Profitability Context and the Cross-Section of Stock Returns
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Alex Kim; Valeri V. Nikolaev
- University of Chicago
- ?University of Chicago Booth School of Business
Strategy in a nutshell
The strategy leverages context-adjusted operating profitability (OPCN) by combining numeric financial data with narrative insights from MD&A sections using BERT embeddings and a deep neural network. OPCN improves predictive power for future stock returns compared to standard operating profitability (OP) or text-only proxies (OPC). Portfolios sorted on OPCN consistently generate positive alphas, higher Sharpe ratios, and superior asset pricing performance, demonstrating the advantage of integrating qualitative context with quantitative characteristics for portfolio construction and stock selection.
Economic rationale
The strategy addresses a limitation of traditional asset pricing models that ignore qualitative context. By incorporating narrative information alongside numeric profitability, OPCN captures variations in firm quality that standard measures miss, particularly for small or high-growth stocks. Context-adjusted profitability enhances predictability, improves pricing of problematic portfolios, and allows investors to exploit insights from qualitative disclosures, leading to more effective and informed investment decisions.