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Haraldsen, Håvard Schei - One of the best experts on this subject based on the ideXlab platform.
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Oil and gas companies’ capital expenditure announcements and the stock market’s responses
University of Stavanger Norway, 2019Co-Authors: Haraldsen, Håvard ScheiAbstract:Master's thesis in Applied FinanceThis thesis attempts to find possible explanations to the Research Problem: Why does the stock prices of oil and gas companies not always respond in accordance with neoclassical standard financial theory when companies announce changes in capital expenditure plans? The Research Problem is deeply rooted within principal-agent theory, and to find answers two theories are applied. First, neoclassical standard financial theory, that assumes all market participants are rational (Becker, 1962). Second, behavioral corporate finance theory, with the biased managers perspective, that assumes managers are biased due to overconfidence, while all other market participants are rational (Baker & Wurgler, 2013; Malmendier, 2018). To solve the Research Problem empirically, two hypothesis are tested. First, to answer whether the news presented on the event days have any effect on the behavior of the firms’ stock prices. Three event studies are conducted to find evidence of abnormal return responses to eight integrated oil and gas companies’ announcements. The three models confirms correlations, where news including plans to increase capital expenditure, result in statistically significant negative average cumulative abnormal return responses ranging from -0.33 to -2.00 percent in the different event windows. Second, to answer whether the capital expenditure news have any effect on the behavior of the firms’ stock prices. Three regression analysis attempts to determine if the capital expenditure news cause abnormal (daily) return responses. One analysis reveals causality, if the firms increase capital expenditure, they experience a statistically significant negative abnormal (daily) return response of -1.66 percent. The stock market’s negative responses are first discussed within neoclassical standard financial theory, where abundant free cash flow and increased managerial power might have caused rational overinvestment in negative net present value projects (Jensen, 1986; McConnell & Muscarella, 1985). Strengthening the issue, managers’ compensation contracts were potentially misaligned in the sample period (Hall & Liebman, 1998; Hall & Murphy, 2000, 2002). Second, within behavioral corporate finance theory, the responses might indicate that managers are overconfident, causing irrational overinvestment in negative net present value projects (Malmendier & Tate, 2008). Both theories point towards excessive use of internal funds as the culprit of the stock market’s negative responses. Where restricting managers’ use of internal financing, improving the boards of directors and monitoring are potential solutions (Baker & Wurgler, 2013; M. Harris & Raviv, 1990; Jensen, 1986; Malmendier & Tate, 2005, 2008, 2015)
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Oil and gas companies’ capital expenditure announcements and the stock market’s responses
University of Stavanger Norway, 2019Co-Authors: Haraldsen, Håvard ScheiAbstract:This thesis attempts to find possible explanations to the Research Problem: Why does the stock prices of oil and gas companies not always respond in accordance with neoclassical standard financial theory when companies announce changes in capital expenditure plans? The Research Problem is deeply rooted within principal-agent theory, and to find answers two theories are applied. First, neoclassical standard financial theory, that assumes all market participants are rational (Becker, 1962). Second, behavioral corporate finance theory, with the biased managers perspective, that assumes managers are biased due to overconfidence, while all other market participants are rational (Baker & Wurgler, 2013; Malmendier, 2018). To solve the Research Problem empirically, two hypothesis are tested. First, to answer whether the news presented on the event days have any effect on the behavior of the firms’ stock prices. Three event studies are conducted to find evidence of abnormal return responses to eight integrated oil and gas companies’ announcements. The three models confirms correlations, where news including plans to increase capital expenditure, result in statistically significant negative average cumulative abnormal return responses ranging from -0.33 to -2.00 percent in the different event windows. Second, to answer whether the capital expenditure news have any effect on the behavior of the firms’ stock prices. Three regression analysis attempts to determine if the capital expenditure news cause abnormal (daily) return responses. One analysis reveals causality, if the firms increase capital expenditure, they experience a statistically significant negative abnormal (daily) return response of -1.66 percent. The stock market’s negative responses are first discussed within neoclassical standard financial theory, where abundant free cash flow and increased managerial power might have caused rational overinvestment in negative net present value projects (Jensen, 1986; McConnell & Muscarella, 1985). Strengthening the issue, managers’ compensation contracts were potentially misaligned in the sample period (Hall & Liebman, 1998; Hall & Murphy, 2000, 2002). Second, within behavioral corporate finance theory, the responses might indicate that managers are overconfident, causing irrational overinvestment in negative net present value projects (Malmendier & Tate, 2008). Both theories point towards excessive use of internal funds as the culprit of the stock market’s negative responses. Where restricting managers’ use of internal financing, improving the boards of directors and monitoring are potential solutions (Baker & Wurgler, 2013; M. Harris & Raviv, 1990; Jensen, 1986; Malmendier & Tate, 2005, 2008, 2015)
David Jobber - One of the best experts on this subject based on the ideXlab platform.
