• Title/Summary/Keyword: Stock management

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A Multivariate GARCH Analysis on International Stock Market Integration: Korean Market Case

  • Kim, Namhyoung
    • Management Science and Financial Engineering
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    • v.21 no.1
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    • pp.31-39
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    • 2015
  • Financial integration is a phenomenon in which global financial markets are closely connected with each other. This article investigates the integration of Korean stock market with other stock markets using a multivariate GARCH analysis. We chose total seven countries including Korea for this paper based on the amount of export and then we chose major stock indices which can be thought as representative stock markets of those countries. The empirical analysis has shown that countries' financial integration.

Development of a Stockbreeding Management System for Dairy Cattle (젖소의 사양관리 시스템 개발)

  • Kim, Dong-Won;Han, Byung-Sung;Chong, Kil-To;Kim, Yong-Jun;Kim, Myoung-Soon;Lim, Tae-Yeong;Chae, Seok
    • IE interfaces
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    • v.11 no.3
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    • pp.193-207
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    • 1998
  • The agriculture and fishery share in the Korean GDP is continuously decreasing after 1960s. Furthermore the proportion of these industries in the GDP has diminished as low as 10 percent in recent years. However, the stockbreeding sector in these industries are considerably expanded. More than 50 percent of the whole farmhouses are involved in the livestock farming, and the stock farming portion is steadily increased in its size and scope. Thus, the mechanization and the automization of stockbreeding equipments are greatly required to reduce down production cost, as well as to win the competitiveness in the global market. From this aspect, developed in this paper is a stockbreeding management system (SMS) for dairy cattle, which can be used in small and medium sized dairy farms. First, the basic schema of the stockbreeding management system are addressed in view of stockbreeding management for individual dairy cattle. Electronic identification (EI) systems and sensory devices have changed stockbreeding management strategy from group stock control into individual stock control manner. The SMS receives stock body measurement data through the sensory devices such as weight, temperature, and milk conductivity meters. A common database then integrates those measuring data together so that the SMS can determine the appropriate solution on each stock's breeding such as feeding and milking. Thus, each stock can be supervised by a sophisticated SMS that provides the best solution to the stockbreeding throughout the stock's whole life-cycle. Secondly. six major submodules of the SMS, based on the EI and sensory devices, are proposed. They are individual stock management, disease management, health management, feeding management, milking management, and a propagation management submodule. Finally, a prototype system for the SMS is demonstrated. The system is developed using Delphi 2 client-server system run under the Windows 95 environment.

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Stock Price Prediction and Portfolio Selection Using Artificial Intelligence

  • Sandeep Patalay;Madhusudhan Rao Bandlamudi
    • Asia pacific journal of information systems
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    • v.30 no.1
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    • pp.31-52
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    • 2020
  • Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

Long Term Mean Reversion of Stock Prices Based on Fractional Integration

  • Jun, Duk-Bin;Kim, Yong-Jin;Park, Dae-Keun
    • Management Science and Financial Engineering
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    • v.17 no.2
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    • pp.85-97
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    • 2011
  • In this study we examine the long term behavior of stock returns. The analysis reveals that negative autocorrelations of the returns exist for a super-long horizon as long as 10 years. This pattern, however, contrasts to predictions of previous stock price models which include random walks. We suggest the introduction of a fractionally integrated process into a nonstationary component of stock prices, and demonstrate empirically the existence of the process in NYSE stock returns. The predicted values of autocorrelation from our stock price model confirm the super-long term behavior of the returns observed in regression, indicating that inefficiency in the stock market could remain for a long time.

Quantitative Causal Reasoning in Stock Price Index Prediction Model

  • Kim, Myoung-Joon;Ingoo Han
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1998.10a
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    • pp.228-231
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    • 1998
  • Artificial Intelligence literatures have recognized that stock market is a highly unstructured and complex domain so that it is difficult to find knowledge that belongs to that domain. This paper demonstrates that the proposed QCOM can derive global knowledge about stock market on the basis of a set of local knowledge and express it as a digraph representation. In addition, inference mechanism using quantitative causal reasoning can describe the qualitative and quantitative effects of exogenous variables on stock market.

