Forecasting International Sugar Prices: A Bayesian Model Average Analysis

Amrouk, El Mamoun; Heckelei, Thomas

doi:10.1007/s12355-020-00815-0

Cited by 8 publications

(5 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, Kuzmenko et al [38] revealed mutual interaction between selected stock exchanges and confirmed long-term equilibrium. Global sugar prices are recognised as highly volatile [40]; the volatility stems from the economic and physical characteristics of the sugar markets [41,42], as well as various support measures that benefit the subsector [43]. However, the international sugar agreement dissolution (1983) had a large impact on volatility, which resulted in an overnight drop in international sugar price by 38% [44].…”

Section: Introductionmentioning

confidence: 99%

Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

et al. 2021

View full text Add to dashboard Cite

Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial market uncertainty in a crisis time. In more detail, using sequential Bai–Perron tests for structural breaks, we check whether the global financial crisis and the COVID-19 pandemic have induced structural breaks in that relationship. Sugar prices are represented by the S&P GSCI Sugar Index, while the S&P 500 option-implied volatility index (VIX) is used to show stock market uncertainty. To investigate the changes in the relationship between sugar prices and stock market uncertainty, a regression model with a sequential Bai–Perron test for structural breaks is applied for the daily data from 2000–2020. We reveal the existence of two structural breaks in the analysed relationship. The first breakpoint was linked to the global financial crisis outbreak, and the second occurred in December 2011. Surprisingly, the COVID-19 pandemic has not induced the statistically significant structural change. Based on the regression model with Bai–Perron structural changes, we show that from 2000 until the beginning of the global financial crisis, the relationship between the sugar prices and the financial market uncertainty was insignificant. The global financial crisis led to a structural change in the relationship. Since August 2008, we observe a significant and negative relationship between the S&P GSCI Sugar Index and the S&P 500 option-implied volatility index (VIX). Sensitivity analysis conducted for the different financial market uncertainty measures, i.e., the S&P 500 Realized Volatility Index confirms our findings.

show abstract

Section: Introductionmentioning

confidence: 99%

Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Regarding the sugar prices, the results were very similar. It is expected that their prices will have stronger convergence with each other, including in the short term, given that Brazil is the largest global supplier and, therefore, its supply has a significant impact on international prices (Amrouk and Heckelei 2020 ). Rumánková et al ( 2019 ) found evidence that the main international sugar prices, such as New York and London, despite their regional differences and technical specificities, have a significant interrelationship, with Brazil and India as key players in this interdependence due to their supply capabilities.…”

Section: Resultsmentioning

confidence: 99%

Exploring the potential of the carbon credit program for hedging energy prices in Brazil

Palazzi,

Quintino,

Ferreira

et al. 2024

Environ Sci Pollut Res

View full text Add to dashboard Cite

The transition to a low-carbon economy is imperative to reduce reliance on fossil fuels and mitigate pollution emissions. This preposition also aligns with the United Nations Sustainable Development Goals (SDGs-13), which highlight the climate change action. In this vein, Brazil has implemented the Decarbonization Credit (CBIOS) program to incentivize biofuel production and promote environmental sustainability through carbon credit emissions. To this end, the present study evaluates the effectiveness of the CBIO contract as a hedging tool for investors in the face of energy price fluctuations and decarbonization efforts. Specifically, we employ conditional dynamic correlation (DCC-GARCH) and optimal hedge ratio (HR) techniques to assess the relationship between CBIO and the futures and spot prices of sugar, oil, and ethanol. Our findings suggest that the current CBIO contract is not an effective hedge against energy spot and future prices. However, our analysis identifies a strengthening correlation between ethanol traded in Chicago and CBIO over time, highlighting the potential for an underlying contract to serve as an effective hedging tool in the future. Our study adds to the existing literature on carbon pricing mechanisms and their impact on financial markets, emphasizing the importance of sustainable energy policies and their potential to mitigate the risks associated with energy price volatility and decarbonization efforts.

show abstract

“…The literature on modeling international sugar markets and projecting their prices tends to use general equilibrium models [6] or partial equilibrium models [15][16][17]. These are usually recursive approaches that provide annual market balances for production, consumption, trade, and world prices over a projection period.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Linear Models and Artificial Neural Networks for Sugar Price Prediction

Barchi,

dos Santos,

Bassetto

et al. 2024

FinTech

View full text Add to dashboard Cite

Sugar is an important commodity that is used beyond the food industry. It can be produced from sugarcane and sugar beet, depending on the region. Prices worldwide differ due to high volatility, making it difficult to estimate their forecast. Thus, the present work aims to predict the prices of kilograms of sugar from four databases: the European Union, the United States, Brazil, and the world. To achieve this, linear methods from the Box and Jenkins family were employed, together with classic and new approaches of artificial neural networks: the feedforward Multilayer Perceptron and extreme learning machines, and the recurrent proposals Elman Network, Jordan Network, and Echo State Networks considering two reservoir designs. As performance metrics, the MAE and MSE were addressed. The results indicated that the neural models were more accurate than linear ones. In addition, the MLP and the Elman networks stood out as the winners.

show abstract

Forecasting International Sugar Prices: A Bayesian Model Average Analysis

Cited by 8 publications

References 33 publications

Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Exploring the potential of the carbon credit program for hedging energy prices in Brazil

Comparative Analysis of Linear Models and Artificial Neural Networks for Sugar Price Prediction

Contact Info

Product

Resources

About