Friday, November 10, 2023

Stocks for the Long Run, Sixth Edition

Jeremy Siegel recently wrote, with Jeremy Schwartz, the sixth edition of his popular book, Stocks for the long Run: The Definitive Guide to Financial Market Returns and Long-Term Investment Strategies.  I read the fifth edition nearly a decade ago, and because the book is good enough to reread, this sixth edition gave me the perfect opportunity to read it again.

I won’t repeat comments from my first review.  I’ll stick to material that either I chose not to comment on earlier, or is new in this edition.

Bonds and Inflation

“Yale economist Irving Fisher” has had a “long-held belief that bonds were overrated as safe investments in a world with uncertain inflation.”  Investors learned this lesson the hard way recently as interest rates spiked at a time when long-term bonds paid ultra-low returns.  This created double-digit losses in bond investments, despite the perception that bonds are safe.  Siegel adds “because of the uncertainty of inflation, bonds can be quite risky for long-term investors.”

The lesson here is that inflation-protected bonds offer lower risk, and long-term bonds are riskier than short-term bonds.

Mean Reversion

While stock returns look like a random walk in the short term, Figure 3.2 in the book shows that the long-term volatility of stocks and bonds refutes the random-walk hypothesis.  Over two or three decades, stocks are less risky than the random walk hypothesis would predict, and bonds are riskier.

Professors Robert Stombaugh and Luboš Pástor disagree with this conclusion, claiming that factors such as parameter and model uncertainty make stocks look riskier a priori than they look ex post.  Siegel disagrees with “their analysis because they assume there is a certain, after inflation (i.e., real) risk-free financial instrument that investors can buy to guarantee purchasing power for any date in the future.”  Siegel says that existing securities based on the Consumer Price Index (CPI) have flaws.  CPI is an imperfect measure of inflation, and there is the possibility that future governments will manipulate CPI.

Siegel continues: “Additionally, the same caution about the interpretation of historical risk that applies to stocks also applies to every asset.  All assets are subject to extreme outcomes called tail risks or black swan events.”

Rating Agencies’ Role in the Great Financial Crisis of 2008-2009

Siegel offered a partial defense of rating agencies who failed to see that mortgage-related securities were risky:

“Standard & Poor’s, as well as Moody’s and other ratings agencies, analyzed these historical home price series and performed the standard statistical tests that measure the risk and return of these securities.  Based on these studies, they reported that the probability that collateral behind a nationally diversified portfolio of home mortgages would be violated was virtually zero.  The risk management departments of many investment banks agreed with this conclusion.”

Standard statistical tests are notoriously unreliable when it comes to extreme events.  Flawed math might say an event has probability one in a trillion trillion when its true probability is one in ten thousand.  The world is full of people who use statistical methods they don’t understand, and there are others who use statistics to get the answer they want for personal gain.


I still agree with my conclusion in reviewing the previous edition: This book is very clearly written and offers powerful evidence for the advantages of investing in stocks. I highly recommend it to investors.