K-Waves and Debt Cycles and Bear Markets, Oh My!

Defensive Investing Part 3, can long wave economic theory help predict market timing?

Should big waves influence investment decisions? Image credit Jason Jacobs (CC BY 2.0)

In Part 1 of this series on defensive investing, I showed two case studies; a rookie mistake versus beginner’s luck. In Part 2, I showed how the hubris from beginner’s luck led to losing money by preparing for a correction that didn’t come. This third part looks at long-wave economic theories to see if they can help inform the timing of moves into defensive positions.

Kondratiev Waves (K-Waves)

In the 1920s, Soviet economist Nikolai Kondratiev (also written in English as Kondratieff) published several articles and books making a case for long economic waves of an average length of about 50 years. Most long-wave economic theorists reference Kondratiev’s work, build on and refine it, and introduce theories for the cause of K-Waves. One of the most accepted causes of K-Waves is the theory of technological innovation. Innovation sparks production and growth. Business thrives, stock and commodity prices boom, and inflation grows. In time, debt service reaches unsustainable levels. That leads to falling stock prices, a currency crisis, and high unemployment. The following figure illustrates the timing of six K-Waves along with the technological innovation that drove each.

Kondratiev Waves (K-Waves) and their related technological innovations. Image by the author.

In 2010, the Longwave Group built on the theory of K-Waves to predict a drop of the S&P 500 to the year 2020. Their related chart is a work of art since it combines the S&P 500, U.S. prices, Aaa corporate bond yields, treasury bond yields, and U.S. total debt as a percentage of GDP to make the case. Nevertheless, the S&P 500 has gained more than 300% since 2010. People who believed the Longwave Group’s prediction and moved out of stocks in 2010 and stayed out lost big.

Chart from 2010 using long-wave economic theory to predict a drop in the S&P 500 from 2000 to 2020. Image from Longwave Group.

That prediction from 2010 didn’t come true. Nonetheless, YouTube videos published in the past year include this chart as part of the evidence for an imminent crash. On the flip side, Ark Invest’s Cathie Wood fans might point to her five platforms of innovation as the reason why an economic winter didn’t come to pass. Her five platforms of innovation are as follows: DNA sequencing, robotics, energy storage, artificial intelligence, and blockchain technology.

My conclusion is that theories based on K-Waves are intriguing but not a factor in predicting the timing or direction of economic cycles.

Long-Term Debt Cycles

The easiest way to understand short and long-term debt cycles is to watch the first 20 minutes of How the Economic Machine Works by Ray Dalio. Per Dalio, the long-term debt cycle runs about 75 to 100 years and is caused by expansions and contractions in credit that drive economic cycles. It’s important to note that the long-term cycle outlasts the active investing timeframe of most individuals. As a result, the long-term debt cycle isn’t intuitive to investors who don’t study economic history.

[embed]Understand short and long term debt cycles in the first 20 minutes of this video.

The chart below shows the yield of 10-year Treasuries since 1962 in gray. That’s as far back as the Federal Reserve publishes the data and covers nearly 60 years of a long-term debt cycle. The blue line is a 250-day simple moving average which equates to about a year of trading days. It smooths out the gray line and highlights the short-term debt cycles. The green line is a nonlinear sine curve with exponential decay that best fits the daily data using a least-squares method. It reflects the long-term debt cycle.

The 10-year Treasury constant maturity curve since 1962 illustrates the long-term debt cycle. This and the following images by the author. Data for this and subsequent charts from Federal Reserve Economic Data (FRED).

The green trend line approximates the decline in interest rates from 1981 to 2020 but foretells an increase in the future. Bond prices move opposite of interest rates. When interest rates decrease, the value of existing bonds rises. A nearly 40-year decline in interest rates provided a tailwind to investors with bonds in their portfolios. The long-term debt cycle theory predicts that interest rates will rise and bond values will face a headwind during the cycle’s next phase.

The 250-day moving average indicates a shorter cycle that oscillates about the long cycle. Below, I’ve modeled the short-term cycle with an auburn line that is a best fit sine curve undulating around the long-term green line. The short cycle curve improves the curve fit and reduces the sum of the least-squares by 3%. The short cycle predicts a divergence of ±0.3% interest rate and doesn’t come close to modeling the real swings in interest rates above and below the green line.

This chart replaces the 250-day moving average with a calculated short-term curve.

