Link: https://doi.org/10.1108/MD-05-2025-1161  

Abstract
Purpose

This research aims to examine the effect of managerial sentiment on the stock liquidity of firms listed in India. It further examines whether this relationship varies across stages of the corporate life cycle (CLC).

Design/methodology/approach

This research introduces a novel manager sentiment index that uses FinBERT, a large language model based on the bidirectional encoder representations from transformers, specifically tailored for financial text, and draws on Management Discussion and Analysis (MD&A) reports. Subsequently, a panel fixed-effects model is implemented to examine the effect of manager sentiment on stock liquidity. We conduct multiple robustness checks, including propensity score matching (PSM), instrumental variable (IV) estimation, and a two-step system generalized method of moments (GMM) approach. Additional cross-sectional and interaction-based heterogeneity analyses are also performed.

Findings

The empirical outcomes suggest that managers' optimistic sentiment positively impacts stock liquidity. This favorable relationship is robust even after conducting various endogeneity tests: PSM, IV methods, and system GMM. Furthermore, our study explores the role of CLC and demonstrates that the positive impact of managerial sentiment is only evident during the growth and maturity stages. The heterogeneity analysis reveals that this positive nexus is particularly substantial for smaller firms, those facing financial constraints, and companies lacking environmental, social and governance ratings.

Practical implications

The findings highlight the strategic importance of narrative disclosures for managers, investor relations teams and regulators and demonstrate how sentiment analytics can improve stock liquidity assessment and informed trading decisions.

Originality/value

To the best of our knowledge, this is the first study to examine the relationship between FinBERT-based managerial sentiment and stock liquidity, particularly in an emerging market context.

Keywords:

Manager sentiment, Stock liquidity, Corporate life cycle, Large language model, ESG

Link: https://doi.org/10.1016/j.frl.2026.109518
Abstract: 

This paper investigates the effect of firm-level climate risk exposure (FCRE) on investment efficiency using a comprehensive panel of non-financial firms listed on the National Stock Exchange of India between 2003–04 and 2022–23. We develop a novel FCRE measure by applying a Word2Vec-based natural language processing technique to firm-level Management Discussion and Analysis (MD&A) reports. Employing firm fixed effects estimations, the results indicate that higher climate risk exposure significantly increases investment inefficiency, constraining firms’ ability to achieve optimal investment levels. The adverse impact is further amplified in higher information opaque and pessimistic tone firms. The FCRE positively impacting the investment inefficiency through intensifying the market risk, financial constraints and lowering the CAPEX. Robustness tests, including propensity score matching, two-stage instrumental variable estimations, system GMM and Hackman two stage test, confirm that the findings are not driven by endogeneity. Our findings underscore the importance of climate risk in shaping corporate investment behavior and offer valuable insights for investors, managers, and policymakers seeking to integrate sustainability considerations into investment decision-making. 

Keywords

Climate risk exposure; Investment efficiency; Textual analysis; Corporate investment; Middle-income economy 

Link: https://doi.org/10.1016/j.frl.2025.107864
Abstract:
Abstract

This study examines how managerial sentiment shapes the relationship between macroeconomic uncertainty and stock liquidity. Using a FinBERT-based large language model to assess sentiment from management discussion and analysis (MD&A) disclosures and a customized macroeconomic uncertainty index for India, we find that increased uncertainty significantly reduces stock liquidity. Optimistic managerial sentiment alleviates this adverse effect, particularly in firms with higher information asymmetry. The results are robust to the endogeneity test, propensity score matching, and alternative sentiment and uncertainty measures. This study advances macroeconomic uncertainty research by being the first to explore how managerial sentiment moderates its deterrent effects on stock liquidity.

Keywords

FinBERT, Liquidity, Macroeconomic uncertainty, Managerial sentiment

Link: https://doi.org/10.1111/irfi.70016
Abstract:
This study examines the transmission of monetary policy shocks on stock market returns, liquidity, expected inflation, and inflation under varying economic policy uncertainty (EPU) levels in the Indian context. Using a Smooth Transition VAR model, we find that contractionary monetary policy increases illiquidity and decreases returns during the high EPU regime but has minimal effects during the low EPU regime. Additionally, monetary policy effectively curtails expected inflation and inflation in a low EPU regime than in a high EPU regime. The results emphasize monetary policy transmission via expectation channels over asset pricing channels. 

