• Asia pacific journal of information systems
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• 제24권2호
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.913-921
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• 2021

The objective of the study is to investigate the impact of the COVID-19 pandemic on Saudi Arabia stock market. The study relied on the data of the daily closing stock market price index Tadawul All Share Index (TASI), and the number of daily cases infected with COVID-19 during the period from March 15, 2020, to August 10, 2020. The study employs the Vector Auto-Regressive (VAR) model, the Impulse Response Function (IRF) and Autoregressive Conditional Heteroscedasticity (ARCH) models. The results of the correlation matrix and the Impulse Response Function (IRF) show that stock market returns responded negatively to the growth in COVID-19 infected cases during the pandemic. The results of ARCH model confirmed the negative impact of COVID-19 pandemic on KSA stock market returns. The results also showed that the negative market reaction was strong during the early days of the COVID-19 pandemic. The study concluded that stock market in KSA responded quickly to the COVID-19 pandemic; the response varies over time according to the stage of the pandemic. However, the Saudi government's response time and size of the stimulus package have played an important role in alleviating the impacts of the COVID-19 pandemic on Saudi Arabia Stock Market.

• 경영과정보연구
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• 제38권3호
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• pp.1-19
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• 2019

이 연구에서는 시장의 상황에 따라 이질적으로 나타나는 유가변동성지수(Oil Volatility Index : OVX)가 주식시장에 미치는 효과를 분위수회귀모형을 이용하여 분석하였다. 특히 전체적인 주식시장뿐만 아니라 산업별로 상이하게 나타나는 효과를 분석하기 위하여 2007년 5월부터 2019년 2월까지의 종합주가지수(KOSPI)와 함께 22개 산업별 주가지수 수익률을 사용하였다. 이와 함께 유가변동성지수의 변화율이 증가하는 경우와 감소하는 경우를 구분하여 강세와 약세 시장에서 산업별 주가지수에 미치는 영향을 분석하였다. 그 결과, 각 산업별 주식시장이 약세일 때 유가변동성지수가 미치는 음의 효과가 상대적으로 강하게 나타났으며, 이러한 효과는 강세시장으로 갈수록 사라지는 것을 확인할 수 있었다. 또한 해당 산업의 주식시장이 약세일 때 유가변동성의 증가는 12개 산업에서 통계적으로 유의한 강한 음의 효과를 주는 것으로 나타났으며, 이와는 달리 강세 시장에서는 섬유의복, 기계, 서비스업에서 통계적으로 유의한 양의 효과를 주는 것으로 나타났다. 특히 강세 시장에서 유가변동성 증가가 감소하는 경우 제조업을 포함한 12개 산업에서 주가 수익률에 통계적으로 유의한 음의 효과를 주는 것으로 나타났다. 결과를 통하여 부정적인 소식에 상대적으로 더욱 민감하게 반응하는 주식시장의 특징이 약세시장에서 더욱 명확하게 나타난다는 것을 확인하였다.

• 동아시아경상학회지
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• 제4권4호
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• pp.1-7
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• 2016

This paper has studied the impacts of the exchange rate, government debt as a percent of GDP and other relevant macroeconomic variables on aggregate output in the Philippines. A simultaneous-equation model consisting of aggregate demand and short-run aggregate supply is applied. The dummy variable technique is employed to detect whether the slope and intercept of the real effective exchange rate may have changed. Real depreciation during 1998.Q1 - 2006.Q3, real appreciation during 2006.Q4 - 2016.Q1, a lower domestic debt as a percent of GDP, a lower real interest rate, a higher stock price or a higher lagged real oil price would raise aggregate output. Recent trends of real peso appreciation, declining domestic debt as a percent of GDP, lower real interest rates, and rising stock prices are in line with the empirical results and would promote economic growth. The authorities may need to continue to pursue fiscal prudence and maintain a stronger peso as the positive effect of real appreciation dominates its negative effect in recent years.