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logit model analysis for multivariate categorical data
Journal of Marketing Management, 1994Co-Authors: David JobberAbstract:Logit model analysis of dichotomous dependent and categorical independent variables has great potential in marketing Research, supplementing other multivariate techiques such as regression and discriminant analysis. This paper describes the steps to be taken in its use and by means of a worked example shows how logit model analysis can be applied to a marketing Research Problem.
Jinjun Chen - One of the best experts on this subject based on the ideXlab platform.
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external integrity verification for outsourced big data in cloud and iot
Future Generation Computer Systems, 2015Co-Authors: Chang Liu, Chi Yang, Xuyun Zhang, Jinjun ChenAbstract:As cloud computing is being widely adopted for big data processing, data security is becoming one of the major concerns of data owners. Data integrity is an important factor in almost any data and computation related context. It is not only one of the qualities of service, but also an important part of data security and privacy. With the proliferation of cloud computing and the increasing needs in analytics for big data such as data generated by the Internet of Things, verification of data integrity becomes increasingly important, especially on outsourced data. Therefore, Research topics on external data integrity verification have attracted tremendous Research interest in recent years. Among all the metrics, efficiency and security are two of the most concerned measurements. In this paper, we will bring forth a big picture through providing an analysis on authenticator-based data integrity verification techniques on cloud and Internet of Things data. We will analyze multiple aspects of the Research Problem. First, we illustrate the Research Problem by summarizing Research motivations and methodologies. Second, we summarize and compare current achievements of several of the representative approaches. Finally, we introduce our view for possible future developments. Security of Big Data in cloud and IoT is becoming a major Problem.Efficient external integrity verification is an important part of data security.We provide a big picture through summarizing and analysis of the main results of external integrity verification schemes for big data in cloud.
Pettitt, Anthony N. - One of the best experts on this subject based on the ideXlab platform.
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Discussion of: A Bayesian information criterion for\ud singular models
Royal Statistical Society, 2017Co-Authors: South, Leah F., Drovandi, Christopher C., Pettitt, Anthony N.Abstract:The BIC can be viewed as an easily computable proxy to fully Bayesian model choice, which is conducted by comparing the marginal likelihood (or evidence) for each of the models. However, the derivation for BIC relies on informative data and a noninformative prior and that the models under consideration are non-singular. Thus the development of associated information criteria that are suitable when the models are singular is an important Research Problem. Hence, the authors should be congratulated for their contribution..
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Discussion of: A Bayesian information criterion for singular models
Royal Statistical Society, 2017Co-Authors: South, Leah F., Drovandi, Christopher C., Pettitt, Anthony N.Abstract:The BIC can be viewed as an easily computable proxy to fully Bayesian model choice, which is conducted by comparing the marginal likelihood (or evidence) for each of the models. However, the derivation for BIC relies on informative data and a noninformative prior and that the models under consideration are non-singular. Thus the development of associated information criteria that are suitable when the models are singular is an important Research Problem. Hence, the authors should be congratulated for their contribution..
Chang Liu - One of the best experts on this subject based on the ideXlab platform.
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external integrity verification for outsourced big data in cloud and iot
Future Generation Computer Systems, 2015Co-Authors: Chang Liu, Chi Yang, Xuyun Zhang, Jinjun ChenAbstract:As cloud computing is being widely adopted for big data processing, data security is becoming one of the major concerns of data owners. Data integrity is an important factor in almost any data and computation related context. It is not only one of the qualities of service, but also an important part of data security and privacy. With the proliferation of cloud computing and the increasing needs in analytics for big data such as data generated by the Internet of Things, verification of data integrity becomes increasingly important, especially on outsourced data. Therefore, Research topics on external data integrity verification have attracted tremendous Research interest in recent years. Among all the metrics, efficiency and security are two of the most concerned measurements. In this paper, we will bring forth a big picture through providing an analysis on authenticator-based data integrity verification techniques on cloud and Internet of Things data. We will analyze multiple aspects of the Research Problem. First, we illustrate the Research Problem by summarizing Research motivations and methodologies. Second, we summarize and compare current achievements of several of the representative approaches. Finally, we introduce our view for possible future developments. Security of Big Data in cloud and IoT is becoming a major Problem.Efficient external integrity verification is an important part of data security.We provide a big picture through summarizing and analysis of the main results of external integrity verification schemes for big data in cloud.
