AI Summary of Scholarly Research

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Market greenness predicts liquidity shocks and stock pricing errors

Research area:finance-marketsfinancial-markets

What the study found

The study found that market greenness, meaning the market’s environmental, social, and governance (ESG) performance, predicts liquidity shocks during periods plausibly linked to changes in investors’ ESG tastes. It also found that ESG-related liquidity helps explain stock returns and pricing errors beyond what classic risk factors capture.

Why the authors say this matters

The authors conclude that shifts in investors’ ESG tastes may generate alphas, which are returns not explained by standard risk factors, and that these effects are partly captured by ESG-related liquidity. They suggest this new liquidity measure improves the fit of asset-pricing models compared with the Pástor-Stambaugh liquidity measure in the period they study.

What the researchers tested

The researchers built on the Pástor-Stambaugh liquidity measure, a standard way to study how trading conditions affect returns, and on an equilibrium model that includes investors’ ESG preferences. They tested whether market greenness predicts liquidity shocks, whether ESG-related liquidity is explained by established risk factors, and whether forecasts from their model reduce stock alphas.

What worked and what didn't

Market greenness predicted Pástor-Stambaugh liquidity innovations in 2015–2019. Forecasts of ESG-related liquidity reduced stock alphas more effectively than the Pástor-Stambaugh liquidity measure over the period when market greenness predicted liquidity, and ESG-related liquidity was not spanned by well-established risk factors.

What to keep in mind

The abstract does not provide detailed limitations beyond the timing of the main results, which are described for 2015–2019 and before 2020. It also does not describe the exact data sources or empirical design in detail.

Key points

  • Market greenness predicted liquidity shocks during 2015–2019.
  • ESG-related liquidity was linked to stock returns.
  • ESG-related liquidity was not spanned by well-established risk factors.
  • Forecasts from the ESG-related liquidity model reduced stock alphas more effectively than the Pástor-Stambaugh measure before 2020.
  • The authors tie the predictability to shifts in investors’ ESG demand.

Disclosure

Research title:
Market greenness predicts liquidity shocks and stock pricing errors
Authors:
Javier Rojo-Suárez, Ana B. Alonso-Conde, Vitor Gabriel, Juan David González-Ruíz
Institutions:
Instituto Politécnico da Guarda, Universidad Nacional de Colombia, Universidad Rey Juan Carlos, Universidad Rey Juan Carlos
Publication date:
2026-04-05
OpenAlex record:
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AI provenance: This post was generated by gpt-5.4-mini (OpenAI). The original authors did not write or review this post.