Book review: The 17.6 Year Stock Market Cycle

I have been invited to review this book, which intends to connect the big stock market panics into one cycle. Kerry Balenthiran, the author of the book, studied mathematics and works as a financial consultant.

I have kept to the principle of reading a book twice before giving a review. At about 8o pages it is a book that can be read in one go.

In the opening chapters of the book a variety of known business cycles are presented, like the Kitchin and the Kondratieff cycles. The author points to long term commodity cycles and to human psychology as the main reasons for cycles in the economy and in the stock markets. He does not claim to have invented this 17 to 18 year cycle, indeed such a cycle has been proposed by various economists. The new idea that is being proposed is in the intermediate term turning points that supposedly occur within this longer 17.6 year cycle.

More specifically, the cycle gets divided into 2.2 year portions and in chapter 4 that concept is explained in further detail. An interesting detail is that the author considers a bull and a bear version of his 17.6 year cycle, and they alternate in what is basically a 35 year cycle. I don’t know why the book was not called 35 year cycle, but maybe it was considered that 17 year cycle sounds better as a book title (like in sweet 17).

Reading further we also learn that the cycled is considered in a very flexible way, especially in the bearish part where the lowest low of the cycle does not have to come at the end, and it can come as much as 9 years before the official end of a bearish 17 year cycle. I think that will have some readers question the usefulness of this cycle. The book continues with detailed descriptions and study of five 17 year cycles starting from 1929, with an emphasis on the 2.2 year segments. But in more than a few parts it feels like a curve-fitting exercise where the lows and highs seem chosen to fit the proposed cycle. The normal principle in science is to change our theories to fit the data, rather than mold our data to fit the theory. Sure, the author mentions regularly that it is an idealized cycle, and even writes: “It is easy to identify bull markets in hindsight..”, but readers are likely to wonder how to use this cycle without the benefit of hindsight.

In the 5th chapter of the book the cycle is applied and translated into stock trading advice for the coming years all the way to year 2053. The author contends that based on the idealized cycle we can “forecast with a high degree of confidence” where market lows can be expected. But where does that confidence come from? The book doesn’t have any chapter on how confident we can actually be in this pattern. That’s something I would like to see added in a next version of the book. Let’s not forget that less than three complete 35 year cycles have been properly observed. The question if this pattern also shows up in stock markets that have a low correlation with the US (for example Japan and China) has not been asked. We would probably be more confident if the pattern appeared in other markets too. And as a mathematician the author can probably say something about the likelihood that this pattern is genuine, rather than an artifact of random chance. It is also not considered that while this pattern may be valid, it could be only the most common pattern among two or three variations. It could have a cousin brother that has not been seen since the 1800s. Several good chapters could have been written on these questions and that would have made it a better book. Unfortunately the reader has to do his own guessing on that point.

All in all, I think the book does a good job at laying out some well known economic cycles, and presents an interesting hypothesis with an elegant pattern that tries to connect them. And in a field like economics and stock market, which are not exact science, we can allow cycles to have a few misses here and there. We shouldn’t expect a perfect match with any proposed cycle. But the author of this book appears to be too optimistic that this pattern is for real and will keep showing up, and hasn’t done much to determine how much confidence we can have in it. As such the book risks becoming an example of making conclusions based on too few observed cycles, also known as the law of small numbers. A bit more skepticism would have been more convincing to me, and I hope the author can add a few chapters to answer some questions that readers will be left with if they read it.

Be well,

Danny