Critical Areas of my Research
My research is driven by a central question: How does information shape the behavior of firms and capital market participants in a global, technologically-advancing economy? I investigate the determinants and consequences of corporate disclosure choices and governance structures, with a particular focus on how new forms of reporting and data can enhance transparency and market efficiency.
My completed work and future interests can be broadly categorized into the following areas:
Corporate Reporting & Disclosure Quality
A primary focus of my research is understanding what firms choose to disclose—both voluntarily and mandatorily—and how the quality of that information creates value. My work in this area has investigated the voluntary adoption of Integrated Reporting (IR) and its association with firm performance, the value-relevance of non-financial disclosures like Intellectual Capital, and how a firm’s commitment to holistic reporting can influence financial reporting integrity by reducing earnings manipulation. This research stream seeks to understand the evolving landscape of corporate communication and its tangible impact.
Capital Markets & Corporate Governance
This research area examines the capital market consequences of corporate actions and the effectiveness of governance mechanisms. I have explored classic market puzzles, such as the long-run underperformance of Initial Public Offerings (IPOs) in an emerging market context. Furthermore, I have investigated how internal governance structures, such as board composition and ownership, serve as critical drivers of firm value. This work bridges the gap between corporate policy and market outcomes.
Future Research: AI & Unstructured Data
As I embark on my PhD studies, my objective is to push the boundaries of empirical accounting research by leveraging unstructured data and advanced analytical techniques. My future agenda is focused on using new data sources to answer fundamental questions in capital markets and corporate governance. I am particularly interested in applying machine learning and Natural Language Processing (NLP) for sentiment analysis of complex corporate narratives. A novel avenue I am keen to explore involves using the advanced reasoning capabilities of Large Language Models (LLMs) to analyze regulatory filings and predict compliance.