Rojas, Omar
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Preferred name
Rojas, Omar
Official Name
Rojas Altamirano, Omar Guillermo
Alternative Name
orojas
Main Affiliation
ORCID
Scopus Author ID
22954196800
Researcher ID
K-1066-2013

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Adaptive efficiency of the Mexican Stock Exchange

2018 , Esmeralda Brito-Cervantes , Semei Coronado , Manuel Morales-García , Rojas, Omar

Purpose The purpose of this paper is to analyse the adaptive market efficiency in the price–volume (P–V) relationship of the stocks listed in the Mexican Stock Exchange. The period under study goes from 1982 to 2015. In order to detect causality and, thus, determine adaptive efficiency in the market, one linear and two non-linear tests are applied. There are few papers in the literature that study the P–V relationship in Latin American markets; as such, this paper may be of interest and importance to financial academics and practitioners alike. Design/methodology/approach The Diks and Panchenko (DP) non-parametric Granger causality and the Brooks and Hinich (BH) cross-bicorrelation tests are applied. Findings Derived from the DP test, the findings show that there exists bi-directional non-linear Granger causality in 25.71 per cent of the firms studied, compared to 8 per cent when applying the linear Granger causality test. Therefore, there is evidence of weak-form efficiency in the market. From the BH test, evidence is shown of the adaptive market efficiency, since 71.42 per cent of firms exhibited some form of non-linear dependence in certain periods of time. With these results, the information process should be better studied for a greater comprehension of regulatory policies in the market and better decision-making tools for the investors. Originality/value This paper complements studies on the P–V relationship and efficiency in a Latin American market.

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A Bayesian study of changes in volatility of Bitcoin

2019 , Rojas, Omar , Semei Coronado

<p>This paper is aimed at studying a MS-GARCH model applied to Bitcoin. The Bayesian estimation of the model shows that Bitcoin’s volatility can be modelled using two states of volatility, high and low. The modelled volatility is not stable over time. Twenty eight periods of high volatility were found, the largest period of volatility occurred during 2013. The findings help explain what happened during these high volatility periods.</p><p> </p><p><strong> </strong></p>

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Time-Varying Granger Causality of COVID-19 News on Emerging Financial Markets: The Latin American Case

2023 , Semei Coronado , Jose N. Martinez , Victor Gualajara , Rafael Romero-Meza , Rojas, Omar

This study uses daily COVID-19 news series to determine their impact on financial market volatility. This paper assesses whether U.S. financial markets react differently to COVID-19 news than emerging markets and if such markets are impacted differently by country-specific and global news. To detect the spillover effects from news on market volatility, a time-varying DCC-GARCH model was applied. The results suggest that the U.S. and emerging markets are affected differently by pandemic news, global series have a stronger impact on emerging markets than country-specific ones, and misleading information plays a significant role in financial market volatility, especially for the U.S.

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

2017 , Gustavo Cabrera , Semei Coronado , Rojas, Omar , Rafael Romero-Meza

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A Nonlinear Empirical Analysis of Oil Price Co-movements

2018 , Semei Coronado , Thomas M. Fullerton , Rojas, Omar

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Causality patterns for Brent, WTI, and Argus oil prices

2016 , Semei Coronado , Thomas M. Fullerton , Rojas, Omar

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Crude Oil and Biofuel Agricultural Commodity Prices

2018 , Semei Coronado , Rojas, Omar , Rafael Romero-Meza , Apostolos Serletis , Leslie Verteramo Chiu

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Time-Varying Spillovers between Currency and Stock Markets in the USA: Historical Evidence From More than Two Centuries

2020 , Semei Coronado , Rangan Gupta , Besma Hkiri , Rojas, Omar

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Transfer Entropy Granger Causality between News Indices and Stock Markets in U.S. and Latin America during the COVID-19 Pandemic

2022 , Semei Coronado , Jose N. Martinez , Victor Gualajara , Rojas, Omar

The relationship between three different groups of COVID-19 news series and stock market volatility for several Latin American countries and the U.S. are analyzed. To confirm the relationship between these series, a maximal overlap discrete wavelet transform (MODWT) was applied to determine the specific periods wherein each pair of series is significantly correlated. To determine if the news series cause Latin American stock markets’ volatility, a one-sided Granger causality test based on transfer entropy (GC-TE) was applied. The results confirm that the U.S. and Latin American stock markets react differently to COVID-19 news. Some of the most statistically significant results were obtained from the reporting case index (RCI), A-COVID index, and uncertainty index, in that order, which are statistically significant for the majority of Latin American stock markets. Altogether, the results suggest these COVID-19 news indices could be used to forecast stock market volatility in the U.S. and Latin America.

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Time‐varying causality between bond and oil markets of the United States: Evidence from over one and half centuries of data

2021 , Semei Coronado , Rangan Gupta , Saban Nazlioglu , Rojas, Omar

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