©Photo: Dettmar
Hello, I'm Sasan Mansouri. I am currently an Assistant Professor of Digitalization and AI in the Department of Accounting and Auditing at the University of Groningen, Faculty of Economics and Business. Additionally, I maintain an affiliation with the IWH - Halle Institute for Economic Research as a Junior Researcher in the Data Science in Financial Economics group.
Before my current position at the University of Groningen, I was an assistant professor of finance at Goethe University in Frankfurt. My work spans across various domains, including financial data science, information intermediaries, entrepreneurial finance, and sustainability. I utilize a wide array of machine learning techniques, such as natural language processing, to investigate the dynamics of information transmission in financial markets, focusing on the impact of corporate disclosures and the role of information intermediaries like equity analysts and media outlets.
Outside of academia, I find joy in coding, especially in ML. My hobbies extend to bouldering, hiking, swimming, and reading. You can explore my reading list here.
Sincerely,
Sasan Mansouri
Download my CVAbstract: This study examines the relationship between firms' willingness to share value-relevant information and media coverage. Results indicate that firms reluctant to provide such information receive less coverage, particularly from professional business media. A poor information environment limits media's ability to generate new information but not dissemination of existing information. These findings challenge the idea that audience demand dictates media coverage, emphasizing supply-side factors and revealing complex dynamics between firms and media in shaping the information environment.
Abstract: Context specific language or jargon helps, by definition, to efficiently and precisely transfer information. However, due to its complex nature, jargon might also be a tool to obfuscate information. This paper studies whether jargon is used in verbal firm disclosures to obfuscate or to efficiently transfer information. We observe that, within the Q&A of earnings conference calls, managers use less jargon in responses to tougher questions, and in calls after a quarter of bad success. Moreover, markets interpret the lack of precise information as a bad signal: we find lower cumulative abnormal returns and a higher implied volatility following earnings calls where managers use less jargon. These results support the argument that an excessive use of non-factual language is perceived as blathering that retards the reduction of information asymmetries.
Abstract: This paper investigates the impact of precise language on market efficiency by examining the interplay between regulatory language simplification, as imposed by the Plain Writing Act of 2010, and information asymmetries in financial markets. We posit that financial jargon, while often criticized as complex, plays a pivotal role in facilitating efficient information dissemination within the market. Analyzing earnings conference call text data, we employ an instrumental variable event study framework to evaluate the consequences of the Plain Writing Act. Our findings suggest that the Act's promotion of plain language usage results in a reduction of financial jargon. Paradoxically, this reduction in jargon is associated with a decrease in market efficiency, implying that the Act may inadvertently hinder information flow and impair the market's price setting mechanism.
Abstract: Using a novel measure for analysts' attention during earnings conference calls, this paper studies how markets discipline banks. We consider two groups of banks: a treated group with implicit bail-out guarantees and an untreated group without such guarantees. Our analysis focuses on the information that analysts request from banks, which we classify using DebtBERT, a specifically trained large language model. We find that analysts increased their scrutiny post-global financial crisis. This increased attention affects banks' abnormal stock returns in the short-term and leverage in the long-term, which is especially notable in banks lacking bail-out guarantees. This result suggests a moral hazard problem, where investors strategically discipline banks based on their perception of bail-out guarantees. Our findings have important implications for regulatory and policy decisions aimed at promoting transparency and stability in the banking sector.
Abstract: This paper presents evidence for a regulatory stringency channel through which firm emissions affect firm value. Using the Paris Agreement as an exogenous shock to expected future environmental regulation, we show that high-polluting firms located in states with a high probability of adopting stricter environmental regulations are associated with lower realized returns. We show that this effect is strongest in states with stricter climate policy enforcement. These results suggest that high-polluting firms are at risk of facing additional regulatory stringency after large natural disasters, as citizens affected by frequent natural disasters may push for stricter environmental regulations in their state. Understanding the channels that translate policy change into investors (i.e. firm owners) behaviour is particularly relevant for the development of effective (climate) policy.
Here you can find more details about my teachings.
You can find the QIS page here. The syllabus and course materials are in OLAT.
Please feel free to contact me to discuss possible bachelor/master thesis topics. You can find the guidelines for writing a thesis in our chair in this document.
Duisenberg Building (801)
Nettelbosje 2, 9747 AE Groningen, NL
