The video titled “Market Cycles Report: Oct 10, 2022 – Cycles of Financial Crisis using long term static cycle models” delves into the significance of long-term static cycle models in predicting financial crises. The video, hosted by Lars Fontin, explores two primary static cycles: the 56/9 years cycle grid by JM Funk (1932) and the Benner cycles (1875). These cycles are juxtaposed with current dynamic cycles to provide a comprehensive understanding of potential market movements, particularly focusing on the year 2023.
5 Key Takeaways
- Historical Significance: Both the 56/9 years cycle grid and the Benner cycles have historically been significant in predicting financial crises.
- Dynamic vs Static Cycles: While dynamic cycles are subject to change, static cycles provide a fixed framework that has remained consistent over decades.
- Year 2023: Both static and dynamic cycles point to the year 2023 as a potential period for financial upheaval.
- High Accuracy: The 56/9 years cycle grid has an outstanding significance, with 27 out of 30 major panics between 1760 and 1930 appearing in this double sequence grid.
- Cycles within Cycles: The alignment of static and dynamic cycles offers a multi-dimensional perspective on market trends, enhancing the predictive power of cycle analysis.
The 56/9 Years Cycle Grid
The 56/9 years cycle grid, initially proposed by JM Funk in 1932, is a long-term static cycle model that has shown a high correlation with historical financial crises. This grid is broken down into sequences of 56 years and 9 years, creating a matrix that has been remarkably accurate in predicting financial panics. For instance, major crises like those in 1837, 1857, 1873, 1893, and 1929 all fall within this grid.
Benner Cycles
Another long-term static cycle model that has stood the test of time is the Benner cycles, initially published around 1875. This cycle is broken down into sequences of 16, 18, and 20 years, averaging to a 54-year cycle. Edward Dewey, the founder of the Foundation for the Study of Cycles, analyzed this cycle and found that it would have yielded 50 times more gains than losses between 1872 and 1939 if used for trading.
Dynamic Cycles
Dynamic cycles, unlike static cycles, are subject to change and are analyzed using modern computational methods. These cycles provide insights into the current phase, length, and amplitude of market trends. When aligned with static cycles, they offer a robust framework for understanding market dynamics.
The Year 2023
Both static and dynamic cycles point to the year 2023 as a significant year for potential financial upheaval. The alignment of these cycles provides a compelling case for heightened vigilance and strategic planning as we approach this year.
The Power of Alignment
The convergence of static and dynamic cycles offers a multi-dimensional perspective that enhances the predictive power of cycle analysis. This “cycles within cycles” alignment is particularly potent in providing actionable insights for traders and analysts.
Lessons Learned
- Historical cycles offer valuable insights: Long-term static cycles have proven to be remarkably accurate in predicting financial crises and should not be overlooked.
- Alignment is key: The convergence of static and dynamic cycles provides a robust framework for understanding market dynamics.
- Be prepared for 2023: Given the alignment of various cycles pointing to this year, it would be prudent to prepare for potential market upheavals.
Final Thoughts
The analysis of long-term static cycles, when aligned with dynamic cycles, provides a compelling framework for understanding market dynamics. As we approach the year 2023, which is highlighted by both types of cycles as a significant year, traders and analysts should exercise heightened vigilance and strategic planning. The historical accuracy of these cycles offers a strong case for their continued relevance in modern market analysis.
Note: The insights provided in this article are based on the video analysis by Lars Fontin, published on October 10, 2022. It is crucial for traders and analysts to conduct their own research and consider multiple factors before making any financial decisions.
