• The Journal of Asian Finance, Economics and Business
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• 제8권7호
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• pp.365-373
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• 2021

This paper investigates the presence of momentum profits in the Saudi stock market. The study applied a quantitative method by utilizing monthly closing prices of 194 listed firms on Tadawal (Saudi Stock Market). The data from January 2010 to February 2019 is taken from the Tadawal market database for analysis. The sample is further divided into two equal sub-samples based on the structural changes that occurred in the Saudi stock market. Moreover, the high- and low-value traded portfolios are also constructed to examine the presence of momentum profits. Sixteen investment strategies are formed for each sample. The results show a very strong presence of momentum profits in the Saudi stock market for the full sample as well as for the sub-samples. The momentum profits are observed for a longer investment horizon. The results confirm that the short or medium-term formation of portfolios produces negative momentum returns for high-value traded stocks. The low-value traded stocks portfolios give similar results to the full sample results in terms of momentum profits. The results suggest that an investor should keep an eye on the past performance of desired stocks for at least three-nine months in which they are willing to invest.

• 한국컴퓨터정보학회논문지
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• 제20권7호
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• pp.85-90
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• 2015

This study surveyed 152 publicly traded companies to investigate group-performance based pay practices and its impacts on labor productivity. Compared a benchmark survey from Department of Labor, those companies show higher introduction rates, especially in small-to-medium sized companies. They also tend to pay profit-sharing bonus more in the form of company stocks and differentiate individual bonuses more by department performance than individual performance. The impact of group-performance based pay on labor productivity is positive and statistically significant. Economic value added per person in those companies adopting group-performance based pay tends to be higher and increases with the coverage of employees under the pay plan. It also reveals that the years after the play adoption are negatively associated with labor productivity.

• 한국융합학회논문지
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• 제6권4호
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• pp.127-132
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• 2015

본 연구는 한국 주식시장에서 가치투자 전략과 연계해 모멘텀 투자전략의 유효성을 분석하였다. 본 연구는 2001년~2014년 동안 한국 주식시장의 상장기업의 주가 및 재무자료를 실증 분석해, 과거 승자 주를 매수하고 패자 주를 매도하는 모멘텀 투자전략과 장부가/시가 비율이 높은 가치주를 매수하고 장부가/시가 비율이 낮은 글래머주를 매도하는 가치 투자전략의 유효성이 기간별로 서로 다르며, 전체 분석기간에 걸쳐 역(-)의 상관관계가 있음을 관찰하였다. 또한 Fama and French[1]가 개발한 3 요인 회귀분석 모형을 추정해, 모형의 절편이 유의적인 양(+)의 값으로 추정됨을 관찰함으로써, 역(-)의 상관관계로 인해 상호 대체관계에 있는 모멘텀 투자전략과 가치 투자전략을 하나의 시스템으로 분석할 때, 모멘텀 투자전략이 세계 주요 증권시장에서와 마찬가지로 한국 증권시장에서도 유효함을 분석하였다.

• 산업경영시스템학회지
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• 제46권1호
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• pp.105-111
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• 2023

Recently, research on prediction algorithms using deep learning has been actively conducted. In addition, algorithmic trading (auto-trading) based on predictive power of artificial intelligence is also becoming one of the main investment methods in stock trading field, building its own history. Since the possibility of human error is blocked at source and traded mechanically according to the conditions, it is likely to be more profitable than humans in the long run. In particular, for the virtual currency market at least for now, unlike stocks, it is not possible to evaluate the intrinsic value of each cryptocurrencies. So it is far effective to approach them with technical analysis and cryptocurrency market might be the field that the performance of algorithmic trading can be maximized. Currently, the most commonly used artificial intelligence method for financial time series data analysis and forecasting is Long short-term memory(LSTM). However, even t4he LSTM also has deficiencies which constrain its widespread use. Therefore, many improvements are needed in the design of forecasting and investment algorithms in order to increase its utilization in actual investment situations. Meanwhile, Prophet, an artificial intelligence algorithm developed by Facebook (META) in 2017, is used to predict stock and cryptocurrency prices with high prediction accuracy. In particular, it is evaluated that Prophet predicts the price of virtual currencies better than that of stocks. In this study, we aim to show Prophet's virtual currency price prediction accuracy is higher than existing deep learning-based time series prediction method. In addition, we execute mock investment with Prophet predicted value. Evaluating the final value at the end of the investment, most of tested coins exceeded the initial investment recording a positive profit. In future research, we continue to test other coins to determine whether there is a significant difference in the predictive power by coin and therefore can establish investment strategies.

• 한국IT서비스학회지
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• 제17권1호
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• pp.33-45
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• 2018

Recently, many South Korean firms have suffered financial losses and damaged corporate images from the data breaches. Accordingly, a firm should manage their IT assets securely through an information security investment. However, the difficulty of measuring the return on an information security investment is one of the critical obstacles for firms in making such investment decisions. There have been a number of studies on the effect of IT investment so far, but there are few researches on information security investment. In this paper, based on a sample of 76 investment announcements of firms whose stocks are publicly traded in the South Korea's stock market between 2001 and 2017, we examines the market reaction to information security investment by using event study methodology. The results of the main effects indicate that self-developed is significantly related to cumulative average abnormal returns (CAARs), while no significant effect was observed for discloser, investment characteristics and firm characteristics. In addition, we find that the market reacts more favorably to the news announced by the subject of investment than the vendor, in case of investments with commercial exploitation. One of main contributions in our study is that it has revealed the factors affecting the market reaction to announcement of information security investment. It is also expected that, in practice, corporate executives will be able to help make an information security investment decision.

