Abstract
We examine the occurrence of structural breaks in the mean return and volatility of the BRICS currency returns. We propose a novel methodology to identify regimes with same statistical variance based on sequential Bayesian change point model. We find frequent occurrence of structural breaks in the mean returns and volatility of BRICS currencies. The segments with same statistical properties are merged into regimes. We sorted the regimes from low to high regarding their volatility. We show that the last regime exhibits the highest returns and incorporates the shortest periods across all currencies with exception to the Chinese and Brazilian currency. This is an indication that periods of high volatility are few and offers high returns compared to periods of low volatility.
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Notes
We have conducted the sensitivity results by taking different value of η and α as advised by the referee. We found that essentially, overall numbers of regimes do not change. Small change happens in the number of observations in each regime, though. The results may be made available upon request.
We have used Matlab 2013 for the analysis in the paper and codes will be made available upon request.
By the end of 2014, the ruble was devalued by 58.2 per cent to the US dollar, compared to December 2013.
Bloomberg News. China Rattles Markets With Yuan Devaluation, August 11, 2015.
We thank the second referee who points out if our results are robust across the alternative methodologies of structural break point tests (e.g., Bai-Perron test and others), we argue that Bai-Perron test is limited to capture only five breaks while in our approach, we can set as high number as we want and then pass on to the distribution results to generate the regimes. However, for the purpose of comparison, we have applied the Iterated Cumulative Sums of Squares (ICSS) algorithm proposed by Sansó et al. (2020). Based on this algorithm, we found 18 breaks for BRL, three breaks for CNY, six breaks for INR, 20 breaks for ZAR and nine breaks for RUB. Detailed results would be made available upon request.
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Tiwari, A.K., Taufemback, C.G. & Kumar, S. A Sequential Bayesian Change-Point Analysis of BRICS Currency Returns. J. Quant. Econ. 19, 393–402 (2021). https://doi.org/10.1007/s40953-020-00227-7
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DOI: https://doi.org/10.1007/s40953-020-00227-7