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Explore the dynamics of public equity investing in the artificial intelligence (AI) sector by analyzing key technology companies and financial statements, developing critical insights into AI's economic and investment potential.
Artificial intelligence is transforming industries and markets, making it a hot topic for public equity investors. In this Build Project, you will assume the role of a public equity analyst, focusing on AI technology companies in the semiconductor, software, and internet sectors. You will gain a practical understanding of the tasks entry-level equity analysts perform, by developing skills in fundamental analysis, including business, financial, and qualitative analysis, to determine whether AI stocks represent a long-term growth opportunity or a speculative bubble. The workshops will be interactive with group activities to discuss whether an AI company is a good or bad business, hand-on valuation exercises, and watching videos of what experts have addressed to discuss the current state of AI developments. By the end of the project, you will have produced a simple stock pitch and prepared for job interviews in the public equity space, with experience tackling the types of questions typically asked in interviews for analyst roles.
We will start with introductions to get to know each other. You will then learn the basics of public equity investing, including long-only, long/short, and activist investment strategies. You'll engage in discussions on the career paths available in public equity and what sets public equity roles apart from other investment roles. Lastly, this workshop will also introduce you to the course structure and expectations.
You will dive into analyzing businesses by evaluating real-world AI companies through the case study of Nvidia and Microsoft. You will learn about leading AI firms in sectors such as semiconductors and software, identifying key commonalities that make a business strong or weak. This workshop also introduces AI's scope in public markets and explores the companies at the forefront of AI development and commercialization.
In this workshop, you will study the three core financial statements—Income Statement, Balance Sheet, and Cash Flow Statement—focusing on the critical line items most relevant to technology companies. You will also learn about key performance indicators (KPIs) commonly used in AI and tech sectors, and how alternative data can influence public equity decisions.
You will review and analyze real-world earnings call transcripts for a company you choose for the final project. You will learn how to interpret management commentary, identify signals of competitive positioning, and assess market sentiment.
You will explore valuation methods, including discounted cash flow (DCF) and comparable company analysis (comps), discussing their strengths and limitations. Through practical exercises, you will build valuation models for AI companies, considering the impact of macroeconomic factors on technology stock valuations.
This workshop will focus on whether AI investing is overhyped, drawing parallels with the dot-com bubble and the crypto boom. You will learn about the technology adoption curve, the hype cycle, and discuss how to identify speculative versus sustainable growth trends in AI.
You will be guided on how to structure and deliver a compelling stock pitch. You'll receive feedback on your thesis statements, and practice Excel shortcuts and presentation skills, honing your ability to present complex financial analysis in a clear, concise manner. Common mistakes made by first-year analysts will also be covered to help you avoid pitfalls.
You will present their final stock pitches, either recommending the AI company as a long or short investment opportunity. You will defend your thesis with data-backed financial analysis, qualitative insights, and competitive landscape evaluations. The workshop will conclude with a group Q&A where your field questions as if presenting to a portfolio manager.
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Danielle Kim is a Build Fellow at Dream Ventures Lab, where she works with students leading projects in finance.
Danielle is an analyst at Analog Century Management, where she focuses on fundamental equity research for long short equity strategies.
Danielle has over 5 years of experience in the public equities investment field. She holds a Bachelor’s Degree in Princeton University.
A fun fact about Danielle is that she has travelled to more countries than provinces in my home country.