Quantifying the Predictability and Efficiency of the Cointegrated Ethanol and Agricultural Commodities Price Series

Abstract

Ethanol is an energy commodity and a biofuel that has contributed to mitigate the use of fossil fuels. Nonetheless, the environmental benefits derived from the use of ethanol can occur at the expense of the agricultural commodities prices, affecting their volatilities and efficiency. This problem occurs because most of the raw materials currently used to produce biofuels, such as corn in the US, sugarcane in Brazil and oilseeds in Europe, are also important global commodities. This work adopts several mathematical tools, namely the Detrended Fluctuation Analysis, fractal dimension, and the Hurst and Lyapunov exponents. This set of tools measures the market efficiency and the prices’ predictability for the ethanol and some agriculture commodities that revealed price transmission (cointegration), in a previous work. The results show that, in general, the ethanol has a lower predictability horizon than the other commodities. Moreover, it is discussed a quantitative measure to assess the market performance, by means of the efficiency index. We observe that the ethanol efficiency is similar to the other agricultural commodities evaluated.

The recovery of global stock markets indices after impacts due to pandemics

“…The trend, drift and constant are types of regression models that can properly identify the integration order ( ) of a TS, that is, the number of times necessary to differentiate a TS that was originally non-stationary to become a stationary one. This is a necessary property to identify a cointegration relation between two TS ( David et al, 2019 ).…”

“…In the follow-up the data and methods adopted in this work, such as the cointegration analysis ( Johansen, 2002 , David et al, 2019 ) and the VECM methodology ( Colombage, 2009 ) are discussed.…”

“…With regard to financial indices we follow 11 indices namely the Dow Jones (USA), S&P 500 (USA), Euro Stoxx (Eurozone), DAX (Germany), CAC (France), Nikkei (Japan), HSI (Hong Kong), Kospi (South Korea), S&P (Australia), Nifty (india) and Ibov (Brazil). For this purpose, we adopt the Johansen cointegration test ( Johansen, 2002 , David et al, 2019 , Quintino et al, 2017 ) and the bivariate VECM ( Colombage, 2009 ) exploited by the orthogonal impulse response (OIR) and the forecast error variance decomposition (FEVD). Additionally, in order to provide a better perspective and scope, we also evaluate the historical volatility and the recovering of the stock indices during those pandemics.…”

Forecasting Brazilian Ethanol Spot Prices Using LSTM

“…The author concludes that ethanol is sensitive to short-and long-term changes in the oil. David et al [8] state that in general, ethanol has a lower predictability horizon than other commodities. Pokrivčák and Rajčaniová [17] also find a relationship in oil and ethanol prices.…”

“…Besides, it is not difficult to find researchers that find contrary outlines. For instance, David et al [8] evaluates the price transmission via cointegration among ethanol and other commodities, especially coffee and Carpio [5] noticed the oil prices have affected ethanol prices when analysing more than 20 years. In addition, the volatility of spot prices encourages agents for hedging against market risk in the Brazilian and American markets [9].…”