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We investigate the behaviour of retail diesel prices in Brazil using fractional integration, with weekly data from January 2010 to April 2020. In this period, we have 3 episodes of relevant economic implications in the country under analysis: i) impeachment of the Brazilian President; ii) the lorry-drivers' strike; iii) the rise of the global Covid-19 epidemic. We use a sliding windows approach to analyze price dynamics over time. The results suggest that, at the beginning of the sample, prices were non-stationary and non-mean reverting. Over the time, diesel prices become non-stationary with mean-reversion in Midwest, South and Southeast regions, while in the North and Northeast we cannot reject non-stationarity and non-mean reversion (d > 1). Results are relevant for market agents and policy-makers, as it can be inferred whether exogenous shocks are temporary, despite taking some time to dissipate completely. [ABSTRACT FROM AUTHOR]

Abstract: We study the statistical properties of hourly wind speed time series detected at four weather stations in the state of Pernambuco, Brazil, in the period 2008–2009. We find that the average and maximum hourly wind speeds deviate from a mutual linear relationship, and that they may be well explained individually by a Weibull distribution, however, with different shape parameter values. On the other hand, the long-term correlations of both of these observables obey the same power-law behavior, with two distinct scaling regimes. Our results agree with previous studies on wind speed series correlations in other regions of the world, which is suggestive of universal behavior. [Copyright &y& Elsevier]

We report an empirical study of the Ibovespa index of the Sa˜o Paulo Stock Exchange in which we detect the existence of long-range correlations. To analyze our data, we introduce a rescaled variant of the usual detrended fluctuation analysis that allows us to obtain the Hurst exponent through a one-parameter fitting. We also compute a time-dependent Hurst exponent H(t) using 3-year moving time windows. In particular, we find that before the launch of the Collor Plan in 1990 the curve H(t) remains, in general, well above 1/2, while afterwards it stays close to 1/2, while afterwards it stays close to 1/2. We thus argue that the structural reforms set off by the Collor Plan has lead to a more efficient stock market in Brazil. We also suggest that the time dependence of the Ibovespa Hurst exponent could be described in terms of a multifractional Brownian motion. [Copyright &y& Elsevier]

We analyze trend and persistence in Standardized Precipitation Index (SPI) time series derived from monthly rainfall data at 133 gauging stations in Pernambuco state, Brazil, using a suite of complementary methods to address the spatially explicit tendencies, and persistence. SPI was calculated for 1-, 3-, 6-, and 12-month time scales from 1950 to 2012. We use Mann–Kendall test and Sen's slope to determine sign and magnitude of the trend, and detrended fluctuation analysis (DFA) method to quantify long-term correlations. For all time scales significant negative trends are obtained in the Sertão (deep inland) region, while significant positive trends are found in the Agreste (intermediate inland), and Zona da Mata (coastal) regions. The values of DFA exponents show different scaling behavior for different time scales. For short-term conditions described by SPI-1 the DFA exponent is close to 0.5 indicating weak persistency and low predictability, while for medium-term conditions (SPI-3 and SPI-6) DFA exponents are greater than 0.5 and increase with time scale indicating stronger persistency and higher predictability. For SPI-12 that describes long-term precipitation patterns, the values of DFA exponents for inland regions are around 1, indicating strong persistency, while in the shoreline the value of the DFA exponent is between 1.0 and 1.5, indicating anti-persistent fractional Brownian motion. These results should be useful for agricultural planning and water resource management in the region. [ABSTRACT FROM AUTHOR]