Forecasting ethanol price volatility under structural breaks

Abstract

The use of ethanol as a vehicle fuel has reduced greenhouse gas emissions significantly. The introduction of ethanol has also led to a decrease in crude oil prices. Considering the economic and environmental significance of the biofuel markets, a strand of literature investigates the price and volatility dynamics of US ethanol prices. In this paper, in contrast to previous studies, we investigate whether information on structural breaks plays an important role in predicting US ethanol market volatility. Our findings reveal that generalized autoregressive conditional heteroskedasticity (GARCH) models incorporating these breaks improve the prediction of US ethanol market volatility. Furthermore, the persistence of volatility tends to decline when structural breaks are included in the GARCH models. We further note that the influence of good and bad news is properly assessed under such breaks. Our results suggest that ignoring such breaks could mislead the risk assessment procedure for the US biofuel industry. © 2020 Society of Industrial Chemistry and John Wiley & Sons Ltd

Relationship between US and Brazilian ethanol prices: new evidence based on fractal regressions

“…complemented the analysis and found evidence that, in the short term, the markets are not connected, but in the long term these markets are globalized, with mutual influence. Recently, Bouri et al 16 . studied whether structural breaks are relevant for the prediction of ethanol market volatility, in the case of the USA, concluding that this was the case.…”

Forecasting Brazilian Ethanol Spot Prices Using LSTM

“…However, it is important to highlight that in the cited article the forecast periods are only 1, 2 and 3 days. On the contrary, Bouri et al [16] remind that the volatility (risk) perceived in periods is lower, which has greater meaning and more corresponding to this study.…”

“…Bouri et al [16] stated that the generalized autoregressive conditional heteroscedasticity (GARCH) models can incorporate structural breaks and improve the prediction of the volatility of the ethanol market in the United States. They also noted that the influence of good and bad news is properly assessed under such breaks.…”

An investigation into the relationship between sugarcane and grain prices in Brazil: a fractional cointegration approach

“…23 Considering the US market, bearing in mind that corn is used for the production of US ethanol, Dutta 22 studied whether the implied volatility of corn helps in predicting future corn price returns. With regard to US ethanol, Bouri et al 23 . determined whether the detection of structural breaks improves the forecast of future prices, and Dutta, 24 Hernandez et al 25 .…”