How to Exploit Commodity Cycles with Python
Commodities are subject to what is known as a commodity cycle. This phenomenon is particularly evident in the case of soft commodities, such as food. When the prices of wheat or soybeans surge in a given year due to increased demand, there is a substantial increase in cultivation in the following season, leading to a subsequent decline in prices. This cycle repeats regularly. In contrast, industrial metals follow a different pattern. This is because it takes seven to eight years to explore and develop new deposits, thereby increasing the supply.
Secular boom phases lasting around 10 years are observed in industrial metals, typically driving prices up by several hundred percent. This is often followed by a pronounced downward trend lasting approximately 15 years. The last price peak occurred in 2008, and the downward trend persisted until 2021 with fluctuations. Starting in 2013/2014, commodity companies responded to the price decline with reduced investments. This trend applies to both industrial metals and fossil fuels (oil, gas, coal). In recent years, the discussion around “stranded assets” has significantly intensified this decline in investment. Many experts concluded that undeveloped resource deposits are worthless due to efforts to combat the climate crisis and must be written off. This misconception led to a massive scarcity of supply because global energy…
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