The indicative module outline is as follows:
Data-Driven Corporate Strategy
This module provides a rigorous and data-driven oriented treatment of empirical corporate finance, bridging the theoretical frameworks of corporate finance with the quantitative methods and empirical evidence used to test and refine them. The module trains students to think as researchers and critical consumers of empirical evidence, equipping them with the tools to evaluate causal claims, interpret econometric findings, and engage independently with the academic literature in corporate finance. The module draws extensively on research datasets and students will develop hands-on experience in constructing and analysing large-scale corporate finance datasets using the R language. By combining methodological rigour with substantive depth, the module prepares students for doctoral study, advanced financial research roles, and careers in investment management, consulting, and regulatory bodies where the ability to critically evaluate empirical evidence is increasingly valued.
Upon successful completion, students will be able to:
- Explain and critically evaluate the methodological foundations of empirical research in corporate finance.
- Construct, clean, and analyse large-scale corporate finance datasets
- Critically evaluate the empirical evidence on core corporate finance topics and empirical methods used in landmark published studies.
- Apply text-based analytical methods to corporate financial disclosures.
- Design, execute, and present an independent empirical research project in corporate finance.
13 thematic units across the semester.
Foundations of Empirical Research in Corporate Finance: The role of empirical evidence in corporate finance, the distinction between correlation and causation, the identification problem, observational versus experimental data, the credibility revolution in empirical finance, an overview of major data sources and merging data from major financial databases, variable construction procedures and sample selection criteria consistent with best practice in the empirical corporate finance literature, an introduction to research design in corporate finance.
Econometric Applications on Corporate Finance Research I: Panel data methods and their application in corporate finance, fixed effects and random effects estimators, the within transformation, clustered standard errors and their importance in corporate finance settings, the Hausman test, and the handling of unobserved heterogeneity in firm-level panel regressions, with applications in R and Python.
Econometric Applications on Corporate Finance Research II: The difference-in-differences estimator and its assumptions, parallel trends and pre-treatment tests, staggered DiD designs and recent developments in heterogeneous treatment effects, the instrumental variables estimator and the search for valid instruments in corporate finance, regression discontinuity designs and their application to governance and financing research, with replication exercises from published studies.
Empirical Evidence on Capital Structure: The determinants of leverage in the cross-section and over time, testing the trade-off theory and pecking order theory empirically, the Rajan and Zingales (1995) leverage regressions, dynamic capital structure adjustment models and the speed of adjustment literature, market timing and the Baker and Wurgler (2002) study, and the empirical challenges of identifying causal effects in capital structure research.
Investment, Financing Constraints, and the Q Theory: Tobin's Q and its measurement, the Fazzari, Hubbard, and Petersen (1988) investment-cash flow sensitivity framework, the Kaplan and Zingales critique, measures of financial constraints (KZ index, WW index, SA index), the real effects of financial constraints, and recent advances in identifying the causal effect of financing frictions on corporate investment.
Empirical Evidence on Payout Policy: Testing the dividend irrelevance proposition empirically, the determinants of dividend policy in the cross-section, the causal effect of dividends on firm value using natural experiments, share repurchases and their motives, the substitution hypothesis, payout flexibility, and the empirical literature on special dividends and dividend initiations and omissions.
Event Studies and the Market for Corporate Control: The event study methodology, abnormal return calculation using the market model, cumulative abnormal returns, statistical inference in event studies, the empirical evidence on announcement returns in mergers and acquisitions, acquirer and target returns, deal characteristics and their cross-sectional determinants, long-run post-merger performance, and the methodology of long-run event studies using buy-and-hold abnormal returns and the calendar-time portfolio approach.
Corporate Governance and Executive Compensation: Measuring corporate governance empirically, evidence on board composition, ownership structure, CEO pay-performance sensitivity, and shareholder activism, methodological challenges of establishing causal relationships in governance research, governance indices (G-index, E-index, ISS ratings), the Gompers, Ishii, and Metrick (2003) study and its replications and critiques, board composition and firm performance, the causal effect of board independence using natural experiments, executive compensation structures, CEO pay-performance sensitivity, the Jensen and Murphy (1990) study, managerial entrenchment and its consequences, and the empirical literature on shareholder activism and hedge fund activism.
Initial Public Offerings and Seasoned Equity Offerings: The empirical regularities of IPOs including underpricing, the winner's curse, and hot issue markets, the Ritter (1991) long-run underperformance study, theories of underpricing and their empirical tests, seasoned equity offerings and the adverse selection problem, the announcement effect of SEOs, and rights issues versus book-built offerings in international markets.
Text-Based Analysis in Empirical Corporate Finance: The role of textual disclosures in corporate finance research, dictionary-based sentiment analysis using the Loughran-McDonald financial dictionary, the analysis of earnings call transcripts and annual report narratives, topic modelling using LDA and BERTopic, FinBERT and transformer-based approaches to financial text classification, measuring managerial tone, uncertainty, and readability, and applications to earnings management, information asymmetry, and corporate governance research.
Cross-Country and International Corporate Finance: The role of legal origin and investor protection in shaping corporate finance outcomes, the La Porta, Lopez-de-Silanes, Shleifer, and Vishny (LLSV) framework, cross-country evidence on capital structure, dividends, and ownership concentration, the empirical challenges of international corporate finance research including accounting differences and data availability, and recent evidence on the convergence of corporate governance practices across countries.
Research Design and Independent Project Workshop: Formulating a research question in empirical corporate finance, identifying an appropriate identification strategy, sourcing and constructing the dataset, variable definition and sample selection, econometric specification and robustness checks, presenting and defending empirical findings, academic writing conventions in corporate finance, and an introduction to the publication process and the structure of leading corporate finance journals including the Journal of Finance, Journal of Financial Economics, and Review of Financial Studies.
Description of the assessment process
Assessment Language, Assessment Methods, Formative or Summative, Multiple Choice Test, Short Answer Questions, Essay Development Questions, Problem Solving, Written Assignment, Report/Report, Oral Examination, Public Presentation, Laboratory Paper, Clinical Patient Examination, Artistic Interpretation, Other/Other
Explicitly defined assessment criteria and if and where they are accessible by students are mentioned.
The module assessment language is in English and students are expected to exhibit the required level of proficiency.
The assessment of the course consists of:
Midterm Exam (40%, problem solving)
Final exam (60%, problem solving)
The evaluation criteria across modes of assessment include the following:
Demonstration of key knowledge related to the content of course
Demonstration of an ability to apply the knowledge in a given problem or case study
Critical ability evident in applying appropriate methods/knowledge in a given case and/or developing theory-based and literature based arguments.
Structure and presentation
Use of English language
More detailed assessment criteria will be provided to you in the module handbook document or posted on the course webpage, if deemed necessary.
- Brealey, R.A., Myers, S.C., Allen, F. and Edmans, A. (2025) Principles of Corporate Finance. 14th edn. McGraw-Hill.
- Brooks, C. (2019) Introductory Econometrics for Finance. 4th edn. Cambridge University Press.
- Damodaran, A. (2014) Applied Corporate Finance. 4th edn. John Wiley & Sons.
- James, G., Witten, D., Hastie, T. and Tibshirani, R. (2023) An Introduction to Statistical Learning with Applications in R. 2nd edn. Springer.
- Wickham, H. and Grolemund, G. (2023) R for Data Science. 2nd edn. O'Reilly Media.
- Wooldridge, J.M. (2020) Introductory Econometrics: A Modern Approach. 7th edn. Cengage Learning.
- Selected academic papers for discussion will be also provided by the instructors in each session.
- Other library sources, including journal articles accessible through the Library, as assigned by the instructor.