• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.399-407
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• 2021

Stock movement is difficult to predict because it has dynamic characteristics and is influenced by many factors. Even so, there are some approaches to predict stock price movements, namely technical analysis, fundamental analysis, and sentiment analysis. Many researches have tried to predict stock price movement by utilizing these analysis techniques. However, the results obtained are varied and inconsistent depending on the variables and object used. This is because stock price movement is influenced by a variety of factors, and it is likely that those studies did not cover all of them. One of which is that no research considers the use of fundamental analysis in terms of currency exchange rates and the use of foreign stock price index movement related to the technical analysis. This research aims to predict stock price movements in Indonesia based on sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machine. The result obtained has a prediction accuracy rate of 65,33% on an average. The inclusion of currency exchange rate and foreign stock price index movement as a predictor in this research which can increase average prediction accuracy rate by 11.78% compared to the prediction without using these two variables which only results in average prediction accuracy rate of 53.55%.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.132-139
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• 2019

We address the problem about forecasting the direction of stock price movement in the Korea market. Recently, the deep neural network is popularly applied in this area of research. In deep neural network systems, proper parameter initialization reduces training time and improves the performance of the model. Therefore, in our study, we propose a novel parameter initialization technique and apply this technique for the stock price movement prediction model. Specifically, we design a framework which consists of two models: a base model and a main prediction model. The base model constructed with LSTM is trained by using the large data which is generated by a large amount of the stock data to achieve optimal parameters. The main prediction model with the same architecture as the base model uses the optimal parameter initialization. Thus, the main prediction model is trained by only using the data of the given stock. Moreover, the stock price movements can be affected by other related information in the stock market. For this reason, we conducted our research with two types of inputs. The first type is the stock features, and the second type is a combination of the stock features and the Korea Composite Stock Price Index (KOSPI) features. Empirical results conducted on the top five stocks in the KOSPI list in terms of market capitalization indicate that our approaches achieve better predictive accuracy and F1-score comparing to other baseline models.

• 한국콘텐츠학회논문지
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• 제18권9호
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• pp.623-632
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• 2018

주가 이동 방향의 정확한 예측이 주식 매매에 관한 전략적 의사결정에 중요한 역할을 할 수 있기 때문에 투자자와 연구자 모두의 관심이 높다. 주가 이동 방향에 관한 기존 연구들을 종합해보면, 주식 시장에 따라서 그리고 예측 기간에 따라서 다양한 변수가 고려되고 있음을 알 수 있다. 이 연구에서는 한국 주식 시장을 대표하는 지수와 주식들을 대상으로 이동 방향 예측 기간에 따라서 어떤 데이터마이닝 기법의 성능이 우수한 것인지를 분석하고자 하였다. 특히, 최근 공개경쟁에서 활발히 사용되며 그 우수성이 입증되고 있는 익스트림 그라디언트 부스팅 기법을 주가 이동 방향 예측 문제에 적용하고자 하였으며, SVM, 랜덤 포리스트, 인공 신경망과 같이 기존 연구에서 우수한 것으로 보고된 데이터마이닝 기법들과 비교하여 분석하였다. 12년간 데이터를 사용하여 1일 후에서 5일 후까지의 이동 방향을 예측하는 실험을 통해서, 예측 기간과 종목에 따라서 선택된 변수들에 차이가 있으며, 1-4일 후 예측에서는 익스트림 그라디언트 부스팅이 다른 기법들과 부분적으로 동등함을 가지면서도 가장 우수함을 확인하였다.

• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.107-115
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• 2020

This study is concerned with the relationship between firm's ownership structure and the co-movement of the stock return with the market return. Four different types of firm ownership, including managerial ownership, state ownership, foreign ownership, and concentrated ownership, are among the main features of the company's governance mechanism and have been separately documemented in the previous research to understand their impact on stock price synchronicity. We constructed the regression model, using stock price synchronicity as the dependent variable and the above four components of ownership structure as explanantory variables. The pooled OLS, the fixed effects model, and the random effects are employed to investigate the outcome of the study. Data used in the reserch are of public firms listed on the Ho Chi Minh City Stock Exchange (HOSE) during the five-year period term from 2015 to 2019. The data sample contains 235 companies from 10 industries with 1135 observations. The results revealed by the fixed effects model, the large ownership and the managerial ownership are found to have adverse effect on the stock price synchronicity, whereas the foreign ownership model is revealed to have positive influence on the stock return co-movement. The effect of the state ownership on the stock price synchronicity is not confirmed.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1075-1084
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• 2012