• 마케팅과학연구
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• 제20권1호
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• pp.80-88
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• 2010

相当多的调查目的是为了证明股东资产值和一些市场战略之间的关系. 之前的研究包括关于股票价格表现和广告之间的关系, 顾客服务学, 新产品介绍, 研究与开发, 名人转让, 品牌感知, 品牌价值评估, 公司名称变化, 以及运动相关的赞助者地位. 另一个据调查可以对股东资产值产生影响的因素是内含特殊体育事件的电视广告, 例如超级杯. 调查指出以超级杯为题材做了广告的公司股票价值都有所提升. 报告给出广告投资和股东价值提升之间的关系, 作为既普通又特殊的事件, 令人吃惊的是调查关注的奥林匹克运动会的相关广告投资以及之后的效果对股东价值的影响效果较小. 然而调查结果显示奥林匹克运动会的主办地却备受关注, 另外所受关注的是赛事的电视广播进行期间广告的财政稳固. 著名的包括Peters (2008), Pfanner (2008), Saini (2008), and KellerFay Group (2009). 这篇论文提出了有关在2000, 2004以及2008年夏季奥林匹克运动会期间在美国国家广播中进行过电视广告宣传的客户的研究.以下为所验证的五个假设: 假设一: 2008, 2004和2000年在美国电视广播中播放奥运广告的公司股票价格在同期比斯坦普500股票价格指数表现要好. 假设二: 奥运相关股票价格比斯坦普500股票价格指数在整个广告播放期间都表现的更好, 播放期间是指从奥运开始前的周一到当年年底. 假设三: 奥运相关股票价格比斯坦普500股票价格指数长期都表现的更好, 长期是指从奥运开始前的周一第二年的年中. 假设四: 在没有奥运会的期间, 奥运相关股票价格和斯坦普500股票价格指数间没有明显差异. 假设五: 在美国电视广播中播放奥运广告的公司的当年年报比其他非奥运年份要好. 本研究记录在过去三届奥运会期间做广告公司的股票价格(北京奥运, 雅典好运, 悉尼奥运). 我们通过Google和电视网络(例如NBC)来确定这些广告. NBC在过去的三届奥运会获得了在美国转播权. 我们使用互联网来确定这些做过广告的品牌的母公司. 股票价格是通过使用Yahoo财经频道来获得的. 本文所使用的所有的信息都是被公开的信息. 总共有117个奥运广告在2008, 2004和2000年在美国播放. 细节可以从图例1中获得. 结果表明这些奥运相关股票在奥运期间以及奥运前期比斯坦普500股票价格指数表现要好. 相同的结果也可以在奥运开始以后到当年年底, 以及之后半年的记录中获得. 价格压力, 信号理论, 高收视率, 以及企业的刺激战略都对这一个结果有着贡献. 论文最后为广告商和研究者提出了建议并对以后的研究提出了方向.

• 지능정보연구
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• 제17권3호
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• pp.187-201
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• 2011

방향성(Direction)과 변동성(Volatility)에 대한 분석은 증권투자를 위한 시장분석의 기초가 된다. 변동성분석이 옵션 투자에서 중요하다면 주식이나 주가지수선물투자는 방향성분석에 의하여 투자성과가 결정된다. 기존의 금융분석에서 기계학습을 이용한 방향성에 대한 연구는 주가나 투자위험의 예측을 중심으로 이루어졌으며, 최근에 와서야 실전투자를 위한 매매시스템(trading system) 개발에 대한 연구가 이루어지고 있다. 인공지능형 주가예측모형에서는 ANN(artificial neural networks), fuzzy system, SVM(Support Vector Machine) 등의 기법이 주로 활용되고 있다. 본 연구에서는 방향성매매를 위한 지능형 기계학습방법 중에서도 패턴인식에서 좋은 성과를 보이고 있는 은닉마코프 모형(Hidden Markov Model)을 이용한다. 실무적으로는 방향성 예측을 위해 주로 주가의 추세분석(Trend Analysis)을 활용한다. 다양한 기술적 지표를 이용한 추세분석에 기반한 시스템트레이딩(System Trading) 기법은 실전투자에서 점차 확대추세에 있다. 본 연구에서는 시스템트레이딩 기법 중 실무에서 많이 이용되는 이동평균교차전략(moving average cross)에 연속 은닉마코프모형을 적용한 지능형 매매시스템을 제안하고, 실제 주가자료를 이용한 시뮬레이션 결과를 제시한다. 세계적 선물시장으로 성장한 KOSPI200 선물시장에서 제안된 매매시스템의 장기간의 투자성과를 분석하기 위하여 지난 21년 동안의 KOSPI200 주가지수자료를 실증 분석하였다. 분석결과는 KOSPI200 주가지수선물의 방향성매매에서 제안된 CHMM기반 지능형 매매시스템이 실전에서 일반적으로 활용되는 시스템트레이딩 기법의 투자성과를 개선할 수 있음을 보여주었다.