Special Issue – Measuring What Matters: Alternative Data, Sentiment, and ESG Signals in Financial Markets

Measuring What Matters: Alternative Data, Sentiment, and ESG Signals in Financial Markets   Background and Motivation

ESG investing has moved from niche to mainstream, yet its empirical foundations remain contested. Conventional ESG ratings produced by a small number of incumbent providers are well documented to disagree substantially with one another, to lag material events, and to reflect disclosure quality as much as underlying sustainability performance. At the same time, the volume of ESG-relevant information generated outside formal disclosure channels has grown substantially: corporate sustainability reports, earnings call transcripts, regulatory filings, social media, satellite imagery, supply chain records, and consumer review platforms all carry signals that ratings agencies either cannot incorporate at scale or choose not to.

This Special Issue takes a measurement-first perspective. It proceeds from the view that progress in sustainable finance depends less on theoretical refinement and more on better, faster, and more objective ways to extract ESG-relevant signals from the expanding universe of alternative data sources and translate those signals into actionable insights across equity, fixed income, credit, and multi-asset financial markets. The guest editor invites original empirical and applied research that develops, evaluates, or deploys such methods in the context of ESG assessment, portfolio construction, or related investment decisions.

Scope

The special issue welcomes submissions across the following areas. This list is indicative, not exhaustive.

ESG Signal Extraction and Measurement

• NLP and large language model (LLM) applications to sustainability reports, proxy filings, regulatory disclosures, and corporate communications
• Sentiment analysis of earnings calls, analyst reports, media coverage, and social platforms with respect to ESG themes
• Satellite and geospatial data for environmental monitoring (emissions, deforestation, water use, land cover change)
• Image and video analysis for supply chain, physical asset, and labour practice assessment
• Audio-based analysis of corporate communications for ESG-relevant signals

Greenwashing Detection and Disclosure Quality

• Computational methods for identifying inconsistency between ESG claims and observable outcomes
• Textual analysis of greenwashing rhetoric across disclosure types and regulatory regimes
• Market and reputational consequences of greenwashing events identified via alternative data
• Regulatory developments and their measurable effects on disclosure behaviour (ASIC, SEC, FCA, and ESMA contexts are particularly welcome)

ESG Ratings: Disagreement, Bias, and Improvement

• Empirical analysis of rating disagreement and its drivers
• Alternative or hybrid rating constructions using non-traditional data inputs
• Timeliness and nowcasting of ESG assessments relative to incumbent ratings

Portfolio Construction and Asset Pricing

• ESG sentiment as a factor in equity, fixed income, and multi-asset portfolios
• Portfolio integration of alternative ESG signals: construction methodology, turnover, and implementation costs
• ESG investing in fixed income and sovereign debt contexts
• Carbon risk, physical climate risk, and transition risk in portfolio frameworks
• Performance attribution and risk decomposition for ESG-tilted strategies

Investor Behaviour and Market Dynamics

• Retail and institutional investor responses to ESG sentiment and controversy events
• Flow dynamics around ESG fund categories in response to data and media signals
• Price discovery and information efficiency around ESG-relevant alternative data releases

What the Special Issue Is Not Looking For

To assist authors in self-selecting appropriately, the following are outside the scope of this issue:

• Purely theoretical models of ESG preferences or equilibrium without empirical application
• Papers in which ESG is incidental rather than central — for example, a general ML forecasting paper that includes one ESG variable
• Papers focused exclusively on ESG fund flows or manager behaviour without a data or measurement dimension
• Normative or prescriptive policy analysis without empirical grounding

Submission Guidelines

Manuscripts should be prepared in accordance with the standard author guidelines for Applied Finance Letters, available at here

Authors are asked to:

• Submit via the journal’s manuscript management system, selecting the Special Issue designation “SI: Measuring What Matters” from the drop-down menu
• Include a cover letter identifying the primary ESG topic addressed, and the primary data source(s) used
• Confirm that the work is not under review elsewhere

All submissions will undergo double-blind peer review. Desk rejection will be applied to manuscripts that fall materially outside the stated scope or that do not meet the journal’s standards for empirical rigour and clarity of exposition.

Key Dates

Submission deadline: 1 November 2026

 

Guest Editor

Vitali Alexeev  |  University of Technology Sydney (UTS)

Research interests: ESG and sustainable finance, portfolio construction, sentiment analysis

Contact for scope enquiries (not submissions): vitali.alexeev@uts.edu.au