Over a timeframe of nearly 60 years, the green curve is a decent fit visually for the data except for the interest rate bubble from 1980 to 1985. The following chart drills into a shorter timeframe and highlights the trend since 2015. Neither the long nor short curves help predict interest rates from year to year. However, it appears that when interest rates have deviated more than 0.6% from the long cycle curve since 2015, they tend to swing in a way to close the gap.

The 10-year Treasury constant maturity curve since 2015 illustrates that neither the long nor short curves are helpful for year-to-year predictions. Nevertheless, they point to long-term trends supported by Ray Dalio’s research.

Ray Dalio’s Archetypal Big Debt Cycle

In 2018, Ray Dalio published a 204-thousand word examination of big debt cycles titled, Principles for Navigating Big Debt Crises. He looked at big debt crises in different countries over the past 500 years to develop an “Archetypal Big Debt Cycle.” People who study 100-year floods or pandemics can more easily see them on the horizon and be better prepared. Similarly, Ray Dalio studied big debt crises. His research suggests another one is on the horizon. Ray Dalio freely published his findings to help others, including policymakers navigate a big debt crisis.

When things are so good that they can’t get better — yet everyone believes that they will get better — tops of markets are being made.

–Ray Dalio

Near the equities’ top of a big debt cycle, prices are driven by leveraged buying. The market gets overpriced and is ripe for a reversal. Ray states, “This reflects a general principle: When things are so good that they can’t get better — yet everyone believes that they will get better — tops of markets are being made.” Three of Dalio’s charts below illustrate the relationship between yield curves, equity prices, and debt.

Increased debt fuels a rise in equity prices until high debt service causes a contraction.

The first chart illustrates the relationship between short-term rates and long-term rates. An inverted yield curve where long-term debt has lower yields than short-term debt, signals a top in equity prices. The second chart illustrates the movement of equity prices during an archetypal big debt cycle. From the early part of the big debt cycle until the top, equity prices rise in step with the increase in total debt and debt service (third chart). At some point, the debt service becomes onerous, and equity prices drop. In other words, increased debt fuels a rise in equity prices until high debt service causes a contraction.

The relationship between yield inversions, equity prices, and debt from Principles for Navigating Big Debt Crises, Ray Dalio, 2018.

Comparing the Timeframe of Long-Term Debt Cycles to Yearly Temperature Cycles

I’m intrigued by long waves of 50+ year cycles in economics, particularly since several point to a season of winter. Yet, the accuracy of the predicted timeframes is dreadful. Many proponents of long-wave economics predicted significant declines in equity prices throughout the past decade. As a comparison to a natural cyclic phenomena, I looked at historical winter temperatures in Washington, D.C., and their yearly cycle. I wanted to understand the timing of the coldest recorded temperature each year. What day does the coldest temperature occur? And if the same coldest temperature happens on different days during the same winter season, I want to know the last day.

Most people would expect the coldest temperature in Washington, D.C. to occur in January, some would say December, and others might say February. Weather Underground provides historical data for 56 years. The last day of the lowest temperature in Washington, D.C. for 56 winter seasons is graphed below.

Chart showing the dates for the last day of the lowest temperature in Washington, D.C. Image by the author. Data from Weather Underground.

There is quite a range in dates, and it doesn’t look like a normal distribution. The results are summarized below.

Table summarizing the results for the last day of the lowest temperature in Washington, D.C.

I was surprised to learn that the coldest day of each winter for 56 winter seasons ranged from Dec 16 to Mar 23. That’s a span of 97 days or 27% of the days of a year. In other words, if you had to bet on the day of the lowest temperature in Washington, D.C, about a quarter of the calendar is feasible. You could research and discover that the median is Jan 22. Nevertheless, the coldest day only happened on Jan 22 twice in the most recent 56 seasons.

We understand the variability of winter temperatures and don’t expect a meteorologist to predict the timing of the coldest day of winter… Similarly, no one can predict the timing of the tops or bottoms of long economic cycles within a timeframe of a few years.

Applying the same percent variability of Washington, D.C.’s yearly winter temperature cycle to a long debt cycle with an average of 87 years means that a cycle is 87 years plus or minus 12 years. (I spent a lot of time manipulating weather data to reinforce Ray Dalio’s stated range of approximately 75–100 years.) We understand the variability of winter temperatures and don’t expect a meteorologist to predict the timing of the coldest day of winter. Knowing that winter is coming is good enough to prepare for it. And knowing that spring will follow allows us to hunker through winter. Similarly, no one can predict the timing of the tops or bottoms of long economic cycles within a timeframe of a few years.

