• Title/Summary/Keyword: stock market index

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The Empirical Study of Variation of KOSPI Index & Macro Economic Variation (거시경제 변수 변화와 KOSPI 지수 변동의 연관성 분석)

  • An, Chang-Ho;Choi, Chang-Yeoul
    • International Commerce and Information Review
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    • v.12 no.4
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    • pp.171-192
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    • 2010
  • In general, a stock index and its individual stocks are assumed to follow a random walk. A stock index is an important source of information and one that is seen by people everyday, regardless of their investment intentions. This paper examines the correlation between the KOSPI-the index that best reflects the Korean stock market and the macro - economic variables that have been found to influence the index by previous studies. The sample period considers the years after 2000 when the Korean stock market matured as restrictions on foreign investors were removed. For this purpose, a Vector Error Correction Model (VECM) and KOSPI equation with a general pacific approach were used. This paper aims at verifying the factors that determined the KOSPI after 2000 and at examining whether there was structural change in the investment environment. It also investigates changes in the factors determining the KOSPI's performance as a result of structural changes in the investment environment. The V AR (Vector Autoregressive) model including the nine variables was selected as a baseline model whose stability was tested using the unit root test. The results from the VECM and the structural changes in the investment environment can be summarized by the following Inner story points.

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COVID-19 Pandemic and the Reaction of Asian Stock Markets: Empirical Evidence from Saudi Arabia

  • SHAIK, Abdul Rahman
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.12
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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.

ANALYZING CONTENTS OF MARKET SENTIMENT BASED ON INVESTERS' EMOTION

  • Lee, Sanggi;Song, Joonhyuk
    • The Pure and Applied Mathematics
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    • v.24 no.4
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    • pp.227-241
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    • 2017
  • The study investigates the stock market using emotion index calculated from SMD based on investors' emotion. In the VAR anlaysis, we find that the correlation between the KOSPI200 return and emotion score sum is highest in 2- or 3- day lag. This study concludes that explanatory power of the SMD emotion index is limited in explaining the Korean stock market yet.

The Contagion Effect from U.S. Stock Market to the Vietnamese and the Philippine Stock Markets: The Evidence of DCC - GARCH Model

  • LE, Thao Phan Thi Dieu;TRAN, Hieu Luong Minh
    • 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.

Hedging Transaction in the Stock Index Futures (주가지수선물의 헤징거래)

  • 윤석곤
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.4
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    • pp.139-144
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    • 1998
  • Introduced into korea to diversify risk coming from the fluctuation of stock price with opening of the domestic capital market to foreigners, Suppress the turbulence of the dentistic securities market caused by the short term funds from foreign countries and vitalize investment in stock, the hedging transaction of stock index futures will promote the introduction of financial futures and commodity futures transaction. and it will contribute to enhancing the introduction all over the country and accelerating the advancement of the korea banking market. In addition, it is expected to make a great contribution to economic stability and smooth comic activity through its function of risk diversification and price decrement with the launch of the stock index futures.

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Two-Stage forecasting Using Change-Point Detection and Artificial Neural Networks for Stock Price Index

  • Oh, Kyong-Joo;Kim, Kyoung-Jae;Ingoo Han
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.11a
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    • pp.427-436
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    • 2000
  • The prediction of stock price index is a very difficult problem because of the complexity of the stock market data it data. It has been studied by a number of researchers since they strong1y affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain Intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network (BPN). Fina1ly, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

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Investment Strategies for KOSPI Index Using Big Data Trends of Financial Market (금융시장의 빅데이터 트렌드를 이용한 주가지수 투자 전략)

  • Shin, Hyun Joon;Ra, Hyunwoo
    • Korean Management Science Review
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    • v.32 no.3
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    • pp.91-103
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    • 2015
  • This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.

A study on the Co-movement of Stock Market between Digital Contents Industry in Korea and Foreign Market (디지털컨텐츠산업의 해외주식시장 동조화 연구)

  • Wi, Han-Jong
    • Proceedings of the Korea Contents Association Conference
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    • 2006.05a
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    • pp.43-46
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    • 2006
  • This study examined the stock return co-movement among Korean digital contents industry, American NASDAQ, and Japanese NIKKEI225. This is to identify the reaction of Korean digital contents industry on the movement of foreign stock market. To investigate the co-movements, during the period of 1999 to 2005, daily logarithm difference returns of each stock market indices are tested by the methodology of Granger(1963, 1969)'s causality test. The positive influence from NASDAQ index to Korean digital contents industry index are found, but not vice versa. It means that the market value of firms in Korean digital contents industry affected by the movement of American NASDAQ market which composite with digital IT firms. However, the co-movements with NIKKEI225 did not found.

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An Empirical Study on the Validity of the Availability Huristics and Anchoring Huristics in the Korean Stock Market (한국주식시장에서 가용성 어림짐작과 닻내림 어림짐작의 유효성에 관한 실증연구)

  • Sam-Ho Son;Jeong-Hwan Lee;Se-Jun Lee
    • Asia-Pacific Journal of Business
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    • v.14 no.1
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    • pp.265-279
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    • 2023
  • Purpose - The purpose of this paper is to compare and review behavioral economics models that explain stock price changes after large-scale price shocks in the Korean stock market and to find a suitable model. In this paper, among the theories reviewed, it was confirmed that the anchoring heuristics theory has high explanatory power for stock prices after large-scale stock price fluctuations. Design/methodology/approach - This paper conducts an event study on stock price shocks in which the individual stocks that make up the KOSPI200 index show more than 10% fluctuation on a daily basis. In order to materialize the abstract predictions of heuristics theories in a varifiable form, this paper uses the daily stock price index change as a reference point for availability heuristics, and uses the 52-week highest and lowest price as reference point for anchoring heuristics. Research implications or Originality - As a result of the empirical analysis, the stock price reversals did not consistently appear for changes in the daily index. On the other hand, the stock price drifts consistently appeared around the 52-week highest and the 52-week lowest price. And in the multiple regression analysis that controlled for company-specific and event-specific variables, the results that supported the anchoring heuristics were more evident. These results suggest that it is possible to establish an investment strategy using large-scale price change in Korean stock market.

System Dynamics Approach for the Forecasting KOSPI (시스템다이내믹스를 활용한 종합 주가지수 예측 모델 연구)

  • Cho, Kang-Rae;Jeong, Kwan-Yong
    • Korean System Dynamics Review
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    • v.8 no.2
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    • pp.175-190
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    • 2007
  • Stock market volatility largely depends on firms' value and growth opportunities. However, with the globalization of world economy, the effect of the synchronization in major countries is gaining its importance. Also, domestically, the business cycle and cash market of the country are additional factors needed to be considered. The main purpose of this research is to attest the application and usefulness of System Dynamics as a general stock market forecasting tool. Throughout this research, System Dynamics suggests a conceptual model for forecasting a KOSPI(Korea Composite Stock Price Index), taking the factors of the composite stock price indexes in traditional researches. In conclusion of this research, System Dynamics was proved to bean appropriate model for forecasting the volatility and direction of a stock market as a whole. With its timely adaptability, System Dynamic overcomes the limit of traditional statistic models.

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