• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.63-74
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• 2020

This study investigates the behavior of foreign investors in the Stock Exchange of Thailand (SET) in the time of coronavirus disease 2019 (COVID-19) as to whether trading is abnormal, what strategy is followed, whether herd behavior is present, and whether the actions destabilize the market. Foreign investors' trading behavior is measured by net buying volume divided by market capitalization, whereas the stock market behavior is measured by logged return on the SET index portfolio. The data are daily from Tuesday, August 28, 2018, to Monday, May 18, 2020. The study extends the conditional-regression model in an event-study framework and extracts the unobserved abnormal trading behavior using the Kalman filtering technique. It then applies vector autoregressions and impulse responses to test for the investors' chosen strategy, herd behavior, and market destabilization. The results show that foreign investors' abnormal trading volume is negative and significant. An analysis of the abnormal trading volume with stock returns reveals that foreign investors are not positive-feedback investors, but rather, they self-herd. Although foreign investors' abnormal trading does not destabilize the market, it induces stock-return volatility of a similar size to normal trade. The methodology is new; the findings are useful for researchers, local authorities, and investors.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.31-38
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• 2021

The study investigates the diversification behavior of Islamic stocks against US financial uncertainty. Considering limitations found in the literature, a comprehensive index of financial uncertainty (FU) is used, developed by Jurado, Ludvigson, and Ng (2015). The empirical analysis uses monthly data from four Islamic markets - Saudi Arabia, Malaysia, Indonesia, and Turkey - for the period from January 2010 to September 2019. Results of the bivariate EGARCH models show that Islamic stocks can be used for diversification purpose against the financial uncertainty of the US because the volatility of US uncertainty does not propagate in the Islamic stock markets. Moreover, findings show that the spillover effect of financial uncertainty varies with the FU forecast horizon. The spillover effect of FU increases with an increase in the FU forecast horizon and becomes significant over 3-month and 12-month periods in the case of Saudi Arabia. The current volatility of Islamic stock returns is independent of the size of shocks in past volatility. The leverage effect and asymmetry have been found in Saudi Arabia and Malaysia. The findings validate the arguments of the literature that Islamic markets are resilient facing uncertainties and perform well during crisis periods. The findings are important for investors in making better portfolio decisions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.297-309
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• 2021

In this study, to capture the skewness and kurtosis detected in both conditional and unconditional return distributions of the stock markets of Kazakhstan and Russia, two versions of normal mixture GARCH models are employed. The data set consists of daily observations of the Kazakhstan and Russia stock prices, and world crude oil price, covering the period from 1 June 2006 through 1 March 2021. From the empirical results, incorporating the long memory effect on the returns not only provides better descriptions of dynamic behaviors of the stock market prices but also plays a significant role in improving a better understanding of the return dynamics. In addition, normal mixture models for time-varying volatility provide a better fit to the conditional densities than the usual GARCH specifications and has an important advantage that the conditional higher moments are time-varying. This implies that the volatility skews implied by normal mixture models are more likely to exhibit the features of risk and the direction of the information flow is regime-dependent. The findings of this study contain useful information for diverse purposes of cross-border stock market players such as asset allocation, portfolio management, risk management, and market regulations.

• Asia-Pacific Journal of Business
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• v.11 no.1
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• pp.61-75
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• 2020

Purpose - The purpose of this study was to examine the efficiency of the foreign exchange markets in Korea, Japan and China. Design/methodology/approach - This study collected 1327 observations each of the daily closing exchange rates of the three currencies against the US dollar for the sample period from January 1, 2015 to January 31, 2020, based on the tests for autocorrelation, unit root tests and GARCH-M(1,1) model estimation. Findings - We have found that the autocorrelation test indicates the lack of autocorrelation and unit root test confirms the existence of unit roots in all times series of the three currencies, respectively. The GARCH-M(1,1) test results, however, suggest that the exchange rates do not follow a random walk process. In conclusion, the recent spot foreign exchange markets in Korea, Japan and China are believed to be informationally inefficient. Research implications or Originality - These findings have practical implications for both individual and institutional investors to be able to obtain excess returns on their investments in the foreign exchange markets in three countries by using appropriate risk management, portfolio strategy, technical analysis, etc. This study provides the first empirical examination on the foreign exchange market efficiency in the three biggest economies in Asia including China, which has been excluded from research due to its exchange rate regime.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.1-9
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• 2022

The study examines stock prices (LOGKSE) and exchange rate (LOGPK)-Pakistani Rupee vis-à-vis US Dollar- interactions in Pakistan. This study employs a multivariate VAR-GARCH model using monthly data from January 2012 to October 2020. The results of the Johansen cointegration test show that there is no relationship between Foreign Exchange Market and Stock Market in the long run. In the short-run, stock exchange returns are affected slightly negatively by the changes in the foreign exchange market, but the foreign exchange market does not seem to be affected by the ups and downs of the stock exchange. The VAR model and Granger Causality show that both markets are strongly influenced by their own lagged values rather than by the lagged values of one another and show weak or no correlation between the two markets. Volatility persistence is observed in both the stock and foreign exchange markets, implying that shocks and past period volatility are major drivers of future volatility in both markets. Thus greater uncertainties today will induce panic and consequently generate higher volatility in the future period. This phenomenon has been observed many times on Pakistan Stock Exchange especially. The results have important implications for local international investors in portfolio diversification decisions and risk hedging strategies.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.113-129
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• 2023

