Additional information
by Jivka Ovtcharova (Contribution by), Gabriele Zedlmayer (Contribution by), Alexander Welzl (Contribution by)
The global innovation race is heating up, with advances in artificial intelligence, blockchain, biotechnology, data storage and other cutting-edge technologies transforming sectors and global markets. This is also evidenced in the fact that the ratio of tangible to intangible assets of industry leaders around the world has been seeing a drastic change over the past four decades. The market capitalization of S&P 500 is currently made up of 84% intangible assets, up from 20% in 1975 (according to MSCI).In this book we demonstrate that analyzing intangible assets of a company in great detail allows building models to accurately forecast a company's ability to convert its intellectual property into stock value in the following quarter. We also demonstrate that a company's Artificial Intelligence-IP impact correlates significantly with its future stock returns.The book also introduces a new innovation-related measure, which is contemporaneously associated with market valuation and predicts future operating performance and stock returns. Existing research relating to innovation and market performance focus on the effects of either the input (R&D) or the output (patents) of innovation separately. This book differs in focusing on Artificial Intelligence based innovative efficiency as a ratio of innovative output to input, based on the idea that efficiency should be highly value relevant. We find that the predictive power of AI innovation is incremental to that of other innovation related variables such as R&D intensity, significant R&D growth, patent counts and citations.We also demonstrate that portfolio analysis confirms the hypothesis and show that a portfolio of top innovative companies with top AI-IP generated a return of 237% (+159% to baseline) in the period between January 2017 to June 2019, which is significantly higher than the market (+78%).
