Aswath Damodaran - The Value of a User Video
While traditional business valuations have treated cash flow as the ultimate metric for gauging success, many of today's companies focus more on the size of their user community than their bottom line. Responding to evolving perspectives, newer valuation models attempt to assign value to individual consumers, but these models involve a series of assumptions and generalizations that do not always withstand scrutiny. Using Uber as a case study, this session will compare and contrast user-based valuation models with more traditional discounted cash flow (DCF) models, identifying where they converge and diverge.
Aswath Damodaran holds the Kerschner Family Chair in Finance Education and is a Professor of Finance at New York University Stern School of Business. He received a B.A. in Accounting from Madras University, an M.S. in Management from the Indian Institute of Management, and an M.B.A. and Ph.D. in Finance from the University of California. He has been voted “Professor of the Year” by the graduating M.B.A. class five times during his career at NYU. In addition, Professor Damodaran is the author of several highly-regarded and widely-used academic texts on Valuation, Corporate Finance, and Investment Management. Professor Damodaran currently teaches Corporate Finance and Equity Instruments & Markets. His research interests include Information and Prices, Real Estate, and Valuation.
The L2 Digital Leadership Academy, led by faculty from NYU Stern, Kellogg School of Management, Harvard Business School, and L2 researchers, is a two-day conference rooted in business fundamentals coupled with tactical sessions on digital topics.
About the Site 🌐
This site provides links to random videos hosted at YouTube, with the emphasis on random. 🎥
Origins of the Idea 🌱
The original idea for this site stemmed from the need to benchmark the popularity of a video against the general population of YouTube videos. 🧠
Challenges Faced 🤔
Obtaining a large sample of videos was crucial for accurate ranking, but YouTube lacks a direct method to gather random video IDs.
Even searching for random strings on YouTube doesn't yield truly random results, complicating the process further. 🔍
Creating Truly Random Links 🛠️
The YouTube API offers additional functions enabling the discovery of more random videos. Through inventive techniques and a touch of space-time manipulation, we've achieved a process yielding nearly 100% random links to YouTube videos.
About YouTube 📺
YouTube, an American video-sharing website based in San Bruno, California, offers a diverse range of user-generated and corporate media content. 🌟
Content and Users 🎵
Users can upload, view, rate, share, and comment on videos, with content spanning video clips, music videos, live streams, and more.
While most content is uploaded by individuals, media corporations like CBS and the BBC also contribute. Unregistered users can watch videos, while registered users enjoy additional privileges such as uploading unlimited videos and adding comments.
Monetization and Impact 🤑
YouTube and creators earn revenue through Google AdSense, with most videos free to view. Premium channels and subscription services like YouTube Music and YouTube Premium offer ad-free streaming.
As of February 2017, over 400 hours of content were uploaded to YouTube every minute, with the site ranking as the second-most popular globally. By May 2019, this figure exceeded 500 hours per minute. 📈
List of ours generators⚡
Random YouTube Videos Generator
Random Film and Animation Video Generator
Random Autos and Vehicles Video Generator
Random Pets and Animals Video Generator
Random Travel and Events Video Generator
Random People and Blogs Video Generator
Random Entertainment Video Generator
Random News and Politics Video Generator
Random Howto and Style Video Generator
Random Education Video Generator