• 통상정보연구
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• 제7권4호
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• pp.325-349
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• 2005

One aspect of the globalization of the financial market after the 1980s is represented by the concurrent monetarization of the national stock markets. As the IR activity is regarded as a new financial productivity measure, the IR activity in the stock market is being emphasized domestically and internationally. This study analyzes domestic IR activities and compares them with foreign IR activities. Specifically the "road show", a typical IR activity, which is known to resolve the information asymmetry between the firm and the investors is analyzed to see the extent of the their value increase impact on the firm. The study employs domestic and international firms that publicly announced "road shows" after April 2004. Event studies are done to see the existence of abnormal return after the public announcement of road shows. Domestic firms were found to have positive IR impacts on the stock prices, but international firms were found to have negative IR impacts on the stock prices. Also it was found that international public announcement of the road show have stronger positive impact on the stock price than domestic public announcement. The investigation of the statistically significant difference of CAR before and after the fair public announcement enforcement rule showed that the positive CAR impact is strengthened after the adoption of the rule. The conclusion is that increase of the firm value after the road show implies that the information asymmetry is reduced by the active IR actions on the firm side. The policy implication is that we have to reassure the understanding of the role of the IR activities. Specifically Korean firms may have to encourage IR activities to share the information of the firms with the investors, which may result in the trustworthy relationship between the firms and investors.

• Asian Journal of Business Environment
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• 제7권4호
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• pp.5-9
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• 2017

Purpose - Many countries rely on currency depreciation or debt-financed government spending to stimulate their economies. Currency depreciation tends to increase net exports and aggregate demand but reduce short-run aggregate supply due to higher import costs. Debt-financed government spending increases aggregate demand, but the crowding-out effect due to a higher real interest rate may reduce private spending and aggregate demand. Therefore, the net impact of currency depreciation or debt-financed government spending on equilibrium real GDP is unclear. Research design, data, and methodology - This paper examines potential impacts of real depreciation of the ringgit, more government debt as a percent of GDP and other relevant macroeconomic variables on aggregate output in Malaysia. Results - Applying the AD/AS model, this paper finds that aggregate output in Malaysia is positively associated with real appreciation during 2005.Q3-2010.Q3, real depreciation during 2010.Q4-2016.Q1, the debt-to-GDP ratio and the real stock price, negatively affected by the real lending rate and inflation expectations, and is not influenced by the real oil price. Conclusions - Real depreciation of the ringgit after 2010. Q3 or sustainable expansionary fiscal policy would be beneficial to the economy.

• 지능정보연구
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• 제21권4호
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• pp.37-51
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• 2015

인터넷 기술의 발전과 인터넷 상 데이터의 급속한 증가로 인해 데이터의 활용 목적에 적합한 분석방안 연구들이 활발히 진행되고 있다. 최근에는 텍스트 마이닝 기법의 활용에 대한 연구들이 이루어지고 있으며, 특히 문서 내 텍스트를 기반으로 문장이나 어휘의 긍정, 부정과 같은 극성 분포에 따라 의견을 스코어링(scoring)하는 감성분석과 관련된 연구들도 다수 이루어지고 있다. 이러한 연구의 연장선상에서, 본 연구는 인터넷 상의 특정 기업에 대한 뉴스 데이터를 수집하여 이들의 감성분석을 실시함으로써 주가의 등락에 대한 예측을 시도하였다. 개별 기업의 뉴스 정보는 해당 기업의 주가에 영향을 미치는 요인으로, 적절한 데이터 분석을 통해 주가 변동 예측에 유용하게 활용될 수 있을 것으로 기대된다. 따라서 본 연구에서는 개별 기업의 온라인 뉴스 데이터에 대한 감성분석을 바탕으로 개별 기업의 주가 변화 예측을 꾀하였다. 이를 위해, KOSPI200의 상위 종목들을 분석 대상으로 선정하여 국내 대표적 검색 포털 서비스인 네이버에서 약 2년간 발생된 개별 기업의 뉴스 데이터를 수집 분석하였다. 기업별 경영 활동 영역에 따라 기업 온라인 뉴스에 나타나는 어휘의 상이함을 고려하여 각 개별 기업의 어휘사전을 구축하여 분석에 활용함으로써 감성분석의 성능 향상을 도모하였다. 분석결과, 기업별 일간 주가 등락여부에 대한 예측 정확도는 상이했으며 평균적으로 약 56%의 예측률을 보였다. 산업 구분에 따른 주가 예측 정확도를 통하여 '에너지/화학', '생활소비재', '경기소비재'의 산업군이 상대적으로 높은 주가 예측 정확도를 보임을 확인하였으며, '정보기술'과 '조선/운송' 산업군은 주가 예측 정확도가 낮은 것으로 확인되었다. 본 논문은 온라인 뉴스 정보를 활용한 기업의 어휘사전 구축을 통해 개별 기업의 주가 등락 예측에 대한 분석을 수행하였으며, 향후 감성사전 구축 시 불필요한 어휘가 추가되는 문제점을 보완한 연구 수행을 통하여 주가 예측 정확도를 높이는 방안을 모색할 수 있을 것이다.

