Andreu’s blog

Book review. Financial Shenanigans (Third Edition) by Howard M. Schilit and Jeremy Perler

I saw this book mentioned in Patrick McKenzie's newsletter Bits about Money and I immediately thought about something that I read in the report published by Norges Bank Investment Management (NBIM) called 20 years with investing in equities. The mandate of NBIM is to invest in equities in all markets, a kind of index fund encompassing the whole world. NBIM increases the returns of its fund by lending some equities to short sellers, but also by underweighting some securities in its portfolio. Specifically shares from companies that it suspects of engaging in fraudulent accounting. I thought about what kind of techniques the fund may use to detect fraud and this book gives a possible answer.

I read the third edition of the book. I believe the fourth edition is already out, but it was not available through the Norwegian public library system. The book is divided into sections for different kinds of manipulations, manipulations of the Earnings statement, manipulations of the Cash Flow statement and manipulation of other Key Metrics. In the introduction the book also talks about the risks of bad governance. Through the book it becomes clear that many accounting manipulations to show better earnings or cash flow are quite easy to spot if one starts looking for them. Typically, a company may change criteria for booking revenue or expenses in order to present better earnings. Such changes may be detected by observing that other accounts do not change in a way that is consistent with reported earnings (for example it appears that it takes longer for the company to get paid) or simply by reading disclosures in the footnotes.

Being able to detect a manipulation does not necessarily mean that one can profit from it. The profits to be made by short selling shares of companies with shady accounting are limited and there is no guarantee that they will be realized in the short term.

Accounting manipulations present a problem for index investing. By definition, if a portfolio follows an index, the manager does not act on information regarding individual companies. The fund just tries to track the index as closely as it can. If the index contains some bad companies, in the long term, it will result in a worse performance than if those companies had been excluded. It may be different in the short run. The bad companies may fool most investors and the performance of the index may be better with them than without.

The situation of the Norwegian pension fund is clearly a case where the long run is more important. The fund invests in thousands of companies and I wonder how do they manage to screen them all (the fund is known for having a relatively small staff). I believe they may use some kind of automation. Before reading the book, I thought they might need lots of non financial data to detect fraud, but now I expect that the bulk of the data comes from financial rapports that the companies provide themselves and that are available online in a single place, like EDGAR fillings, for example. Accounting data from the financial statements seems quite straightforward to process and by itself gives enough information to detect many kinds of manipulations. Extracting information from the footnotes seems more complicated, but not entirely impossible. I can imagine a system using natural language processing (NPL) and machine learning. There must be enough historical cases of fraud to train the system or at least to detect cues that may indicate suspicious activity, like changes in criteria used to record transactions in the financial accounts.

The book starts with failures of corporate governance and I think this is a very important topic. Environmental, Social and Governance (ESG) investing is becoming more widespread. The Norwegian Pension Fund, for example, is prohibited to invest in certain companies, like coal producers. The theory is that ESG investing is not only morally right, but also more profitable in the long run. I have my doubts with regards to the E and S part, but as the book shows, bad governance does indeed pose a risk of bad returns. A recent example, not from the book, is Facebook, which allegedly overpaid FTC fine by billions in order to protect Mark Zuckerberg from personal liability. As CEO of Facebook, Zuckerberg was the ultimate responsible for users data. A board that truly represented the interests of the shareholders, would have tried to minimize the FTC fine and let the CEO face charges, even possibly questioning his ability to continue in the role. But Facebook (now Meta) has a dual share class structure, meaning that Zuckerberg's shares, although not a majority, have more voting rights than the rest, so he basically can run the company unchecked. This is a bad governance practice.

Overall I liked the book. It seems like a practical resource if one is considering building some kind of automated system for detecting corporate fraud, or simply if one needs to do due diligence on a company's financials. The writing tries to be light and funny at times, but I found some of the jokes to be dated. Maybe in the fourth edition they have been changed or eliminated altogether. But again, no one will read the book for its literary quality, and the practical content is very good indeed.

Last updated: 2021-12-27