본 논문은 중국의 상해, 심천, 홍콩증권시장간의 정보이전효과를 연구한 것이다. 세 개의 중국 증권시장은 모두 미국의 증권시장수익률에 강하게 영향을 받는데 그 정도는 개방화가 제일 잘된 홍콩증권시장이 가장 크며 상해증권시장, 심천증권시장의 순으로 영향을 받는 것으로 나타나고 있다. 상해증권시장이나 심천증권시장은 서로 간에 수익률이전효과나 변동성전이효과가 존재하지 않지만 이 두 시장은 모두 홍콩증권시장수익률의 영향을 받는 것으로 나타났다. 하지만 미국증권시장의 움직임을 통제하면 이러한 효과는 사라지게 되어 중국의 증권시장간의 정보이전효과는 존재하지 않는 것으로 나타나고 있다. 이러한 결론은 중국의 세 개의 증권시장이 상호독립적인 성격이 강하다는 것을 의미하며, 중국의 증권시장 연구 시 시장 간의 독립성을 반영해야 할 것으로 생각된다.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.1113-1119
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• 2021

This study aims to determine the impact of the news coverage of the COVID-19 pandemic on the composite stocks' movement (IHSG) in Indonesia. This study used secondary data of daily time series with an observation range of March 2020-June 2020. This study used three main variables, namely, COVID-19 news, the daily price of a composite stock market index (IHSG), and interest rate. This study clarifies pandemic news into two forms to facilitate quantitative analysis, namely, good news and bad news. Both pandemic news conditions, which have been clarified, are then processed into the index and reprocessed along with two other variables using vector autoregressive (VAR). The results showed that the good news have a dominant effect on developing the composite stock price index (IHSG) in Indonesia during the COVID-19 pandemic. Although the good news dominates the composite stock price index (IHSG) movement in Indonesia, the bad news must also be anticipated. By implementing a series of macroeconomic policies that follow the conditions of the composite stock price index (IHSG) movements on the stock exchange floor, the bad news response can decrease the potential for a decline in investor confidence, so that the financial system's macroeconomic stability is maintained.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2006년도 춘계 종합학술대회 논문집
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• pp.43-46
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• 2006

본 연구는 게임 및 e-business컨텐츠 등을 중심으로 한 디지털컨텐츠업종의 주가가 해외주식시장 모멘텀에 어떻게 반응하는지를 분석하였다. 분석 결과, 국내 KOSDAQ 시장 내 디지털컨텐츠업종의 시장가치가 미국 디지털 IT 관련기업 중심의 NASDAQ시장에 유의한 (+)의 관계로 동조하는 것이 확인되었다. 따라서 국내에서 디지털컨텐츠업을 영위하는 기업이라 할지라도 자신의 시장가치가 미국 NASDAQ시장의 등락에 영향 받아 변동될 수 있음을 인지하여야 할 것이며, 나아가 그에 기초한 기업가치 관리를 행하는 것이 바람직할 것이다. 한편 일본의 대표적 주가지수인 NIKKEI225지수와의 동조화 여부를 분석한 결과, 양자간의 유의한 인과관계는 발견되지 않았다. 이는 NIKKEI225지수가 디지털 IT기업을 중심으로 구성된 지수가 아님에 따른 결과로 이해되었으며, 따라서 일본시장과 관련한 디지털컨텐츠 기업 시장가치 변동을 이해하는데 있어서는 NIKKEI225 지수 동향에만 의존하여서는 안 될 것이라는 시사점이 도출되었다.

