Please use this identifier to cite or link to this item:
https://scholarhub.balamand.edu.lb/handle/uob/3622
Title: | Predicting stock prices via dividend discount model | Authors: | Shalhoub, Melissa Chamra, Souad |
Advisors: | Assaf, Ata | Subjects: | Investments analysis Stocks |
Issue Date: | 2017 | Abstract: | Investment is related to the marketable security in order to buy or sell at the existent period. Time and risk are major factors in predicting future prices since the return behind those funds are expected to be at high risk and vice versa. In our project , we will study the Dividend Discounted Model in the wheat, oil and food sectors, especially Bunge and Glencore , Valero and Shell, Kelloggs and General Mills' companies. This model is used by investors in order to calculate an intrinsic value that helps them in the process of buying, holding or selling the stock. The intrinsic value of a stock is treated like the actual value of a company. It also determines the stock prices based on the discounted future cash flows in a way that investors will get what they pay for. In this project, our main objective is to run a regression of the intrinsic value as a function of return on equity and the net income in order to find the significance and effectiveness of those two factors on the intrinsic value. As a result, in most companies, both ROE and net income affect the intrinsic value, but there is always an exception where higher prices can be attained such as Glencore. In other words, one of those two aforementioned factors will affect the intrinsic value. We declare that the dividend discount model is a reliable model to estimate the intrinsic value that should be lower than the actual price when comparing them. |
Description: | Includes bibliographical references (p. 34-35). Supervised by Dr. Ata Assaf. |
URI: | https://scholarhub.balamand.edu.lb/handle/uob/3622 | Rights: | This object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holder | Ezproxy URL: | Link to full text | Type: | Project |
Appears in Collections: | UOB Theses and Projects |
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.