In this paper we investigate the adaptive market efficiency of the agricultural commodity futures market, using a sample of eight futures contracts. Using a battery of nonlinear tests, we uncover the nonlinear serial dependence in the returns series. We run the Hinich portmanteau bicorrelation test to uncover the moments in which the nonlinear serial dependence, and therefore adaptive market efficiency, occurs for our sample. Eficiencia del Mercado Adaptativo en los Contratos Futuros de Productos Agrícolas ResumenEn este documento se investiga la eficiencia del mercado adaptativo del mercado de futuros de productos básicos agrícolas, utilizando una muestra de ocho contratos de futuros. Se utiliza una batería de pruebas no lineales para descubrir la dependencia no lineal en la serie de retornos. Aplicamos el estadístico Hinich portmanteau bicorrelación para descubrir los momentos de dependencia no lineal en las series, y por lo tanto se encuentra que cuatro productos del mercado tienen adaptable eficiencia Palabras claves: mercados eficientes, no linealidad, hipótesis de mercados adaptativos, productos agrícolas, mercado de futuros

The Global Fear Index (GFI) is a measure of fear/panic based on the number of people infected and deaths due to COVID-19. This paper aims to examine the interconnection or interdependencies between the GFI and a set of global indexes related to the financial and economic activities associated with natural resources, raw materials, agribusiness, energy, metals, and mining, such as: the S&P Global Resource Index, the S&P Global Agribusiness Equity Index, the S&P Global Metals and Mining Index, and the S&P Global 1200 Energy Index. To this end, we first apply several common tests: Wald exponential, Wald mean, Nyblom, and Quandt Likelihood Ratio. Subsequently, we apply Granger causality using a DCC-GARCH model. Data for the global indices are daily from 3 February 2020 to 29 October 2021. The empirical results obtained show that the volatility of the GFI Granger causes the volatility of the other global indices, except for the Global Resource Index. Moreover, by considering heteroskedasticity and idiosyncratic shocks, we show that the GFI can be used to predict the co-movement of the time series of all the global indices. Additionally, we quantify the causal interdependencies between the GFI and each of the S&P global indices using Shannon and Rényi transfer entropy flow, which is comparable to Granger causality, to confirm directionality more robustly The main conclusion of this research is that financial and economic activity related to natural resources, raw materials, agribusiness, energy, metals, and mining were affected by the fear/panic caused by COVID-19 cases and deaths.

The purpose of this paper is to analyze the test applied at the eighth Statistics II tournament to students from the University Center for Economic and Administrative Sciences of the University of Guadalajara, for the purpose of determining whether it promotes competitive learning among students. To achieve this, Item Response Theory (IRT) is used, specifically in the form of a threeparameter logistic model. The findings show that approximately 20 % of the participating students performed at a level ranging from outstanding to satisfactory, while the rest had a performance that fell between regular and poor. The findings also indicate that participating students were motivated by academic competition and the opportunity to improve their skills in the area of statistics. Moreover, we concluded that the tournament's assessment instruments need to be substantially improved in terms of design and the content of the items.

This paper presents a study of the multiple choice test from the eleventh knowledge tournament for Statistics I, in order to determine whether it instills competitive learning in university students. This research uses Item Response Theory (IRT). The results obtained show that only 27 students (13.43% of the total number of participants) have an acceptable level of ability (1.03 to 2.58), while the level of ability of the rest of the students is not satisfactory (-1.68 to 0.76). The participants are not a group of students seeking to test their knowledge of the subject or looking for an academic challenge. Better strategies for motivating students in terms of competitive learning must be found.

Recently, statistical reasoning has been of vital importance not only in quantitative analysis but also in the interpretation of graphs at all educational levels. There are students that can make calculations almost immediately but are not able to interpret or present their ideas graphically. In this way, the present study seeks to conduct a diagnostic of the problems that economic-administrative students have when reading and interpreting graphs in their statistics courses. For this, a Spanish version of the test Comprehensive Assessment of Outcomes in Statistics (CAOS) was administered. This instrument allows for the determination of reasoning applied to different types of statistical graphs and in some cases to determine what type of calculation is required to do it. The instrument was applied to 138 undergraduate students from the economic-administrative area of the University of Guadalajara during January-June 2018. The results show that a large percentage of students confuse a normal distribution with a uniform one and that they are unable to distinguish that a bias can be determined from the measures of central tendency and dispersion, as well as other statistical reasoning difficulties. This may be as a result of a deficiency that exists in statistical teaching, an insufficient mathematical preparation on the part of the students, among other factors.