• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.127-137
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• 2021

Mainland China area has been a long-term, major trade rival and partner of Taiwan, accounting for more than 40% of Taiwan's total annual trade exports, and so Sino-US trade friction is expected to have a significant impact on Taiwan's economy in the future. This study focuses on major bad news of Sino-US trade frictions and how it generates short-term shocks for Taiwan's equity market and fear sentiment. It further explores the mutual interpretation relationship between price changes such as VIX, Taiwan's stock market index, and the VIX ETF to identify which factors have information leadership as leading indicators. The study period covers 750 trading days from 2017/1/3 to 2020/1/31. This study finds that, when a policy news is announced, the stock market index falls significantly, the change in the trading price (net value) of the VIX ETF rises significantly, and the overprice rate significantly drops, but VIX does not, showing that fear sentiment exists in the Taiwan's market. The net value of the VIX ETF shows an information advantage as a leading indicator. This study suggests that, when the world's two largest economies clash over trade, the impact on Taiwan's equity market is inevitable, and that short-term fear effects will arise.

• 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.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.107-118
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• 2022

In this study, daily data from January 2002 to June 2022 were used to investigate the relationship between risk-return relationship and market fear, uncertainty, stock market, and maritime freight index for the crude oil market. For this study, the time varying EGARCH-M model was applied to the risk-return relationship, and the wavelet consistency model was used to analyze the relationship between market fear, uncertainty, stock market, and maritime freight index. The analysis results of this study are as follows. First, according to the results of the time-varying risk-return relationship, the crude oil market was found to be related to high returns and high risks. Second, the results of correlation and Granger causality test, it was found that there was a weak correlation between the risk-return relationship and VIX, EPU, S&P500, and BDI. In addition, it was found that there was no two-way causal relationship in the risk-return relationship with EPU and S&P500, but VIX and BDI were found to affect the risk-return relationship. Third, looking at the results of wavelet coherence, it was found that the degree of the risk-return relationship and the relationship between VIX, EPU, S&P500, and BDI was time-varying. In particular, it was found that the relationship between each other was high before and after the crisis period (financial crisis, COVID-19). And it was found to be highly associated with organs. In addition, the risk-return relationship was found to have a positive relationship with VIX and EPU, and a negative relationship with S&P500 and BDI. Therefore, market participants should be well aware of economic environmental changes when making decisions.

• Korean small business review
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• v.43 no.4
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• pp.59-93
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• 2021

This study surveyed 413 small business owners who experienced closure to see how the loss perception experienced by small business owners affects their comeback through fear of failure. The analysis results are as follows. First, the larger the received loss of financial capital, market capital, and social capital, the greater the fear of failure. Second, the greater the fear of failure, the less willingness to re-start-up, but it did not affect the willingness to work. Third, perceived loss of financial capital, market capital, and social capital grew fear of failure, which negatively affected the willingness to re-start. However, as for the willingness to work, only the perception of loss to market competitiveness strengthened the willingness to work through fear of failure. This suggests that if you think you are out of business due to market competitiveness, you are more likely to choose to get a job than to start a business. Fourth, those with higher entrepreneurial self-efficiency had less effect of perceived loss on fair of failure than those with lower entrepreneurial loss. In other words, it can be seen that a person with high entrepreneurial self-efficiency is likely to start-up. It is noteworthy that despite the tendency to fail due to market competition and lack of understanding of risks, small business operators were most aware of the loss of social capital. This is presumed to have had the greatest impact on fear of failure because small business owners try to receive funding or business revitalization support through social networks such as acquaintances and relatives. Based on the above results, this study requires sufficient market research to secure a competitive advantage when preparing for start-ups through policy practice suggestions, and suggests ways to reduce financial loss through the establishment of sophisticated business plans.

• 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%.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.84-93
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• 2021

The purpose of this study is to analyze whether the spread of COVID-19 infectious diseases acts as a fear to investors and affects the direction and volatility of stock returns. The investor fear index was proposed using the domestic confirmed patient information of COVID-19, and the influence on stock prices was empirically analyzed. The direction and volatility models of stock prices used the Granger causality and GARCH models, respectively. The results of empirical analysis using the KOSPI index from February 20, 2020 to June 30, 2021 are as follows: First, the COVID-19 fear index showed causality to future stock prices. Second, the COVID-19 fear index has a negative effect on the volatility of KOSPI index returns. In future studies, it is necessary to document the cause by using individual business performance and stock price instead of the stock index.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.87-93
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• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2771-2779
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• 2018

The recent financial crises cause the co-movement and transmit the risk across different markets and assets. It is well known that market fear affects the quality of credit in the financial markets. In this context, this study examines the co-movement between the volatility index (VIX) of the Chicago Board Options Exchange (CBOE), or VIX, and six emerging countries' credit default swaps (CDSs), by implementing wavelet coherence. Our research aims at revealing whether the VIX can be used to hedge against the bubble behavior of the CDS market in different investment holding periods (short-run, medium-run, and long-run), as well as whether either market can be used to manage and hedge overall market downside risks. The wavelet coherence results show a high degree of co-movement between the VIX and CDS during the 2007-2009 global financial crisis, across the 16-64 weeks' frequency band. In addition, we observe that the positive correlation between the VIX and the CDS markets, implying that the market turmoil intensifies the co-movement between the VIX and CDS markets.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.171-176
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• 2022

The article analyzes the impact of psychological factors on the level of loans used by investors in Vietnam's real estate market. Individual investors in the Vietnamese real estate industry were surveyed using a questionnaire. A total of 320 questionnaires were collected for the survey. The author finalized 314 questionnaires after deleting those that were invalid due to too many blank cells. SPSS 25 was used to conduct quantitative research. According to the findings, Excessive Optimism (EO) is the factor that has the highest impact on the level of loan used by investors in the Vietnamese real estate market, and this relationship is positive. With an influence level of 0.261 and 0.130, the elements of herd psychology and overconfidence also have a beneficial impact on the degree of loan used by investors in Vietnam's real estate market. Fear of loss is a factor that has a negative relationship with the level of loan utilization by investors in the Vietnamese real estate market, although, with a beta coefficient of 0.134, the degree of influence is not significant. Studies on psychological aspects and human behavior in general, and investors in particular, can help investors avoid falling into these psychological traps.

• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.51-59
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• 2019

Edge computing, which is computing on the edge of the network, is becoming a market value as a means of overcoming the fear of communication disconnection and delay reduction, which are the technical weaknesses of cloud computing. Edge computing is continuously expanding applications in various applications such as safety industry, smart factories, autonomous vehicles, mobile communications, and AR/VR. Looking at edge computing trends from Microsoft, IBM, HPE, and Dell EMC, current edge computing must be understood as an integral binding technology and not as a simple complement to the cloud. This paper examines market trends in edge computing and analyzes the impact of edge computing on major related industries.