Chan, Keng WaiKeng WaiChan2026-01-222026-01-222023-10https://dspace.usj.edu.mo/handle/123456789/6896Meta Platforms, Inc. (‘the Company’) is a global tech firm offering online social networking services to users worldwide. The Company's mission centers on creating tech solutions that foster human connections, enable community discovery and support business expansion. This dissertation conducts a thorough financial analysis of the Company, focusing on determining its intrinsic value as of December 31, 2021, compared to the market valuation. The study explores various facets, including a deep dive into the Company, an evaluation of market positioning and strategy, an assessment of financial performance with internal and external factors, a ten-year pro forma financial projection, and an exploration of methodologies to calculate the Company's intrinsic value using three discounted cash flow (DCF) models. The findings from three valuation models, enterprise discounted cash flow (EDCF), discounted economic profit (DEP), and adjusted present value (APV), converge on approximate intrinsic values for the Company that was $303.32, $303.54, and $303.28, respectively. The analysis indicates the Company was overvalued compared to the Company’s market stock price of $336.35 as of December 31, 2021. Moreover, recommendations for the Company's management include a strategic shift toward data-centric initiatives and digital infrastructure, emphasizing security and nurturing virtual economies. Short-term objectives encompass proactive investments in the burgeoning metaverse ecosystem, collaborations with external stakeholders, and safeguarding user data. These imperatives position the Company for sustainable growth. Furthermore, the analysis explores how changes in the key factors, the growth rate in perpetuity (g), expected return on new invested capital (RONIC), and market risk premium (MRP) influence the Company's intrinsic value. This examination spans positive and negative fluctuations in these variables, equipping the Company's management with insights for value-oriented decision-making. Simultaneously, it helps investors in identifying areas for further investigation in valuation.entext::thesis::master thesis