• 재무관리연구
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• 제25권3호
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• pp.79-109
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• 2008

비대칭적정보(Asymmetric Information)에 근거한 정보가설에 의하면 (Ross, 1977; Myers and Majluf, 1984 등), 유상증자 공시가 기업가치에 미치는 효과는 결국 정보의 효율성에 달려있음을 강조하고 있다. 그럼에도 불구하고 지금까지 진행된 국내 유상증자 관련 연구들은 대부분 유상증자를 공시한 모든 기업을 하나의 샘플로 분석함으로서 모든 기업들의 정보효율성이 동일하다는 가정 하에서 연구가 이루어졌다. 본 연구는 이러한 문제인식 아래 2000년 1월 1일부터 2005년 12월 31일까지 유상증자를 공시했던 국내 122개 기업들을 정보효율성에 따라 분류하여 다양한 기간별로 유상증자 공시효과를 분석하였다. 유상증자를 공시한 모든 기업을 대상으로 분석한 결과는 대다수의 국내선행연구들과 마찬가지로 유상증자 공시시점의 주가상승과 공시직후의 주가하락으로 나타났다. 그러나 정보효율성 고려시 상대적으로 효율성이 높을 것으로 여겨지는 KOSPI200에 속하는 기업은 평균적으로 공시시점에 주가가 하락하고 공시직후엔 오히려 주가가 상승하는 모습을 보인 반면 기타의 KOSPI 기업의 경우는 전체기업 분석결과와 마찬가지로 공시시점에 주가상승과 공시직후의 주가하락을 보여 상반된 주가 움직임을 보이고 있는 것으로 나타났다. 유상증자공시가 장 단기적으로 주가에 악영향을 미친다는 미국시장에서의 연구들과는 달리 한국의 경우는 공시시점까지는 주가가 상승하고, 공시직 후 및 장기적으로는 주가가 하락한다는 상이한 연구결과가 주를 이루었는데 이러한 차를 그간 제도상의 차이로 설명하였다. 그러나 본 연구에서는 유상증자공시 기업을 정보효율성에 따라 개략적으로나마 구분함으로써 공시시점의 유상증자효과가 기존의 국내 연구들과 반대로, 국내시장보다 좀 더 효율적일 것으로 여겨지는 미국시장에서의 분석과 동일한 결과를 도출함으로써, 이러한 상이한 유상증자효과가 제도상의 차이뿐만 아니라 시장효율성의 차에 기인할 수 있음을 발견하였다.

• Journal of Information Technology Applications and Management
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• 제21권1호
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• pp.177-184
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• 2014

This research analyzes the effects of factors on the demands for outbound to the countries such as Japan, China, the United States of America, Thailand, Philippines, Hong Kong, Singapore and Australia, the countries preferred by many Koreans. The factors for this research are (1) economic variables such as Korea Composite Stock Price Index (KOSPI), which could have influences on outbound tourism and exchange rate and (2) unpredictable events such as diseases, financial crisis and terrors. Regression analysis was used to identify relationship based on the monthly data from January 2001 to December 2010. The results of the analysis show that both exchange rate and KOSPI have impacts on the demands for outbound travel. In the case of travels to the United States of America and Philippines, Korean tourists usually have particular purposes such as studying, visiting relatives, playing golf or honeymoon, thus they are less influenced by the exchange rate. Moreover, Korean tourists tend not to visit particular locations for some time when shock reaction happens. As the demands for outbound travels are different from country to country accompanied by economic variables and shock variables, differentiated measure to should be considered to come close to the target numbers of tourists by switching as well as creating the demands. For further study we plan to build outbound tourism forecasting models using Artificial Neural Networks.