Purpose - The purpose of this study is to examine whether trading volume amplifies the extent to which lottery-type stocks are overpriced, and whether economic sentiment index explains time-variation in the magnitude of the volume amplification effect. Design/methodology/approach - We examine monthly returns on 5x5 monthly bivariate portfolios formed by lottery characteristics (measured by maximum daily return) and trading volume. In addition, we perform time-series regression tests to examine how the volume amplification effect changes in high and low economic sentiment periods, after controlling for Fama-French three factors. Findings - Our bivariate portfolio analysis shows that the overpricing of lottery-type stocks are mostly pronounced among high trading volume stocks. In contrast, for low trading volume stocks, overpricing of lottery-type stocks appears to vanish. Furthermore, the amplification effect of trading volume on overpricing of lottery-type stock is concentrated in high economic sentiment periods. Research implications or Originality - This study is the first attempt to examine whether trading volume drives lottery-type stocks' overpricing in the Korean stock market. Furthermore, our analysis unveils the time-varying nature of volume amplification effect. The results suggest that trading volume might play a important hidden role in asset pricing, opening a new line of researches in the future.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.151-180
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• 2003

We examine the interdependence of the major Asia-Pacific stock markets including S&P 500, FTSE 100, Kualar Lumpur Composite, Straits Times, Hang Seng, NIKKEI 225 and KOSPI 200 from October 4, 1995 to March 31,2000. The analysis employs the vector-auto-regression, Granger causality, impulse response function and variance decomposition using daily returns on the national stock market indices. The findings in this paper indicate that the volatilities of all countries has grown after IMF crisis, while there is no significance in cointegration test of both total period and sub-periods. This result implies that investors are able to get abnormal returns by investment diversification according to the portfolio theory. We find that while the effect from NIKKEI 225 to others is relatively weak, the interdependence from S&P 500 to other countries is strong. Also we find that the strong effect from Straits Times to Hang Seng exists. This study suggests that there is slight feedback relation between KOSPI 200 and Kualar Lumpur Composite, Straits Times, Hang Seng stock market.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.22-28
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• 2023

In this study, we conducted research on the automated trading of U.S. stocks through a volatility strategy using the Fear and Greed index. Volatility in the stock market is a common phenomenon that can lead to fluctuations in stock prices. Investors can capitalize on this volatility by implementing a strategy based on it, involving the buying and selling of stocks based on their expected level of volatility. The goal of this thesis is to investigate the effectiveness of the volatility strategy in generating profits in the stock market.This study employs a quantitative research methodology using secondary data from the stock market. The dataset comprises daily stock prices and daily volatility measures for the S&P 500 index stocks. Over a five-year period spanning from 2016 to 2020, the stocks were listed on the New York Stock Exchange (NYSE). The strategy involves purchasing stocks from the low volatility group and selling stocks from the high volatility group. The results indicate that the volatility strategy yields positive returns, with an average annual return of 9.2%, compared to the benchmark return of 7.5% for the sample period. Furthermore, the findings demonstrate that the strategy outperforms the benchmark return in four out of the five years within the sample period. Particularly noteworthy is the strategy's performance during periods of high market volatility, such as the COVID-19 pandemic in 2020, where it generated a return of 14.6%, as opposed to the benchmark return of 5.5%.

• Asia Marketing Journal
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• v.16 no.1
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• pp.21-33
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• 2014

When the negative event is published, the company tends to go through the negative impact on the firm performance. Especially, with the SNS, the negative event is instantly spread on indefinite region so the impact seems bigger than the period before the SNS media appearance. It seems that everyone considers the SNS media impact on the firm performance quite big. However, there has been no empirical study on the impact comparison on the firm performance between pre and post SNS media occurrence periods. This study tries to empirically compare the impact of the negative event on the firm performance between pre and post SNS media appearance. Our study starts fromthe basic but not verified question; Does really the negative event have more negative impact in the post-SNS-occurrence period than in the pre-SNS-occurrence period? In order to examine the impact of the negative publicity on firm performance in two eras, pre and post SNS media appearance, we used CAR (Cumulative Abnormal Resturns) model. By using this model, we could verify the statistical significance of cumulative abnormal returns in market between before and after the events. For event samples, we focused on food manufacturers and collected the negative events from 1991 to 2003 for pre-SNS occurrence period, and from 2010 to 2013 for post-SNS occurrence period. Based on the listed food companies at KOSPI, we researched Naver News Library (newslibrary.naver.com) and Naver News (news.naver.com) for all the individual negative events published for both periods. Firm returns data were collected from TS 2000 (KOCO Info) and market portfolio data were collected from KRX Exchange. Through our empirical analysis, our finding is interesting to note that the type of events differently influences on the firm performance. With the SNS, the health-related events have influence on the firm performance 'after the event day' whereas the company behavior trust events have influence 'before the event day'. Our findings have implications for management. When a negative event directly related to or threatening customers or their life such as health, it is crucial to fix up the situation right after the event occurs. On the other hand, when a negative event is not publicly available information such as company behavior trust, it is important for marketers to strengthen the firms' trust reputation and control the bad WOM before the event.

• Environmental and Resource Economics Review
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• v.22 no.4
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• pp.691-726
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• 2013

We develop a hybrid model which allows the change in electricity generation mix by adding the electricity-sector components of bottom-up model to the conventional CGE model. The electricity sector is represented as a sum of separate generation technologies, each of which has the form of DRTS (Decreasing Returns to Scale) production function, unlike the conventional CGE model. We compare the effects of the 30% emission reduction target using the hybrid model with those using the conventional CGE model. The cost of meeting the target is lower with the hybrid model than the conventional CGE. It is consistent with previous studies in that adding the bottom-up components to the top-down model reduces the cost of emission reduction. In an extra analysis we find that an additional regulation like RPS (Renewable Portfolio Standard) increases the cost.