Leslie, KirstenAlmayouf, Abdulaziz2023-11-282023-11-282023-11-09https://hdl.handle.net/20.500.14154/69880The thesis aims to conduct a comprehensive examination and consolidation of current scholarly works on asset pricing models within the oil industry, employing the PRISMA methodology. Furthermore, this study employs regression analysis and model comparisons utilising Microsoft Excel to assess the efficacy of various asset pricing models in predicting asset prices within the oil industry. The literature review involves conducting a thorough search and analysis of pertinent studies, emphasising the significance of asset pricing models within the oil industry. Arbitrage Pricing Theory (APT), the Capital Asset Pricing Model (CAPM), and the Fama-French Three-Factor Model (FF3) are some theories that have been studied in the literature. The performance evaluation of asset pricing models involves the utilisation of Microsoft Excel for conducting regression analysis and model comparisons. The analysis primarily centres on the assessment of the adequacy of the model fit by utilising statistical measures such as R-squared, adjusted R-squared, and the significance of coefficients. Residual analysis facilitates the evaluation of model performance by enabling the examination of discrepancies between predicted and observed values. The utilisation of the PRISMA methodology in conducting a systematic review allows for the identification and analysis of the strengths, weaknesses, and gaps present within the existing body of literature. This comprehensive evaluation provides practitioners and researchers with the necessary information to make well-informed decisions. The utilisation of regression analysis contributes to the advancement of knowledge by assessing the efficacy of various models, among which the Arbitrage Pricing Theory (APT) model exhibits potential in its ability to forecast asset prices within the oil industry. This thesis underscores the necessity of developing more advanced and customised asset pricing models that incorporate the distinctive attributes of the oil industry. The strengths and weaknesses that have been identified serve as a valuable guide for practitioners in developing risk management strategies. Additionally, the insights obtained from the regression analysis provide valuable information for determining future research directions in asset pricing specifically within the oil industry.64enasset pricing modelsoil industryPRISMA methodologyregression analysisCAPMFF3APTThesis