Commodity Cycles Database

Commodity Cycles Turning Points Database

“What commodity prices lack in trend, they make up for in variance.” - Deaton (1999) 

When does a commodity boom begin, and when does it end? 

The Commodity Cycles Turning Points Database provides a consistent chronology of booms and slumps across 27 commodity prices over six decades, identifying peaks, troughs, and cycle phases using a commodity-specific dating methodology. The database offers researchers and practitioners a consistent tool for comparing commodity cycles and analyzing their causes and consequences.

Methodology: Turning points are identified using a cycle-dating algorithm adapted from established business-cycle methods. The procedure combines local peak and trough detection with restrictions on phase length, cycle duration, and amplitude to isolate economically meaningful price movements. Importantly, the algorithm is applied directly to commodity price levels, without smoothing or detrending, preserving the timing and magnitude of observed price movements while filtering out short-lived or economically insignificant fluctuations.

Access: The database is currently available on a limited-access basis. To request access, please contact me by email.

Citation

When using the database, please cite:

Balatti Commodity Cycle Database (v1_Jun2026) from Balatti 2026.

and the accompanying paper:

Balatti (2026) "Cracking Commodity Cycles: Uncovering the Hidden Clock and Decoding the Drivers", Available at SSRN

Abstract: Commodity prices exhibit pronounced cyclical behavior, but the duration and drivers of booms and slumps remain underexplored. This study addresses these gaps along three dimensions. First, it develops a commodity-specific cycle-dating algorithm that yields a comprehensive database of price cycles for 27 commodities spanning six decades. Second, the resulting dataset is used to investigate whether commodity price cycles are duration dependent—whether the probability of reversal increases as a phase ages. The empirical analysis provides strong evidence of positive duration dependence, indicating a “hidden clock” mechanism in commodity price dynamics. Third, the empirical results indicate that macroeconomic, financial, and geopolitical conditions significantly influence cycle persistence. While supply-side dynamics emerge as major drivers of phase transitions, demand-side factors also play a role: expanding economic activity and a strengthening global financial cycle tend to extend booms and shorten slumps.