Information Leakages in the Green Bond Market

ArXiv ID: 2504.03311 “View on arXiv”

Authors: Unknown

Abstract

Public announcement dates are used in the green bond literature to measure equity market reactions to upcoming green bond issues. We find a sizeable number of green bond announcements were pre-dated by anonymous information leakages on the Bloomberg Terminal. From a candidate set of 2,036 ‘Bloomberg News’ and ‘Bloomberg First Word’ headlines gathered between 2016 and 2022, we identify 259 instances of green bond-related information being released before being publicly announced by the issuing firm. These pre-announcement leaks significantly alter the equity trading dynamics of the issuing firms over intraday and daily event windows. Significant negative abnormal returns and increased trading volumes are observed following news leaks about upcoming green bond issues. These negative investor reactions are concentrated amongst financial firms, and leaks that arrive pre-market or early in market trading. We find equity price movements following news leaks can be explained to a greater degree than following public announcements. Sectoral differences are also observed in the key drivers behind investor reactions to green bond leaks by non-financials (Tobin’s Q and free cash flow) and financials (ROA). Our results suggest that information leakages have a strong impact on market behaviour, and should be accounted for in green bond literature. Our findings also have broader ramifications for financial literature going forward. Privileged access to financially material information, courtesy of the ubiquitous use of Bloomberg Terminals by professional investors, highlights the need for event studies to consider wider sets of communication channels to confirm the date at which information first becomes available.

Keywords: Event Studies, Information Asymmetry, Abnormal Returns, Green Bonds, Bloomberg Terminal, Fixed Income

Complexity vs Empirical Score

  • Math Complexity: 3.0/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Street Traders
  • Why: The paper employs standard empirical finance methods like event studies and factor models (e.g., CAPM, Fama-French, Carhart) but presents no novel mathematical derivations; its rigor stems from a detailed, multi-year dataset of Bloomberg Terminal headlines and extensive statistical analysis of equity returns and trading volumes.
  flowchart TD
    A["Research Goal: <br>Examine impact of pre-announcement <br>information leakages on equity markets"] --> B["Data Collection: <br>2,036 Bloomberg News/First Word <br>headlines (2016-2022)"]
    B --> C["Identification Process: <br>Detect 259 instances of leaks <br>pre-dating public announcements"]
    C --> D["Analysis: <br>Event study on intraday/daily windows <br>Calculation of abnormal returns & volume"]
    D --> E["Sectoral Comparison: <br>Drivers: Non-financials vs Financials"]
    E --> F["Key Findings: <br>- Significant negative returns & <br>  volume spikes post-leak<br>- Leaks explain price moves better <br>  than public announcements<br>- Driver differences by sector<br>- Implications for event study methodology"]