Applied Fundamental Analysis with Alternative Data

Finding the ground truth regarding the positioning, operations, and prospects of a company, country, resource pool, or investment opportunity is challenging. It is imperative to go beyond the numbers in financial statements with alternative data and information. In this course, we will learn to accept that no predefined formula exists to identify, quantify, and project a complex organization operating in a constantly evolving global environment. We will highlight the importance of sufficiently framing questions for intelligence gathering and analysis. The act of questioning serves as the very foundation of any investigation, project, or research endeavor. It sharpens our focus, guides our inquiry, and lays the groundwork for meaningful and actionable answers. The power to shape our understanding of the world, businesses, consumers, and individual actors lies in the answers and data we gather and the quality and direction of the questions we pose. The confidence to ask the right questions and break down the subject of the analysis and associated materials will be a vital component of the learning. The student will work with real datasets and benefit from direct advice, experience, and practical insights from portfolio managers, research analysts, consulting data analysts, and others to derive value from the world of information within their reach. The combination of traditional and alternative data with the right real-world questions serves to forecast future outcomes. The overarching framework for applied learning will be: • Collection: Framing the appropriate questions and sourcing information and data in context of the subject being evaluated. • Evaluation: Understating the reliability of the data and validity of the information value as presented. • Analysis: Applying methodologies and frameworks, including financial frameworks to transform the data for concise decisions. • Reporting: Frameworks for pushing the data to subject models, including financial models, presenting the derived intelligence in a useable format. • Distribution: Informing user, including oneself and integrating feedback on the outcomes. This course guides the student in acquiring alternative data, extracting insight from it, using it for projections, contextual business model evaluation, and determining “unknown unknowns”. The learning journey is intended to be insightful, engaging, empowering, and supplement traditional data, such as financial statements for students pursuing all disciplines. The knowledge will provide leverage the world of data and analytics, broaden your horizons, and enhance your toolkit for informed decision-making.