Courses & Doctoral Training

Foundations of Accounting & Valuation

A comprehensive introduction to accounting and valuation: how to read, interpret, and analyze the balance sheet, income statement, and statement of cash flows, and how to apply valuation techniques such as discounted cash flow and risk/return analysis to make informed investment, credit, acquisition, and business decisions. The course is taught through interactive lectures and real-world cases built on corporate annual reports and financial statements.

I teach it to Yale College undergraduates (ACC 270) and to graduate students from across the university, including the Schools of Public Health and the Environment (MGT 502).

The Private Firm CFO

Private firm finance is different: no market pricing, no analyst coverage, no mandated disclosure. This course examines the CFO role at private, entrepreneurial companies, following a company’s lifecycle from formation through exit — financial infrastructure, capitalization and equity compensation, driver-based forecasting, board reporting, revenue recognition, fundraising, and exits.

Students work through two cases and two problem sets, and leave with work they keep: a capitalization table from formation through Series A, an operating forecast built with AI tools, a board memo on equity compensation and its tax implications, and a critique of a board reporting package.

Seminar in Accounting Research II: Empirical Papers

A doctoral seminar (co-taught with Aneesh Raghunandan) that surveys empirical financial accounting research and trains students to evaluate and produce it, through paper presentations, a replication exercise, and a full referee report. Topics span disclosure and its regulation, governance of the executive and the board, earnings management, analysts, AI/ML in financial reporting, ESG, and a dedicated session on labor and accounting — the intersection of labor economics and accounting that anchors much of my own work.

I also advise doctoral students at Yale SOM, currently as dissertation co-chair for Ping R. Gong, and teach a PhD module on using AI tools in empirical research, detailed on the AI & Research page.