AI Valuation Paradox Dataset: Complementary Assets, Real Options, and Market Sentiment in S&P 500 Firms (2018–2024)

This dataset provides a comprehensive empirical foundation for analyzing the AI Valuation Paradox in S&P 500 firms, defined as the persistent gap between market valuation and realized financial performance following artificial intelligence investments. It integrates a longitudinal firm-quarter panel (2018–2024) with in-depth comparative case study evidence to examine how AI investment intensity, firm-specific complementary assets, real options, and market sentiment jointly shape equity valuation outcomes. The dataset includes constructed indicators such as the Complementary Asset Index (CAI), AI Investment Intensity (AII), Sentiment Divergence Index (SDI), real option exercise events, and valuation measures including Tobin’s q and operating performance metrics. In addition, it documents event-study dynamics capturing the “integration dip” and provides structured inputs for regression, difference-in-differences, and structural equation modeling analyses. The resource is designed to support replication, extension, and comparative research on AI-driven value creation, corporate valuation of intangible assets, and the strategic and behavioral mechanisms underlying market mispricing.