• 한국콘텐츠학회논문지
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• 제6권8호
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• pp.78-85
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• 2006

본 연구는 게임 및 e-business 컨텐츠 등을 중심으로 한 디지털컨텐츠업종의 주가가 해외주식시장 모멘텀에 어떻게 반응하는지를 분석하였다 이를 위하여 디지털컨텐츠 관련 기업의 상장과 거래가 이루어진 1999년부터 최근에 이르는 기간 동안의 KOSDAQ시장 디지털컨텐츠업종 지수를 대상으로 미국 NASDAQ 지수 및 일본 NIKKEI225지수와의 주가동조화를 분석하였다. 분석 결과, 국내 KOSDAQ시장내 디지털컨텐츠업종의 시장가치가 미국 디지털 IT 관련기업 중심의 NASDAQ시장에 유의한 (+)의 관계로 동조하는 것이 확인되었다. 따라서 국내에서 디지털컨텐츠업을 영위하는 기업이라 할지라도 자신의 시장가치가 미국 NASDAQ 시장의 등락에 영향 받아 변동될 수 있음을 인지하여야 할 것이며, 나아가 그에 기초한 기업가치 관리를 행하는 것이 바람직할 것이다. 한편 일본의 대표적 주가지수인 NIKKEI225 지수와의 동조화 여부를 분석한 결과, 양자간의 유의한 인과관계는 발견되지 않았다. 이는 NIKKEI225 지수가 디지털 IT 기업을 중심으로 구성된 지수가 아님에 따른 결과로 이해되었으며, 따라서 일본시장과 관련한 디지털컨텐츠기업 시장가치 변동을 이해하는데 있어서는 NIKKEI225 지수 동향에만 의존하여서는 안 될 것이라는 시사점이 도출되었다.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.139-147
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• 2020

This paper aims to explore the relationship between the quality of the audit and the level of stock return co-movement in the context of the Vietnamese emerging market. The empirical study is designed based on the quatitative method and deductive approach. The panel dataset includes 256 listed firms from different industries,with 1115 firm-year observations on Ho Chi Minh City Stock Exchange for the period from 2014 to 2018. In the research, we built the econometric regression model, using stock return synchronicity and audit quality as the dependent and independent variable, respectively. Some control variables are also added to the econometric regression models as they are well-documented in prior research to have an effect on stock price synchronicity. To improve the accuracy of the regression coefficients, beside the Ordinary Least Squares, we employ the Random Effects Model and the Fixed Effects Model for better statistical analysis of panel data set. The results show that the quality of the audit is positively correlated to stock price synchronicity. This finding suggests that stock returns of companies with higher quality of the audit are more synchronous with the market. Results for other control variables also support our reasoning for the main findings.

• Journal of Korea Trade
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• 제27권5호
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• pp.167-198
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• 2023

Purpose - This paper aims to compare and analyze the co-movements and information spillover effects between the international commodity futures markets and the South Korean stock markets during the COVID-19 and the 2008 financial crises. Design/methodology - The DCC-GARCH model is used in the co-movements analysis. In contrast, the BEKK-GARCH model is used to evaluate information spillover effects. The statistical data used is from January 1, 2005, to December 31, 2022. It comprises the Korea Composite Stock Price Index data and daily international commodity futures prices of natural gas, West Texas Intermediate crude oil, gold, silver, copper, nickel, soybean, and wheat. Findings - The results of the co-movement analysis were as follows: First, it was shown that the co-movements between the international commodity futures markets and the South Korean stock markets were temporarily strengthened when the COVID-19 and 2008 financial crises occurred. Second, the South Korean stock markets were shown to have high correlations with the copper, nickel, and crude oil futures markets. The results of the information spillover effects analysis are as follows: First, before the 2008 financial crisis, four commodity futures markets (natural gas, gold, copper, and wheat) were shown to be in two-way leading relationships with the South Korean stock markets. In contrast, seven commodity futures markets, except for the natural gas futures market, were shown to be in two-way leading relationships with the South Korean stock markets after the financial crisis. Second, before the COVID-19 crisis, most international commodity futures markets, excluding natural gas and crude oil future markets, were shown to have led the South Korean stock markets in one direction. Third, it was revealed that after the COVID-19 crisis, the connections between the South Korean stock markets and the international commodity futures markets, except for natural gas, crude oil, and gold, were completely severed. Originality/value - Useful information for portfolio strategy establishment can be provided to investors through the results of this study. In addition, it is judged that financial policy authorities can utilize the results as data for efficient regulation of the financial market and policy establishment.