Extending the Curves to 2030

Keeping in mind the caveat that the bottom of a long-term debt cycle could vary plus or minus a decade, the following chart extends the curves to 2030. It foretells that 10-year treasury rates will rise again sometime in the future.

The long and short cycles extended to 2030.

Continuing the earlier metaphor of headwinds and tailwinds, the following chart adds points of sail. In the 1960s and ’70s, rising bond yields acted as a headwind to bond traders. That’s before my time as an investor, but Stanley Druckenmiller tells a story on why he went from management trainee at Pittsburgh National Bank in 1977 to head of the bank’s equity research group after one year. He mentioned that the guys at the bond desk had taken a beating for more than a decade. Stanley’s boss foresaw the shift in interest rates and knew the experience of his more senior traders wouldn’t translate to the new environment. That’s why he offered Stanley the position.

Ray Dalio believes the U.S. economy is reentering the interest rate conditions that prevailed in the 1930s and 1940s. In sailing terms, investors will soon be moving in a different direction relative to the prevailing wind and will need to adjust the lines and helm accordingly.

Points of sail representing different strategies that worked with the prevailing winds of the last six decades.

Starting in the mid-1980’s, falling interest rates provided a tailwind for investors. Successfully front running the short-term cycles during that period was more difficult than a “set it and forget it” strategy of stocks and bonds. However, macro-economic conditions are changing. An environment of rising interest rates will force successful investors to follow a different tack. Back testing portfolios to 1980 has limited application since bond fundamentals will be different in the future.

The subtitle to this article is, “Can long wave economic theory help predict market timing?” Looking to the metaphor of predicting the coldest day of the upcoming winter season. No, weather forecasters can’t accurately predict the date of the coldest day of the year. In a similar vein, market experts can’t predict when the ten-year treasury rate will hit the lowest rate during this long cycle. But like weather forecasters, they understand the long cycle and can predict the changing nature of upcoming market conditions.

Macro-economic conditions are changing. Back testing portfolios to 1980 has limited application since bond fundamentals will be different in the future.

Some people don’t like Ray Dalio’s predictions on upcoming market conditions since he doesn’t put timeframes on his predictions. All his work on researching the big debt cycle has taught him that the timing varies — it can’t be predicted within a year or two. An entire long-term cycle varies by 25 years, so shifts from phase to phase can fluctuate by five or ten years. Nevertheless, during interviews over the past month, Ray Dalio predicts the following:

• Equity markets are “somewhat bubbly,” not frothy. In other words, we’re close to a top but not likely at the peak.
• Equities tend to top out during the cycle; followed by a substantial correction frequently in the range of 50%.
• Bond interest rates will remain below nominal GDP growth (inflation + real growth).
• Cash will receive a lower interest rate than bonds. “Cash is trash.”

If you believe in Dalio’s long cycle theory, this is a tricky time. Investing axioms that have worked for the past 40 years won’t perform during the next ten years.

Young people more than 15 years from retirement may choose to dollar cost average with a 100% stock portfolio since bond prices will drop as interest rates rise. That strategy will likely have some very trying periods. But long cycle theory says it will probably play out well since they’ll be acquiring stocks during a time of low prices.

This is a tricky time. Investing axioms that have worked for the past 40 years won’t perform during the next ten years.

Mature people in retirement or nearing retirement and dependent on withdrawals from an individual retirement account are in a delicate situation. Cash is stable but guaranteed to lose buying power. Bond values will drop. Equities may experience a top followed by a 50% decline. What to do?

[embed]Preparing for the “Fragile Decade” with an Appropriate Asset Mix Optimizing returns after inflation while minimizing volatility is the goalmedium.com

In the next article, Part 4 of this series, I’ll review defensive portfolios that mitigate sequence of returns risk without the drag of a prominent cash position. Follow me if you don’t want to miss it.

This article is the third in a series on defensive investing.

• Part 1 — compared a rookie mistake to beginners’ luck
• Part 2 — showed how beginner’s luck led to hubris
• Part 3 — this article looking at economic cycles and how they can inform defensive positions
• Part 4 — (coming) review of defensive portfolios that mitigate sequence of returns risk

I have no affiliation with any sites listed. This article is only for informational purposes. I am a self-directed investor, not a financial planner, lawyer, or accountant. All material is presented in good faith. Consult an expert before making any financial, legal, or tax decisions.

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