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Text-implied uncertainty in 10-K filings: Do investors get the message?

Oliver Budras et al.

Quarterly Review of Economics and Finance2026https://doi.org/10.1016/j.qref.2026.102121article
AJG 2ABDC B
Weight
0.50

What the paper says

We investigate the role of text-implied uncertainty in the cross-section of stock returns. We employ word embeddings to derive an uncertainty dictionary from 10-K annual company filings. Stocks in the highest uncertainty quintile generate a 0.281% higher monthly return compared to stocks in the lowest quintile. This outperformance survives risk-adjustment. Furthermore, uncertainty is negatively related to filing period abnormal returns. This information is priced within one day after filing. High-uncertainty companies have lower return-on-assets, unexpected earnings, and are less likely to increase dividends in the subsequent fiscal year. Uncertainty-averse investors demand a premium for holding high uncertainty stocks. • We use GloVe embeddings to derive an uncertainty metric in 10-K filings of companies. • Our uncertainty metric is orthogonalized towards risk and sentiment. • Uncertainty is priced with a significantly positive risk premium in the cross-section of stocks. • Filing period returns of high uncertainty stocks decrease within one day after the filing. • Finally, uncertainty is negatively related to future firm fundamentals.

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https://doi.org/https://doi.org/10.1016/j.qref.2026.102121

Or copy a formatted citation

@article{oliver2026,
  title        = {{Text-implied uncertainty in 10-K filings: Do investors get the message?}},
  author       = {Oliver Budras et al.},
  journal      = {Quarterly Review of Economics and Finance},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.qref.2026.102121},
}

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Text-implied uncertainty in 10-K filings: Do investors get the message?

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.