A Statistical Model for Predict Equity Price of the Apple Inc. company in the Information Technology Sector
The goal of this paper was to produce predictions regarding the future stock price of the massive corporation Apple Inc. The Information Technology (IT) sector comprises six distinct industries, among which Apple Inc., which is a large-cap company, has been the mainstay of my research. Apple Inc. is one of the most valuable companies in the world, with a market capitalization of over $2 trillion. In the study, a predictive model has been devised to estimate the equity price of the Apple Inc. company, employing diverse statistical techniques. A variety of statistical methods to examine 23 observations using time series data from FactSet-2022 has been used in this study. Graphical techniques including histograms, dissipate plots, and line plots were used to outwardly investigate the dataset, while elucidating insights were utilized to sum up the attributes of versatile factors like Value, EPS, BVPS, CR, DTA, EBIT, and SPS. Relationship investigation was directed to survey the straight relationship between factors. The essential scientific strategy utilized was relapse examination, with the practical detail of the model framed in Conditions 1, 2, and 3. These conditions portray Cost as a component of book esteem per share (BVPS), income before interest and duties (EBIT), and sell per share (SPS). Two types of the example relapse condition were introduced, one including a catch term (α) and coefficients (β) for every autonomous variable, and another barring the block term. Based on the values of the independent variables, the regression models attempt to predict Price, the dependent variable. The examination was directed utilizing the R programming language. This exploration adds to the field by offering bits of knowledge into the prescient demonstration of value costs inside the IT area, with explicit pertinence to Apple Inc.