Keywords: Monetary policy, Stock liquidity, Economic policy uncertainty, Inflation, Indian Economy

Link: https://doi.org/10.1108/CAFR-05-2024-0055

Abstract

Purpose: This study examines the impact of firm-level climate risk exposure (FCRE) on firm stock liquidity by using a sample of Indian-listed firms from the FY 2003-2004 to 2022-2023. Further, it endeavors to investigate the moderating role of Environmental, social, and governance (ESG) disclosure in this relationship.

Design/methodology/approach: A novel text-based FCRE metric is introduced using a sophisticated Word2Vec model through a Python-generated algorithm for each firm and year based on the management discussions and analysis (MD&A) reports. The panel fixed effect model is used to study how FCRE affects stock liquidity.

Findings: The result shows that FCRE negatively affects firms’ stock liquidity, and the effect remains robust after addressing endogeneity concerns. In addition, we find that a high ESG disclosure rating significantly moderated the adverse effect of FCRE. Furthermore, our analysis reveals that investor sentiment, information quality, corporate life cycle and institutional holdings moderate the impact of FCRE on liquidity

Originality/Value: To the best of our knowledge, this study is an early study to explore the relationship between firm-specific climate risk exposure and stock liquidity using advanced machine learning techniques. It contributes to the existing literature by illustrating how climate risk can lead to adverse market reactions while highlighting the critical roles of corporate ESG practices, investor sentiment, and disclosure quality in influencing this relationship.

Practical implications: The study offers valuable insights for investors, managers, and policymakers on integrating climate risk into investment strategies, improving corporate climate governance, and shaping policies that incentivize sustainable corporate behavior.

Keywords: climate risk exposure, Stock liquidity, ESG, Textual analysis, investor sentiment

Paper type: Research paper

Link: https://doi.org/10.1108/IJAIM-08-2023-0206

Abstract

Purpose

This study aims to examine the impact of manager sentiment on the firm performance (FP) of Indian-listed nonfinancial firms. Further, it endeavors to investigate the moderating role of economic policy uncertainty (EPU) and environment, social and governance (ESG) transparency in this relationship.

Design/methodology/approach

A noble manager sentiment is introduced using FinBERT, a bidirectional encoder representation from a transformers (BERT)-type large language model. Using this deep learning-based natural language processing approach implemented through a Python-generated algorithm, this study constructs a manager sentiment for each firm and year based on the management discussions and analysis (MD&A) report. This research uses the system GMM to examine how manager sentiment affects FP.

Findings

The empirical results suggest that managers’ optimistic outlook in MD&A corporate disclosure sections tends to present higher performance. This positive association remains consistent after several robustness checks – using propensity score matching and instrumental variable approach to address further endogeneity, using alternative proxies of manager sentiment and FP and conducting subsample analysis based on financial constraints. Furthermore, the authors observe that the relationship is more pronounced for ESG-disclosed firms and during the low EPU.

Practical implications

The results demonstrate that the manager sentiment strongly predicts FP. Thus, this study may provide valuable insight for academics, practitioners, investors, corporates and policymakers.

Originality/value

To the best of the authors’ knowledge, this is the first study to predict FP by using FinBERT-based managerial sentiment, particularly in an emerging market context.

Keywords: Manager sentiment, Large language model, Firm performance, Economic policy uncertainty, ESG

Paper type: Research paper

Link: https://doi.org/10.1108/IJMF-12-2023-0617  

Abstract
Purpose – This paper investigates the relationship between managerial sentiment and corporate investment in emerging capital markets. Further, we begin with the assertion that the positive impact of managerial sentiment on corporate investment varies according to the corporate life cycle. Lastly, we investigate whether the relationship between managerial sentiment and corporate investment can be moderated by factors like (1) economic policy uncertainty/geo-political risk, (2) size of the firm, (3) financial constraint, (4) industrial competition, and (5) Environmental Social and Governance (ESG) rating.

