the fear in the financial market. In this paper, we investigate herd behavior in global stock markets with a focus on intercontinental comparison. While various risk measures are available for the detection of herd behavior in the market, we use the standardized herd behavior index in Dhaene et al. (Insurance: Mathematics and Economics, 50, 357-370, 2012b) and Lee and Ahn (Dependence Modeling, 5, 316-329, 2017) for the comparison of herd behaviors in global stock markets. A global stock market data from Morgan Stanley Capital International is used to study herd behavior especially during periods of financial crises.

• International Area Studies Review
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• v.18 no.3
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• pp.67-88
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• 2014

The Chinese stock market has increasingly strengthened its market power on other stock markets due to rapid growth of its economy. In this context, this study investigated return spillover effect as well as asymmetric volatility spillover effect using a VAR-Bivariate EGARCH model among stock markets(China, US, Japan, Korea). Furthermore, we conjectured the impact of 2008 global financial crisis on the spillover effect of the Chinese stock market. In our empirical results, the Chinese stock market has a weak return spillover effect to other markets(US, Japan, Korea), but after the global financial crisis, its return spillover effect becomes stronger among other stock markets. In addition, the Chinese stock market have strengthened its asymmetric volatility spillover effect on other stock markets after the Global financial crisis. As a result, the Chinese stock market has an strong influence on other stock markets.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Distribution Science
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• v.13 no.9
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• pp.37-45
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• 2015

Purpose - This paper's aim is to investigate whether or not gross profitability explains the cross-sectional variation of the stock returns in the Korean stock market. Gross profitability is an alternative profitability measure proposed by Novy-Marx in 2013 to predict cross-sectional variation of stock returns in the US. He shows that the gross profitability adds explanatory power to the Fama-French 3 factor model. Interestingly, gross profitability is negatively correlated with the book-to-market ratio. By confirming the gross profitability premium in the Korean stock market, we may provide some implications regarding the well-known value premium. In addition, our empirical results may provide opportunities for the fund distribution industry to promote brand new styles of funds. Research design, data, and methodology - For our empirical analysis, we collect monthly market prices of all the companies listed on the Korea Composite Stock Price Index (KOSPI) of the Korea Exchanges (KRX). Our sample period covers July1994 to December2014. The data from the company financial statementsare provided by the financial information company WISEfn. First, using Fama-Macbeth cross-sectional regression, we investigate the relation between gross profitability and stock return performance. For robustness in analyzing the performance of the gross profitability strategy, we consider value weighted portfolio returns as well as equally weighted portfolio returns. Next, using Fama-French 3 factor models, we examine whether or not the gross profitability strategy generates excess returns when firmsize and the book-to-market ratio are controlled. Finally, we analyze the effect of firm size and the book-to-market ratio on the gross profitability strategy. Results - First, through the Fama-MacBeth cross-sectional regression, we show that gross profitability has almost the same explanatory power as the book-to-market ratio in explaining the cross-sectional variation of the Korean stock market. Second, we find evidence that gross profitability is a statistically significant variable for explaining cross-sectional stock returns when the size and the value effect are controlled. Third, we show that gross profitability, which is positively correlated with stock returns and firm size, is negatively correlated with the book-to-market ratio. From the perspective of portfolio management, our results imply that since the gross profitability strategy is a distinctive growth strategy, value strategies can be improved by hedging with the gross profitability strategy. Conclusions - Our empirical results confirm the existence of a gross profitability premium in the Korean stock market. From the perspective of the fund distribution industry, the gross profitability portfolio is worthy of attention. Since the value strategy portfolio returns are negatively correlated with the gross profitability strategy portfolio returns, by mixing both portfolios, investors could be better off without additional risk. However, the profitable firms are dissimilar from the value firms (high book-to-market ratio firms); therefore, an alternative factor model including gross profitability may help us understand the economic implications of the well-known anomalies such as value premium, momentum, and low volatility. We reserve these topics for future research.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.833-843
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• 2021

This research examines the impact of audit quality on the extent to which firm-specific information is integrated with a firm's share price - which is determined inversely using stock price synchronicity. The study sample consists of non-financial companies listed on the Amman Stock Exchange i.e., the Jordanian Stock Market, from 2014-2018. After examining 810 firm-year observations from Jordanian industrial companies listed on the ASE, during the study period, we find that the companies using one of the BIG4 audit firms for auditing have less synchronous and more informative stock prices, suggesting high-quality audit improved governance and reduce information asymmetry between firms' insiders and investors which enhances the capitalization of firm's specific information into the stock price, thus less synchronous and more informative stock return. The findings remain consistent over 2 separate measurements of stock price synchronicity (Market and Industry model and Market Model) and show robustness for fixed effect tests. Our multivariate regression results are also robust after controlling for a number of features at the firm level with potential associations with stock price synchronicity. These include the firm size, leverage, return on assets (ROA), and market to book value (MBV).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.11-19
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• 2021

The study aims to investigate the impact of seasonality in Gulf Cooperation Council (GCC) countries' share market during the month of Ramadan. It helps in finding the opportunities for stock market investors to earn abnormal (returns) gain by investing during Ramadan in GCC stock markets. This study uses stock returns data of GCC countries (Saudi Arabia, Bahrain, Qatar, Kuwait, Dubai, and UAE) from January 2004 to November 2019. Stock prices indexes of GCC stock markets have been obtained from Datastream. The ARCH-GARCH model is used to study the impact of the Ramadan month on the return and volatility of the stock market in GCC countries. The results showed that the Ramadan month has a significant impact on share market prices in Saudi Arabia and the United Arab Emirates. However, Ramadan has an insignificant impact on share market prices in Bahrain and Oman. The study found no evidence of serial correlational between residuals in Kuwait; meaning that stock return was not dependent on the prior stock returns in Kuwait, therefore, we cannot go for forecasting. The ARCH-LM test statistic for Qatar does not fulfill the requirement of a good regression model; therefore, we cannot go for forecasting or testing the hypothesis of Qatar.