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- Member of: ASU Electronic Theses and Dissertations
Description
There have been extensive research in how news and twitter feeds can affect the outcome of a given stock. However, a majority of this research has studied the short term effects of sentiment with a given stock price. Within this research, I studied the long-term effects of a given stock price using fundamental analysis techniques. Within this research, I collected both sentiment data and fundamental data for Apple Inc., Microsoft Corp., and Peabody Energy Corp. Using a neural network algorithm, I found that sentiment does have an effect on the annual growth of these companies but the fundamentals are more relevant when determining overall growth. The stocks which show more consistent growth hold more importance on the previous year’s stock price but companies which have less consistency in their growth showed more reliance on the revenue growth and sentiment on the overall company and CEO. I discuss how I collected my research data and used a multi-layered perceptron to predict a threshold growth of a given stock. The threshold used for this particular research was 10%. I then showed the prediction of this threshold using my perceptron and afterwards, perform an f anova test on my choice of features. The results showed the fundamentals being the better predictor of stock information but fundamentals came in a close second in several cases, proving sentiment does hold an effect over long term growth.
ContributorsReeves, Tyler Joseph (Author) / Davulcu, Hasan (Thesis advisor) / Baral, Chitta (Committee member) / Cesta, John (Committee member) / Arizona State University (Publisher)
Created2016
Description
In this study I investigate the organizational strategies that Chinese power generation companies may use to reduce the impact of coal price increases on their profits. Organizations are open systems in that no organization possesses all the resources that it needs and all organizations must obtain resources from their external environments in order to survive. Resource dependent theory suggests that the most important goal of an organization is to find effective mechanisms to cope with its dependence on the external environments for resources that are critical to its survival. Chinese power generation companies traditionally rely heavily on coal as their raw materials, and an increase in coal price can have a significant negative impact on their profits. To address this issue, I first provide a systematic review of the resource dependence theory and research, with a focus on the strategies such as vertical integration, diversification, and hedging that organizations can undertake to reduce their dependence on the external environment as well as their respective benefits and costs. Next, I conduct a qualitative case analysis of the primary strategies the largest Chinese power generation companies have used to reduce their dependence on coal. I then explore a new approach that Chinese power generation companies may use to cope with increases in coal price, namely, by investing in an index of coal companies in the stock market. My regression analysis shows that coal price has a strong positive relation with the price of the coal company index. This finding suggests that it is possible for firms to reduce the negative impact of raw material price increase on their profits by investing in a stock market index of the companies that supply the raw materials that they depend on.
ContributorsSun, Min (Author) / Shen, Wei (Thesis advisor) / Liu, Jun (Committee member) / Pei, Ker-Wei (Committee member) / Arizona State University (Publisher)
Created2015