The Economic Confidence Model & Global Financial Interconnectivity

Historically, economic growth tends to follow periods of continuous expansion and after periods of contraction. Financial markets respond to this cycle as the macro environment determines the level of interest rates and consequently the liquidity conditions for every market worldwide. In several previous articles, we have examined models of business cycles, such as:

» Ray Dalio Economic Cycles

» Gann’s Law of Vibration

» Benner’s Cycle

Below, another model is examined, Martin Armstrong's Economic Confidence Model (ECM).

Highlights of the ECM

• Armstrong claimed that economic cycles follow a constant ratio based on 𝜋=3.14
• He also argued that financial assets do not appreciate linearly over time, instead they follow an 8.6 years cycle (3,141 days or else 𝜋 × 1000)
• According to him, there is a larger 51.6 years cycle consisting of six waves (6 x 8.6 years = 51.6 years)

 

More About Armstrong's Economic Confidence Model

Armstrong's model is based on a cyclical pattern that lasts 8.6 years or else 3,141 days. As mentioned above, this number of days equals 𝜋 × 1000. Inside the 8.6-year cycle, there is an internal quarter-cycle of 2.15 years (785 days).

• At the end of each 8.6-year cycle, the model predicts a very significant crisis to occur
• After this crisis, the economic climate improves again for another 8.6 years

Armstrong also supported that the 8.6-year wave is part of a larger wave that lasts 51.6 years (6 waves x 8.6 years). Furthermore, each wave of 51.6 years is part of an even longer cycle of 309.6 years (six waves x 51.6 years).

• 51.6 years cycle (6 waves 8.6 years)
• 309.6 years cycle (6 waves of 51.6 years)

Armstrong tried to support his theory with historical data. For example, he claimed that the existence of the ancient Roman currency Bronze Follis also followed a 52-year cycle.

Chart: The ECM Model by Martin Armstrong (source)

Who is Martin Armstrong

Martin Arthur Armstrong started his career as an economic forecaster in 1973, when he began publishing predictions for the commodity market. Later, he launched a paid newsletter. Armstrong's theory was initially applied in 1977 when he successfully predicted a strong bullish trend in commodity prices. Since then, he has made some successful predictions that gained him popularity.

However, later in his life things didn’t go well for him. In 1999, the Japanese fraud investigators accused Armstrong of improperly collecting money from Japanese investors. Afterward, he was convicted in the US for investment fraud and spent 11 years in jail. He was released in 2011.

 

 

Other Similar Long Wave Theories

There are quite a few similar models of business cycles, such as Benner’s Cycle recently examined by TradingCenter.org.

 

Benner’s Cycle

Benner’s Cycle predicts the ups and downs of the stock market based on a repetitive cycle that lasts 18/16/20 years. Overall, the model seems reliable at the beginning of each market cycle, and completely unreliable at the end. As concerns market tops and mid-cycle tops, the model proved sometimes accurate, and sometimes not.

» https://tradingcenter.org/index.php/trade/equities/362-benner-cycle

 

The Kondratieff Long Wave Theory

The economist Nikolai D. Kondratieff introduced the long-wave theory during the early Russian Communist era. Kondratieff identified a pattern within the prices of agricultural products and copper. He claimed that the prices of these commodities follow a long-term wave which is the result of technological innovation. This concept was initially introduced in his 1925 book ‘The Major Economic Cycles’. It is estimated that these long waves last 40 to 60 years.

Chart: Kondratieff Cycles by Allianz Global Investors (source)

 

Primary Dimensions of Economic and Market Movement

Martin Armstrong was chairman of Princeton Economics International Ltd. Princeton Economics has published interesting research on their website. According to them, there are four primary dimensions of market and economic movement:

• Time
• Price
• Volatility, and
• Interrelationships

Princeton claim that the global interrelationships and interconnectivity matter a lot. Therefore, the fundamental analysis must be global in nature and not be isolated to domestic trends and events.

 

Examining the Concept of Global Financial Interconnectivity

In recent years, this idea of global financial interconnectivity has been confirmed. After the financial crisis of 2007-2008, there are strong correlations between almost all financial markets. These correlations can be identified between different geographical markets and asset classes. This recent interconnectivity can be attributed to:

(i) the introduction of new financial products such as ETFs

(ii) the implementation of new cross-asset portfolio-diversification strategies

These cross-asset portfolio strategies assume the distribution of capital to multiple asset classes. This can easily happen today via ETFs. Overall, global accessibility enhances the interrelationships and interconnectivity between all financial markets.

Considering the above, the best approach to perform any economic analysis is the “Outside-in". This means examining the general economic environment before focusing on any particular asset class or financial asset. Moreover, recognizing strong intermarket correlations is important for achieving true portfolio diversification. We should consider all cross-asset correlations and adjust our positions accordingly.

 

 

Final Thoughts -Having an Open Mind but Taking Nothing for Granted

Several forecasting models have been examined on TradingCenter, but not because all these models work. There is no such thing as a static economic model that can predict the future. Our world and our economy are fully dynamic and change by the day. How can a static model predict the future of a changing economic environment?

Investment decisions should not be based on any static model. There are indeed patterns in economic activity, but these patterns are dynamic and change according to new economic, political, and technological conditions. Models exclusively based on Phi, Pi, or any other mathematical constant cannot possibly describe the chaotic nature of the economy and successfully predict the behavior of global financial markets.

“Having an open mind doesn’t necessarily mean taking every new idea for granted.”

Finally, as concerns the idea of global financial interconnectivity, there is no doubt about it. The globalization of the economy combined with the introduction of new financial products, such as ETFs, created strong correlations between almost all financial markets. We should consider all these cross-asset correlations and manage our portfolios accordingly.

 

■ Martin Armstrong's ECM Model Based on Pi {π = 3.141}

George Protonotarios, financial analyst

for TradingCenter (c) May, 1st 2024

 

Sources:

• ArmstrongEconomics.com
• Allianz Global Investors -The Sixth Kondratieff Long Waves of Prosperity
• Wikipedia.org
• Models and Methodologies, 2^nd edition, 2015, Martin Armstrong