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This article investigates the connections among the prices of biofuels, agricultural commodities and other relevant assets in Europe, the US, and Brazil. The analysis includes a comprehensive data set covering price data for 38 traded titles during the period from 2003 to 2020. We used the minimum spanning tree (MST) approach to identify price connections in a complex trading system. Our analysis of mutual price connections reveals the major defining features of world-leading biofuel markets. We provide the characteristics of the main bioethanol and biodiesel markets with respect to government policies and technical and local features of the production and consumption of particular biofuels. Despite a relatively long and dynamically evolving history of biofuels, the biofuel systems in the US, Brazil and Europe do not converge toward the same pattern of relations among fossil fuels, biofuels, agricultural commodities and financial assets. [ABSTRACT FROM AUTHOR]

The interconnections within food, biofuel and fossil fuel markets are first described in the context of biofuels technologies and economic policy framework. Consequently, the econometric analysis consisting of Johansen cointegration, error correction model, vector autoregression and Granger causality is applied to price series of 12 biofuel related commodities. While a number of equilibrium relationships are found across the examined markets suggesting their interconnection, we do not obtain a persuasive confirmation of the thesis that biofuels clearly lead to food shortages via the increase in prices of basic food commodities used in the production of biofuels. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new measure of capital market efficiency. For its construction, we use the approaches of fractal dimension, Hurst exponent and entropy. The method is applied on 41 stock indices from the beginning of 2000 till the end of August 2011 and interesting results are found -- the analyzed indices are not self-affine; for the majority of indices, the deviation from the efficient market is dominated by local inefficiencies; and the most efficient capital markets are the stock indices of the most developed countries (FTSE, SPX, NIKKEI and DAX). [ABSTRACT FROM AUTHOR]

We focus on finite sample properties of two mostly used methods of Hurst exponent H estimation-rescaled range analysis (R/S) and detrended fluctuation analysis (DFA). Even though both methods have been widely applied on different types of financial assets, only several papers have dealt with the finite sample properties which are crucial as the properties differ significantly from the asymptotic ones. Recently, R/S analysis has been shown to overestimate H when compared to DFA. However, we show that even though the estimates of R/S are truly significantly higher than an asymptotic limit of 0.5, for random time series with lengths from 29 to 217, they remain very close to the estimates proposed by Anis & Lloyd and the estimated standard deviations are lower than the ones of DFA. On the other hand, DFA estimates are very close to 0.5. The results propose that R/S still remains useful and robust method even when compared to newer method of DFA which is usually preferred in recent literature. [ABSTRACT FROM AUTHOR]

Long-term memory processes have been extensively examined in recent literature as they provide simple way to test for predictabilty in the underlying process. However, most of the literature interprets the results of estimated Hurst exponent simply by its comparison to its asymptotic limit of 0 5. Therefore, we use moving block bootstrap method for rescaled range and periodogram method. In our analysis of evolution of Hurst exponent between 1997 and 2009, we show that PX experienced persistent behavior which weakened in time Nevertheless, the returns of PX remain close to confidence interval separating independent and persistent behavior. [ABSTRACT FROM AUTHOR]