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.本数据集为分析标普500（S&P 500）企业中的人工智能估值悖论（AI Valuation Paradox）提供了全面的实证基础。该悖论被定义为人工智能（artificial intelligence）投资后，企业市场估值与已实现财务绩效之间持续存在的差距。数据集整合了2018至2024年的纵向企业季度面板数据，并辅以深度比较案例研究证据，以考察人工智能投资强度、企业专属互补资产、实物期权与市场情绪如何共同作用于股权估值结果。数据集包含多项自主构建的指标，如互补资产指数（Complementary Asset Index, CAI）、人工智能投资强度（AI Investment Intensity, AII）、情绪分歧指数（Sentiment Divergence Index, SDI）、实物期权行权事件，以及托宾q值（Tobin’s q）、经营绩效指标等估值类衡量维度。此外，本数据集还记录了捕捉“整合低谷”（integration dip）的事件研究动态，并为回归分析、双重差分法（difference-in-differences）与结构方程模型（structural equation modeling）等研究提供了标准化输入数据。本资源旨在支撑人工智能驱动的价值创造、无形资产企业估值以及市场错误定价背后的战略与行为机制相关的可复现研究、拓展研究与比较研究。