Resumo

While both sugar and ethanol have some level of correlation due to their shared agricultural origins, their price dynamics are driven by distinct market forces. Sugar prices are linked to global sugar supply and demand, weather conditions, government policies, and consumer preferences. On the other hand, ethanol prices are more directly linked to the energy market, particularly the price of crude oil. Although these products are not in perfect alignment, their correlations may vary over time, and they may share intricate interdependencies in global markets (Bouri et al., 2021).

The objective is to understand the sugar price volatility and its relationship with the price of ethanol, which is crucial for formulating effective policies and optimal risk management strategies. Furthermore, inefficient risk-sharing mechanisms during periods of price volatility can distort the allocation of production factors, restrict agricultural investment, and delay productivity (Palazzi, Meira & Klotzle, 2022). Therefore, this article aims to contribute to studies on the volatility of sugar prices and their relationship with ethanol prices through wavelet-based analyses.

A new statistical procedure aims to add gains to new situations, improve estimation efficiency, reduce biases, increase robustness to modeling errors, or provide new insights. Wavelets are mathematical functions for analyzing signals and data. This technique decomposes returns into time-scale components and represents the variability and structure of stochastic processes scale by scale (Bouri et al., 2020). In other words, it is an essential function that can represent signals as a sum of different wavelets with different frequencies and scales.

The dataset was obtained from websites such as Macrotrends and Investing, which provide historical data and other relevant financial information. In the first part of the series, sugar prices are adjusted daily, 5 days a week, from November 29, 1962, until May 8, 2023, with the price series totaling 15,137 observations. For the second part, the sugar and ethanol price series have the same length, covering monthly data from January 1, 2005, to January 9, 2023, covering 6,582 observations, and, in both cases, the price is at US dollars per pound.

When the wavelet analysis of sugar and ethanol prices is compared, the curves have a very similar shape, especially when considering the magnitude of the coefficients. The ethanol and sugar curves show greater volatility at the beginning and end of the data series. However, moving forward in the signal, sugar experiences more pronounced fluctuations with more excellent spreads, while the ethanol curve presents fewer variations and oscillations. Observing the Wavelet Power Spectrum leads us to explore the most significant economic and global factors contributing to the correlation.

In conclusion, the analysis revealed time-frequency correlations between these markets, clarifying moments of synchronization and divergence. This dichotomy in their behavior underscores the importance of studying them individually and in conjunction to understand their complex relationship. These findings emphasize the dynamic interaction between sugar and ethanol prices and their responsiveness to various economic and global factors.

Bouri, E., et al. (2020). Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis. The Quarterly Review of Economics and Finance, 77, 156-164. Bouri, E., et al. (2021). The realized volatility of commodity futures: Interconnectedness and determinants. International Review of Economics & Finance, 73, 139-151. Palazzi, R. B., Meira, E., & Klotzle, M. C. (2022). The sugar-ethanol-oil nexus in Brazil: Exploring the pass-through of international commodity prices to national fuel prices. Journal of Commodity Markets, 28, 100257.