Ziehms & Schwartz

Thought Leadership

A conversation with Stephen Penman (webcast)

Stephen Penman is the George O. May Professor Emeritus of Financial Accounting in the Graduate School of Business, Columbia University, a position that was previously held by Benjamin Graham. Penman is also co-director of the Center for Excellence in Accounting and Security Analysis at Columbia.

We will discuss approaches to the valuation of firms, his recent book Financial Statement Analysis for Value Investing, and how the residual income method may be relevant to the valuation of damages. Read More

Forthcoming 10 September 2025

 

Bias in International Arbitration – the Expert Perspective (article)

Chaitanya Arora, John Darlison, Heiko Ziehms
Forthcoming August 2025

 

M&A Disputes: Does a booming stock market lower the efficacy of financial statement warranties? Faculty of law blogs, University of Oxford

Oxford Business Law Blog · Nov 27, 2024
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M&A Disputes: How They Happen, How to Resolve Them, How to Avoid Them (book)

Heiko Ziehms, Wolters Kluwer · November 2023
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Post-completion M&A Disputes: Two Paths to Resolution (book chapter)

John Hudson, Kami Zargar and Heiko Ziehms, GAR – The European Arbitration Review · 2024 – Oct 15, 2023
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A Record-Breaking Year in M&A: The Consequences for Damages in Post-M&A Dispute Resolution in Arbitration

Heiko Ziehms and Anna Baird, Kluwer Arbitration Blog · Jun 16, 2022
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M&A Disputes and Completion Mechanisms: A Commercial and Financial Perspective (book)

Heiko Ziehms, Wolters Kluwer · 2019
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Research Project

Predictive artificial intelligence will affect the work of quantum and forensic experts in profound ways over the coming years. We are creating models for ex-ante assessments of accounts warranty breaches and fraud in M&A transactions.

Our analysis identifies patterns in financial statements, the organisational structure of the acquired firm, or the M&A process that are associated with breaches of financial statement and other warranties and predict the probability of material accounting misrepresentations.