Design/methodology/approach – This study has considered Indian listed companies (465 firms) for the period spanning from 2003–2004 to 2022–2023. This study constructs the managerial sentiment using a novel large language model-financial bidirectional encoder representation from the Transformers (FinBERT), as well as on management discussion and analysis reports. Then, we employ fixed effect regression to investigate the relationship between managerial sentiment and corporate investment. Additionally, we use propensity score matching, two-stage least squares instrumental variables, and a two-step system generalized method of moments approach for robustness tests.

Findings – The findings show a positive and significant relationship between managerial sentiment and corporate investment. Additionally, our results demonstrate that this relationship is evident only during the growth and maturity phase of the corporate life cycle. Moreover, uncertainty pertaining to the economy and geopolitical issues, firm size, financial health, industry dynamics, and ESG disclosure also play a crucial role in shaping the investment-sentiment relationship.

Originality/value – The study is unique because it determines the relationship between managerial sentiment and corporate investment by using the novel FinBERT model. In addition, we have introduced a corporate life cycle, which is an essential aspect of our study. Additionally, this research was conducted in an emerging market with more information asymmetry and weaker disclosure rules. Thus, other emerging markets can benchmark the outcomes.

Keywords:  Corporate investment, Managerial sentiment, Economic policy uncertainty, FinBERT model, ESG disclosure
Paper type: Research paper 

Link:https://doi.org/10.1108/SRJ-02-2024-0132

Abstract

Purpose – This paper aims to examine the relationship between environmental, social and governance (ESG) performance and text-based corporate innovation based on a sample of India’s ESG-disclosed companies from financial year 2011–2012 to 2021–2022. Further, it endeavors to investigate the moderating role of heightened climate policy uncertainty (CPU) in this relationship.

Design/methodology/approach – To verify these hypotheses, the authors first construct a corporate innovation index for India using a sophisticated natural language processing model on each firm-year’s management discussion and analysis reports. Next, the authors use a panel fixed effects model to examine how ESG performance impacts corporate innovation and its moderating and mediating components.

Findings – Empirical evidence suggests higher ESG performance bolsters text-based corporate innovation. After addressing endogeneity issues with the system GMM estimator and two-stage least square IV, incorporating additional control variables and using alternative innovation measurement, the baseline results remain unchanged. Next, the authors find this link is mediated by reducing information asymmetry, financial constraints and managerial myopia. The authors also observe that increased CPU favorably moderates the ESG-innovation nexus. Additionally, the heterogeneity research shows that ESG only positively impacts innovation in specific industries and firms in their growth and mature life cycle phases.

Practical implications – The results demonstrate that sustainable and ethical business practices can foster corporate innovation. Thus, this study may provide valuable insight for investors, managers and policymakers.

Originality/value – To the best of the authors’ knowledge, this is the first study to examine the relationship between ESG performance and text-based corporate innovation using a machine learning model.

Keywords: Corporate innovation, Text-based corporate innovation, Environmental, Social and governance, Textual analysis, Climate policy uncertainty, Corporate social responsibility

Paper type: Research paper

Link:  https://doi.org/10.3390/economies13020030 

Abstract

This study examines the impact of firms’ overall corporate policy risk on stock liquidity. This study constructs a novel overall corporate policies risk index (PRI) for firms by capturing risk embedded in managers’ different policy decisions, such as investment, financing, diversification, and cash management, by weighting each policy risk through the regression decomposition method. Using a large sample of 466 India-listed firms from the financial year 2003–2004 to 2022–2023, this study finds that there is a negative association between PRI and stock liquidity. The study further explores the information environment heterogeneity and finds that the adverse impact of a PRI is a more prominent firm that is hard to value or in a less transparent environment as compared to the transparent firms. Moreover, the adverse impact of PRI on stock liquidity is significantly more pronounced during financial crises, while its effect is less substantial during non-crisis periods. The robustness of these results is confirmed even after addressing endogeneity issues using various techniques, such as propensity score matching (PSM), two-stage least squares instrumental variable approach (2 SLS IV), and the system-generalized method of moments (System GMM).

Keywords: corporate policy risk; stock liquidity; information asymmetry; financial crisis