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Simultaneous Equation Estimation in Finance and Corporate Financial Decision: Empirical Evidence from Pakistan Stock Exchange

  • AHMED, Wahab;KHAN, Hadi Hassan;RAUF, Abdul;ULHAQ, SM Nabeel;BANO, Safia;SARWAR, Bilal;HUDA, Shams ul;KHAN, Mirwaise;WALI, Ahmed;DURRANI, Maryam Najeeb
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.11-21
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    • 2021
  • In the last few years, there is growing interest in the field of simultaneous equation estimation in finance due to the endogeneity problem caused by measurement errors, simultaneity, or omitted variables. This study aims to discuss the endogeneity problem in corporate financing decisions and investigate the interrelationship of financial decision-making such as investment decision, dividend decision, and external financing decision in Pakistan Stock Exchange (PSX) using two-stage least squares (2SLS) and generalized method of moment (GMM) estimation. The Bruech-Pagan test shows that the data has no heteroskedasticity issue and 2SLS is a better approach in the context of this study as compared to the GMM approach, and internal instruments are also sufficiently strong and valid. The three financial decision-making attributes are not jointly determined, and the dividend is influenced by one-sided investment. In the emerging stock market context, external financing and investment are not inter-related and did not affect each other. The question of whether the simultaneous equation estimation can be useful in the context of the emerging stock markets and newly-growing firms remains unanswered. The inclusive evidence shows that the theoretical link in the emerging stock market is difficult to prove like in developed stock markets.

Investigating Repurchase Intention on Sharia Shares: An Empirical Evidence of the Sharia Stock Market in Indonesia

  • MURHADI, Thasrif;AZIZ, Nasir;UTAMI, Sorayanti;MAJID, M. Shabri Abd
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.5
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    • pp.761-768
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    • 2021
  • The Islamic capital market in Indonesia is currently developing rapidly marked by the massive growth of sharia stock investors. It is followed by the development of an online sharia trading platform by stock brokerage companies so that investors can transact online sharia shares. From the number of existing stock investors, however, there are still very few Islamic stock investors who repurchase shares after the previous purchase. This really attracted the attention of researchers to investigate the repurchase intention of sharia share in the Indonesia stock market. 415 samples who are Islamic stock investors in the Indonesia stock market have filled out distributed questionnaires. Then, the data was processed using SEM Amos. The results of this study found that perceived enjoyment, perceived ease to use, and expectation have a positive and significant effect on investor satisfaction. Then, perceived enjoyment and expectation have a positive and significant effect on repurchase intention, while perceived ease to use has a negative and insignificant effect on repurchase intention, but has a positive effect through the mediating variable investor satisfaction. Investor satisfaction has a positive and significant effect on repurchase intention, and investor satisfaction is a good mediator for the exogenous variables in this study.

A Study about the Correlation between Information on Stock Message Boards and Stock Market Activity (온라인 주식게시판 정보와 주식시장 활동에 관한 상관관계 연구)

