Semei Coronado

Analysis of Competitive Learning at University Level in Mexico via Item Response Theory

Abstract 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.

A Bayesian approach to model changes in volatility in the Mexican stock exchange index

ABSTRACT We model the changes in volatility in the Mexican Stock Exchange Index using a Bayesian approach. We study the time series with a wide set of models characterized by a Markov switching heterogeneity. The advantage of this approach is that it allows for a broader spectrum of possible models since the estimation of the moments of the parameters is done using the finite mixture distribution MCMC method, without relying on assumptions about large sampling and mathematical optimization. This is particularly relevant for emerging markets’ financial data because of its special characteristics, like being more susceptible to jumps and changes in volatility caused by exchange rate swings, financial crises and oil and commodity prices. For model comparison, we use the marginal likelihood approach and the bridge sampling technique. The best representation of the data is given by a switching model with three states rather than any other autoregressive linear or non-linear model. The periods of volatility found by the model coincide with different financial crisis. Whereas other studies of volatility for the same market impose the Markovian model that captures changes in volatility, we let our model to be defined in an endogenous way.

Causality patterns for Brent, WTI, and Argus oil prices

ABSTRACT Causality patterns are analysed for daily Brent, West Texas Intermediate (WTI), and Argus Sour Crude Index (Argus) oil prices, Argus is the reference price for exports from Saudi Arabia, Kuwait and Iraq. Nonparametric Granger causality testing uncovers bi-directional causal links between Brent and WTI prices at multiple lags. Unidirectional causality from both Brent to Argus and WTI to Argus is also documented. If the current Saudi Arabia attempt to increase market share is successful, variations in Argus prices may start preceding movements in Brent and WTI, also.

Nonlinearity Testing of Latin American Exchange Rates

This chapter investigates the adequacy of ARCH- and GARCH-type models to describe the behavior of five Latin American currencies against the US dollar by applying a new inferential testing procedure. This latter performs iteratively econometric tests of nonlinearity covering the majority of the most common sources of data dependence. In particular, the testing procedure includes a new maximal bispectral test of linearity with enhanced power against those forms of non-linearity that display flat bispectrum and nonflat higher-order polyspectra. The results suggest that GARCH models cannot capture the data generating processes for four of the five studied currencies.