• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.111-117
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• 1992

In the stock marketing. investor needs speedy and accurate decision making for the investment. A stock exchange index provides the important index of the early of 1993 in Korea using Fuzzy Delphi Method(F. D. M) which is widely used to a mid and long range forecasting in decision making problem. In the Fuzzy Delphi method, considerably qualified experts an first requested to give their opinion seperately and without intercommunication. The forecasting data of experts consist of Triangular Fuzzy Number (T.F.N) which represents the pessimistic, moderate, and optimistic forecast of a stock exchange index. A statistical analysis and dissemblance index are then made of these subject data. These new information are then transmitted to the experts once again, and the process of reestimation is continued until the process converges to a reasonable stable forecast of stock exchange index. The goal of this research is to forecast the stock exchange index using F.D.M. in which subjective data of experts are transformed into quasi -objective data index by some statistical analysis and fuzzy operations. (a) A long range forecasting problem must be considered as an uncertain but not random problem. The direct use of fuzzy numbers and fuzzy methods seems to be more compatible and well suited. (b) The experts use their individual competency and subjectivity and this is the very reason why we propose the use of fuzzy concepts. (c) If you ask an expert the following question: Consider the forecasting of the price index of stocks in the near future. This experts wi11 certainly be more comfortable giving an answer to this question using three types of values: the maximum value, the proper value, and the minimum value rather than an answer in terms of the probability.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.19-26
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• 2019

The paper aims to measure stock price volatility on Ho Chi Minh stock exchange (HSX). We apply symmetric models (GARCH, GARCH-M) and asymmetry (EGARCH and TGARCH) to measure stock price volatility on HSX. We used time series data including the daily closed price of VN-Index during 1/03/2001-1/03/2019 with 4375 observations. The results show that GARCH (1,1) and EGARCH (1,1) models are the most suitable models to measure both symmetry and asymmetry volatility level of VN-Index. The study also provides evidence for the existence of asymmetric effects (leverage) through the parameters of TGARCH model (1,1), showing that positive shocks have a significant effect on the conditional variance (volatility). This result implies that the volatility of stock returns has a big impact on future market movements under the impact of shocks, while asymmetric volatility increase market risk, thus increase the attractiveness of the stock market. The research results are useful reference information to help investors in forecasting the expected profit rate of the HSX, and also the risks along with market fluctuations in order to take appropriate adjust to the portfolios. From this study's results, we can see risk prediction models such as GARCH can be better used in risk forecasting especially.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.2
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• pp.19-23
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• 2017

It is undisputable that crude oil and its price fluctuations are major components that affect most of the countries' economies. Recent studies have demonstrated that beside the impact that crude oil price fluctuations have on common macroeconomic indicators like gross domestic product (GDP), inflation rates, exchange rates, unemployment rate, etc., it also has a strong influence on stock markets and their performance. This relationship has been examined in a number of settings, but it is yet to be unraveled in the Omani context. Accordingly, the main purpose of this study is to examine the possible effect of the oil price fluctuations on stock price movements. The study applies Toda and Yamamoto's (1995) Granger non-causality test on the daily Oman stock index (Muscat Securities Market Index) and oil prices between the period of 2 January 2003 and 13 March 2016. The results indicated that the oil price fluctuations have a significant impact on stock index movements. However, the stock price movements do not have a significant impact on oil prices. These findings have significant implications not only for the Omani economy but also for the economy of similar countries, particularly in the Gulf Cooperation Council (GCC) countries. The latter should carefully consider their policies and strategies regarding crude oil production and the generated income allocation as it might potentially affect the financial markets performance in these countries.

• The Journal of Industrial Distribution & Business
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• v.4 no.2
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• pp.13-19
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• 2013

Purpose - The paper tested the relationship between the stock markets of the Middle East and the USA with the oil price and US dollar index as threshold variables. Research design, data, and methodology - The stock price indices of the USA, the Middle East (Abu Dhabi, Jordan), WTI spot crude oil price, and US dollar index were daily returns in the research period from May 21, 2001 to August 9, 2012. Following Hansen (1999), the panel threshold regression model was used. Results - With the US dollar index as the threshold variable, a negative relationship existed between the stock price indices of Jordan and the USA but no significant result was found between the stock price indices of Abu Dhabi and the USA. Conclusions - The USA is an economic power today:even if it has a closer relationship with the US stock market, the dynamic US economy can learn about subsequent developments and plan in advance. Conversely, if it has an estranged relationship with the US stock market, thinking in a different direction and different investment strategies will achieve good results.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1-9
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• 2021

