Pedro Argento, Marcelo Cabus Klotzle, Antonio Carlos Figueiredo Pinto and Leonardo Lima Gomes
Brazil is characterized by the inexistence of a more robust system of guarantees and rules to minimize risks and protect agents in energy futures contracts. In this sense, this…
Abstract
Purpose
Brazil is characterized by the inexistence of a more robust system of guarantees and rules to minimize risks and protect agents in energy futures contracts. In this sense, this study aims to answer the question of how a centralized clearing agent can compute safety margin requirements to help reduce the systemic risk of the energy futures contracts market in Brazil.
Design/methodology/approach
The intermediate steps and specific objectives are to analyze the volatility behavior, identify the autoregressive conditional heteroscedasticity effects and model the variance of the return series. Based on this, the authors calculate the value-at-risk and conditional value-at-risk metrics for the energy futures contracts. As a robustness test, the authors added a peak over threshold methodology from extreme values theory.
Findings
In general, monthly products require margins because of their higher variance. With the asymmetrical distribution of returns, the authors needed to consider different maintenance margins for the long and short positions. It was also shown that two guarantee margins were required to secure the contracts as follows: the initial margin and the maintenance margin. The three factors that defined the size of the maintenance margin the volatility, skewness and kurtosis of the return series.
Originality/value
The contribution of this study lies in promoting the understanding of the risk dimensions of the energy derivatives market in Brazil and it offers concrete recommendations for how to mitigate this risk through market mechanisms and structures. Similar arrangements can be applied to other emerging markets.
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Jeferson Carvalho, Paulo Vitor Jordão da Gama Silva and Marcelo Cabus Klotzle
This study investigates the presence of herding in the Brazilian stock market between 2012 and 2020 and associates it with the volume of searches on the Google platform.
Abstract
Purpose
This study investigates the presence of herding in the Brazilian stock market between 2012 and 2020 and associates it with the volume of searches on the Google platform.
Design/methodology/approach
Following methodologies are used to investigate the presence of herding: the Cross-Sectional Standard Deviation of Returns (CSSD), the Cross-Sectional Absolute Deviation (CSAD) and the Cross-Sectional Deviation of Asset Betas to the Market.
Findings
Most of the models detected herding. In addition, there was a causal relationship between peaks in Google search volumes and the incidence of herding across the whole period, especially in 2015 and 2019.
Originality/value
This study suggests that confirmation bias influences investors' decisions to buy or sell assets.
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Augusto Ferreira da Costa Neto, Marcelo Cabus Klotzle and Antonio Carlos Figueiredo Pinto
The purpose of this paper is to present the results of a study on investor behavior in exchange-traded fund (ETF) markets. The standard feedback trading model of Sentana and…
Abstract
Purpose
The purpose of this paper is to present the results of a study on investor behavior in exchange-traded fund (ETF) markets. The standard feedback trading model of Sentana and Wadhwani (1992) is used in a sample of 18 ETFs contracts in Brazil, China, South Africa, Korea, Mexico and India, as well as three ETFs contracts in the US market.
Design/methodology/approach
The sample includes data on daily closing prices and net asset values (NAVs) for three ETFs from each of the emerging markets of Brazil, China, Mexico, Korea and India, as well as on three ETFs from the US market. The authors used the earliest start date available in the Thomson Reuters database pertaining to all of the ETFs, and all series ended on May 5, 2017, and applied the well-established Santana and Wadhwani (1992) seminal model to evaluate evidence of feedback trading in the sample.
Findings
The empirical analysis suggests that there is evidence of feedback trading in emerging markets such as Brazil, Korea, Mexico and India, while there is no such evidence for the US market. The results are consistent with the view that developed markets investors are prone to pursue fundamental-driven investment strategies, while emerging markets investors appear to have informational guided behavior.
Research limitations/implications
Emerging markets still make up a very small part of the global ETF market, led by the USA. Nevertheless, it is extremely important that studies of this nature be gradually expanded as these markets grow, in order to verify how emerging markets compare to their developed counterparts in terms of the efficiency of information sharing and rationalization of its operations.
Practical implications
Emerging markets policy makers could benefit from these findings by stimulating new mechanisms that could minimize informational asymmetry and the persistence of so-called noise traders, a phenomenon observed recently in studies regarding ETF markets (Brown, Davies and Ringgenberg, 2018).
Originality/value
The behavior of investors was investigated by analyzing a sample of 18 ETFs from the emerging markets of Brazil, China, South Africa, Korea, India and Mexico, as well as three ETFs from the US market. Despite of being investigated separately both emerging (Charteris et al., 2014) and developed markets (Chau et al., 2011), the innovation consists in comparing those markets in a single study, pursuing to explain potential reasons for the differences observed between developed and emerging markets.
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Mario Domingues Simões, Marcelo Cabus Klotzle, Antonio Carlos Figueiredo Pinto and Leonardo Lima Gomes
The purpose of this study is to ascertain whether nonlinearities could be present in electricity loads observed in subtropical environments, where none or little heating is…
Abstract
Purpose
The purpose of this study is to ascertain whether nonlinearities could be present in electricity loads observed in subtropical environments, where none or little heating is required, and whether threshold autoregressive (TAR)-type regime switching models could be advantageous in the modeling of those loads.
Design/methodology/approach
The actual observed load of a Brazilian regional electricity distributor from January 2013 to August 2012 was modeled using a popularly employed ARMA model for reference, and smooth and non-smooth TAR transition (non-linear) models were used as non-linear regime switching models.
Findings
Evidence of nonlinearities were found in the load series, and evidence was also found on the intrinsic resistance of this type of models to structural breaks in the data. Additionally, to reacting well to asymmetries in the data, these models avoid the use of exogenous variables. Altogether, this could prove to be a definite advantage of the use of such model alternatives.
Research limitations/implications
However, even if the present work may have been limited by the observation frequency of the available data, it appears TAR models appear to be a viable alternative to forecasting short-term electricity loads. Nonetheless, additional research is required to achieve a higher accuracy of forecast data.
Practical implications
If such models can be successfully used, it will be a great advantage for electricity generators, as the computational effort involved in the use of such models is not significantly larger than regular linear ones.
Originality/value
To our knowledge, this type of research has not yet been made with subtropical/tropical electricity load data.