Since the days of Benjamin Graham, fundamental equity analysis has offered tremendous insight into the fair valuation of companies.
Many investment strategies leverage these insights. Indeed, models like discounted cashflow analysis or relative value have become so ubiquitous that they are taught in entry-level corporate finance and investment courses.
In the last few decades, several aspects have changed about how these models should be deployed except one thing: these models take time to construct. Fundamental equity analysis has never been scalable. To cover more companies, firms must hire more analysts.
In this presentation, Lee Davidson will discuss how advances in machine learning and robotics may be poised to up-end that paradigm very soon.