Navigating the Empirical Finance Exam

The empirical finance exam tests your ability to apply statistical methods to real-world financial data. Expect a blend of theoretical understanding and practical application, requiring you to demonstrate proficiency in econometric techniques and their relevance to finance.

Key Topics to Master

Regression Analysis: This is fundamental. Understand ordinary least squares (OLS) estimation, its assumptions, and potential violations (heteroscedasticity, autocorrelation, multicollinearity). Be prepared to address these violations using appropriate techniques like weighted least squares, Newey-West standard errors, or instrumental variables.

Time Series Analysis: Crucial for analyzing financial markets. Study ARIMA models for forecasting, stationarity tests (e.g., Augmented Dickey-Fuller), and cointegration analysis to identify long-run relationships between variables. Understanding GARCH models for volatility estimation is also essential.

Panel Data Analysis: Become familiar with fixed effects and random effects models and the Hausman test for choosing between them. Understand the benefits of using panel data to control for unobserved heterogeneity.

Event Study Methodology: Learn how to assess the impact of specific events (e.g., earnings announcements, mergers) on stock prices. Understand the event window, the estimation window, and how to calculate abnormal returns.

Asset Pricing Models: The exam might ask you to test asset pricing models like the Capital Asset Pricing Model (CAPM) or Fama-French three-factor model using regression analysis. Be prepared to interpret the results and discuss their implications.

Exam Strategies

Practice, Practice, Practice: Solve past exam papers and work through practice problems to solidify your understanding. Focus on applying the concepts rather than just memorizing formulas.

Data Handling: Be comfortable with data manipulation using statistical software like R, Stata, or Python. You might be asked to clean, transform, and analyze a dataset.

Interpretation: Don’t just run regressions; understand what the results mean in a financial context. Can you explain the economic significance of your findings?

Critical Thinking: Be prepared to discuss the limitations of your analysis and potential biases. Acknowledge alternative interpretations of the results.

Assumptions and Diagnostics: Always state your assumptions explicitly and check for violations. Justify your choices of models and techniques.

Example Question Types

• “Describe the potential biases in estimating the effect of a firm’s R&D spending on its stock price using OLS regression.”
• “Explain how to test for cointegration between two time series.”
• “Design an event study to analyze the impact of a new regulation on the banking sector.”

By mastering the key concepts and practicing diligently, you can confidently tackle the empirical finance exam and demonstrate your expertise in applying econometric methods to financial research.