  • Kim, Hyun Mo;Yoon, Ho Young;Soh, Ry;Park, Jae Hong
    • Asia pacific journal of information systems
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    • v.24 no.4
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    • pp.559-575
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    • 2014
  • Individual investors are increasingly flocking to message boards to seek, clarify, and exchange information. Businesses like Seekingalpha.com and business magazines like Fortune are evaluating, synthesizing, and reporting the comments made on message boards or blogs. In March of 2012, Yahoo! Finance Message Boards recorded 45 million unique visitors per month followed by AOL Money and Finance (19.8 million), and Google Finance (1.6 million) [McIntyre, 2012]. Previous studies in the finance literature suggest that online communities often provide more accurate information than analyst forecasts [Bagnoli et al., 1999; Clarkson et al., 2006]. Some studies empirically show that the volume of posts in online communities have a positive relationship with market activities (e.g., trading volumes) [Antweiler and Frank, 2004; Bagnoli et al., 1999; Das and Chen, 2007; Tumarkin and Whitelaw, 2001]. The findings indicate that information in online communities does impact investors' investment decisions and trading behaviors. However, research explicating the correlation between information on online communities and stock market activities (e.g., trading volume) is still evolving. Thus, it is important to ask whether a volume of posts on online communities influences trading volumes and whether trading volumes also influence these communities. Online stock message boards offer two different types of information, which can be explained using an economic and a psychological perspective. From a purely economic perspective, one would expect that stock message boards would have a beneficial effect, since they provide timely information at a much lower cost [Bagnoli et al., 1999; Clarkson et al., 2006; Birchler and Butler, 2007]. This indicates that information in stock message boards may provide valuable information investors can use to predict stock market activities and thus may use to make better investment decisions. On the other hand, psychological studies have shown that stock message boards may not necessarily make investors more informed. The related literature argues that confirmation bias causes investors to seek other investors with the same opinions on these stock message boards [Chen and Gu, 2009; Park et al., 2013]. For example, investors may want to share their painful investment experiences with others on stock message boards and are relieved to find they are not alone. In this case, the information on these stock message boards mainly reflects past experience or past information and not valuable and predictable information for market activities. This study thus investigates the two roles of stock message boards-providing valuable information to make future investment decisions or sharing past experiences that reflect mainly investors' painful or boastful stories. If stock message boards do provide valuable information for stock investment decisions, then investors will use this information and thereby influence stock market activities (e.g., trading volume). On the contrary, if investors made investment decisions and visit stock message boards later, they will mainly share their past experiences with others. In this case, past activities in the stock market will influence the stock message boards. These arguments indicate that there is a correlation between information posted on stock message boards and stock market activities. The previous literature has examined the impact of stock sentiments or the number of posts on stock market activities (e.g., trading volume, volatility, stock prices). However, the studies related to stock sentiments found it difficult to obtain significant results. It is not easy to identify useful information among the millions of posts, many of which can be just noise. As a result, the overall sentiments of stock message boards often carry little information for future stock movements [Das and Chen, 2001; Antweiler and Frank, 2004]. This study notes that as a dependent variable, trading volume is more reliable for capturing the effect of stock message board activities. The finance literature argues that trading volume is an indicator of stock price movements [Das et al., 2005; Das and Chen, 2007]. In this regard, this study investigates the correlation between a number of posts (information on stock message boards) and trading volume (stock market activity). We collected about 100,000 messages of 40 companies at KOSPI (Korea Composite Stock Price Index) from Paxnet, the most popular Korean online stock message board. The messages we collected were divided into in-trading and after-trading hours to examine the correlation between the numbers of posts and trading volumes in detail. Also we collected the volume of the stock of the 40 companies. The vector regression analysis and the granger causality test, 3SLS analysis were performed on our panel data sets. We found that the number of posts on online stock message boards is positively related to prior stock trade volume. Also, we found that the impact of the number of posts on stock trading volumes is not statistically significant. Also, we empirically showed the correlation between stock trading volumes and the number of posts on stock message boards. The results of this study contribute to the IS and finance literature in that we identified online stock message board's two roles. Also, this study suggests that stock trading managers should carefully monitor information on stock message boards to understand stock market activities in advance.

East Asian five stock market linkages (아시아 주식수익률의 동조화에 대한 연구)

  • Jung, Heon-Yong
    • Management & Information Systems Review
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    • v.27
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    • pp.131-147
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    • 2008
  • The study examines common component existing in five Asian countries from 1991 to 2007. To do this, the daily stock market indices of Korea, Malaysia, Thailand, Indonesia, and the Philippines were used. Using a Vector Autoregressive Model this paper analyzes causal relations and dynamic interactions between five Asian stock markets. The findings in this study indicate that level of five Asian stock markets' stock return linkages are low. First, from the statistics for pair-wise Granger causality tests, I find Granger-causal relationship between Korea and Indonesia and between Malaysia and and Indonesia. Second, from the results of response function and the statistics of variance decomposition, I find that week shocks to Korean stock market return on Malaysia, Indonesia, Thailand, and the Philippines stock market returns. The results indicate increased Asian stock market linkages but the level is very low. This implies that the benefits of diversification within the five Asian stock markets are still existed.

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Is Foreign Investors' behavior Involved in Investor Sentiment? Evidence Based on the Korean Stock Crashes

  • Choi, Suyoung
    • Journal of East Asia Management
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    • v.3 no.1
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    • pp.41-55
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    • 2022
  • This study investigates whether foreign investors' behavior is involved in firm-specific investor sentiment. Because the mixed role of foreign investors on investor sentiment formation seems to exist in the Korean stock market, it needs to examine the moderate or incremental effect of foreign investors on the stock price crash risk which is due to investor sentiment. The analysis results using Korea Stock Exchanges - listed firms for the period of 2011-2019 show the increased future stock price crash risk which is attributable to high investor sentiment is mitigated for firms with the high foreign ownership, indicating the moderate effect. This study expands the literature on the foreign investors' behavior in the Korean stock market, by showing foreign investors are not involved in firm-specific investor sentiment, which improves market's efficiency in the Korean stock market. Also, the paper is valuable to the academic and practice field in that the findings shed light on the foreign investors' mitigating role in stock price crashes in the behavioral finance perspective.