Do Sell-side Analyst Reports Have Investment Value?

TL;DR

This study demonstrates that analyst report narratives, analyzed with large language models and machine learning, contain significant investment value and can improve long-term return forecasts beyond traditional metrics.

Contribution

It introduces a novel LLM-ML pipeline to extract and quantify the investment value of analyst narratives, revealing their incremental predictive power.

Findings

Portfolios based on narrative forecasts outperform benchmarks.

Analyst narratives contribute significantly to portfolio performance.

The effect is stronger after adverse news and for growth stocks.

Abstract

This paper documents novel investment value in analyst report text. Using 1.2 million reports from 2000-2023, I embed narratives with large language models (LLMs) and fit machine learning (ML) forecasts of future long-term returns. Portfolios formed on the report narrative forecasts earn sizable and significant performance that is incremental to analysts' numerical outputs and to a broad set of established factors and characteristic-based predictors. The effect is stronger after adverse news and is amplified for growth stocks with aggressive investment. To open the black box, I apply a Shapley decomposition that attributes portfolio performance to distinct topics. Analysts' strategic outlook contributes the most to portfolio performance, especially forward-looking fundamental assessments. Beyond providing direct evidence that analyst narratives contain value-relevant assessments that diffuse into price over time, this study illustrates how interpretable LLM-plus-ML pipelines can scale and augment human judgment in investment decisions.