UAE has rapidly developed into one of the leading global financial hubs, with significant transformations in its stock exchanges. In its attempt at economic diversification in the last two decades, the country has also taken a lead in the GCC region in introducing extensive reforms to attract FDI to the Emirates. However, oil price volatilities have posed a significant challenge to all oil-exporting countries. The main aim of this study is to explore the impact of economic diversification and oil price on the UAE stock market. The study applies Granger Causality and Vector Autoregressive Model on monthly Abu Dhabi stock exchange index, Dubai Fateh crude oil spot price, and FDI inflows during 2001-19. The short-term interbank rate has been included as a monetary policy variable. The results show a substantial difference between the two phases of reforms. Oil price and Abu Dhabi stock index show bidirectional relationship during 2001-09 but no causality was found during 2010-19. Furthermore, the second phase was characterized by unidirectional causation from FDI to ADX index. This study highlights FDI inflows as a key driver of stock market performance during the last decade and emphasizes the success of the intense reforms in the UAE initiated for the diversification of its economy.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.43-51
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• 2018

We study the impact of economic policy uncertainty (EPU) of Asian four countries such as Korea, Japan, Hong Kong, and China on housing market returns in Korea. Also, we document the relationship between the EPU index of those four countries and the housing market including macroeconomic indicators in Korea. The EPU index of those four countries has significantly a negative effect on the housing purchase price index, housing lease price index in Korea. The EPU index in Korea and Japan has significantly a negative effect on the CPI. The EPU index in only Japan has significantly a negative effect on the PPI. The EPU index in Hong Kong and Korea has significantly a negative effect but the EPU index in China significantly has a positive effect on the stock price index in construction industry. The EPU index in only Korea has significantly a negative effect the stock price index in banking industry. This study shows the EPU index of the Korea has the negative relationships on the housing market economy rather than other countries by VECM. And this study has an important evidence of the spillover of several macroeconomic indicators in Korea for the EPU index of the Asian four countries.

• Journal of Distribution Science
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• v.21 no.9
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• pp.103-114
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• 2023

Purpose: This paper aims to assess psychological heuristics' effectiveness on cumulative returns after significant stock price changes. Specifically, it compares availability and anchoring heuristics' empirical validity due to conflicting stock return predictions. Research Design, Data, and Methodology: This paper analyzes stock price changes of Korean distribution industry stocks in the KOSPI market from January 2004 to July 2022, where daily fluctuations exceed 10%. It evaluates availability heuristics using daily KOSPI index changes and tests anchoring heuristics using 52-week high and low stock prices as reference points. Results: As a result of the empirical analysis, stock price reversals did not consistently appear alongside changes in the daily KOSPI index. By contrast, stock price drifts consistently appeared around the 52-week highest stock price and 52-week lowest stock price. The result of the multiple regression analysis which controlled for both company-specific and event-specific variables supported the anchoring heuristics. Conclusions: For stocks related to the Korean distribution industry in the KOSPI market, the anchoring heuristics theory provides a consistent explanation for stock returns after large-scale stock price fluctuations that initially appear to be random movements.

• Journal of Distribution Science
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• v.15 no.12
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• pp.41-51
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• 2017

Purpose - This study proposes the impact of the US and Korean economic policy uncertainty on macroeconomy, and its effect on Korea. The economic policy uncertainty index of the US and Korea is used to represent the economic policy uncertainty on Korean economy. Research design, data, and methodology - In this paper, we collect the eight variables to find out the interrelationship among the US and Korean economic policy uncertainty index of the US and macroeconomic indicators during 1990 to 2016, and use Vector Error Correction Model. Result - The distribution industry stock index in Korea is influenced by the economic policy uncertainty index of the US rather than of Korea. All variables are related negatively to the economic policy uncertainty index of the US and Korea from Vector Error Correction Model. This study shows that the economic policy uncertainty index of the US and Korea has the dynamic relationships on the Korean economy. Conclusions - A higher economic policy uncertainty shows a greater economy recession of a country. Finally, the economic policy uncertainty of the Korea has an intensive impact on Korea economy. Particularly, the economic policy uncertainty of the US has a strong impact on distribution industry stock market in Korea.

• Management & Information Systems Review
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• v.38 no.3
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• pp.1-19
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• 2019

This paper investigates the asymmetric effects of crude oil price uncertainty on industrial stock returns under different market conditions (bearish and bullish stock markets). We consider a quantile regression method using monthly oil volatility index, KOSPI and 22 industrial stock indices from May 2007 to February 2019. Especially, we take care of the positive and negative changes of the oil volatility index to analyze asymmetric effects of the oil price uncertainty for the bearish and bullish stock market conditions. During the bearish markets, the oil volatility index has relatively strong statistically significant negative effects on the industrial stock returns. These effects gradually decrease when the market conditions became more bullish markets. In particular, positive changes in the oil volatility index yields a further significant decrease in 12 industrial stock returns during the extreme bearish markets. Moreover, during the bullish markets, negative changes in the oil volatility index have statistically significant negative effects on the 12 industrial stock returns. From the empirical results, we see that participants of the Korean stock market are sensitive to bad news in a recession.