Each week, Daniels is featuring a researcher who conducts meaningful research that impacts their field and the wider community. Learn more about their work in Q&As with the Daniels Research team and email them to nominate yourself or a colleague for a future Q&A.
Shahram Amini
Shahram Amini is an assistant professor of finance at the University of Denver’s Daniels College of Business. His areas of research include corporate investment efficiency, behavioral finance, corporate misconduct, capital structure, payout policies, mergers and acquisitions, IPO markets, and machine learning. Shahram has taught several courses including Financial Modeling, Investments, Financial Concepts and Skills, and International Finance, for which he has received teaching excellence awards.
What is your area of research?
I specialize in the study of corporate financial policies and their alignment with shareholders’ interests, with a particular focus on corporate investment efficiency. Theoretical and mathematical models provide predictions for optimal investment levels, and I investigate instances of deviation between these predicted values and actual investments, conceptualizing such variance as investment inefficiency. My research delves into the analysis of various factors at the firm, macro and managerial levels, aiming to understand their impact on investment inefficiency.
How do you integrate your research into the classroom?
I consistently integrate examples from my research into my classroom sessions. The nature of my research demands proficiency in coding, data analysis and financial literature. For instance, in my data analysis classes, I discuss my research on investment efficiency and guide students through the replication of the regression models employed in my papers. This undertaking involves working with real financial data, executing data cleaning and manipulation, and utilizing coding to construct control variables. The feedback I receive from these exercises is highly positive, as students value the rigor and practical skills gained in my classes.
Engaging with PhD students, particularly in conversations about the tools and research I’m utilizing, often reveals shared research interests. Currently, one of my focal points involves employing text analysis to comprehend the correlation between public comments on X (formerly Twitter) and other social media platforms, and CEOs’ financial policies. During a brief exchange at their monthly receptions, I discovered that one PhD student shares a keen interest in text analysis and possesses relevant experience in this field. Our discussions have evolved into exploring the potential for collaboration, with the prospect of co-authoring a research paper together.
What do you see as the impact of your work on the business community?
In Finance 101, it’s emphasized that managers should strive to maximize shareholders’ value, and my research centers around precisely that principle. The overarching objective is for managers to examine my findings and enhance their investment decisions, refining aspects such as capital structure and payout choices to achieve greater efficiency. Ultimately, this approach aims to elevate the valuation of investments for ordinary shareholders, including individuals like you and me. My aspiration is that the impact of my research extends its benefits to companies, managers, employees and shareholders alike.
What are you interested in right now, and what is next on your research agenda?
I plan to continue my research within the investment efficiency domain. Additionally, I aim to delve into the connection between CEO characteristics and investment efficiency. Although the exploration of CEO characteristics and financial policies, encompassing investment levels, is a well-explored area, my intention is to make a distinctive contribution by focusing on the relationship between CEO traits and investment efficiency, rather than merely investment levels.
Going deeper into text analysis presents an intriguing prospect for exploring new data sources. This realm of research holds numerous practical applications, offering valuable insights for industries such as hedge funds and mutual funds. By leveraging text analysis, these entities can effectively monitor platforms like Reddit or Stockwitz, extracting meaningful information from posts to gauge investors’ sentiments about different stocks and inform judicious investment decisions.
Moreover, this line of research extends its utility to the analysis of quarterly earnings calls, where CEOs and CFOs expound on their firms’ prospects and competitors. Investors, in turn, can employ text analysis to assess the tone of these discussions, discerning whether managers convey confidence or utilize hedging language. Such analyses contribute to predicting the future performance of the firm, providing a nuanced approach to investment decision-making.