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Calendar effects in Latin American stock markets

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Abstract

One of the most well-documented empirical regularities in international finance is the presence of calendar effects in historical stock returns. The literature focuses mainly on developed countries, and in general, emerging markets have not received much attention on this issue. We aim to bridge this gap by documenting the existence of significant and robust calendar effects for the main stock markets in Latin America. Upon performing an extreme bounds analysis that adjusts our estimations for model uncertainty, we find a significantly negative Monday effect, generally compensated by a significantly positive Friday effect. These effects are robust to model specification and are stable through time. Even though not as widespread, we also find evidence for a robust turn-of-the-month effect.

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Notes

  1. The coefficients \(\delta _{d'}\) and \(\mu _{m'}\) are dropped from (4) and hence need to be computed from the restrictions in (7). The effect coding approach provides also a convenient computational trick to overcome this limitation, in order to obtain a complete profile of day or month effects. Consider another base day \(d'' \ne d'\). Then, it is simple to verify that

    $$\begin{aligned} \sum _{i \ne d'}\delta _i (D_{it} - D_{d't}) = \sum _{i \ne d'}\delta _i (D_{it} - D_{d't}) + \sum _{i }\delta _i (D_{d't} - D_{ d'' t}) = \sum _{i \ne d''}\delta _i (D_{it} - D_{d''t})\,. \end{aligned}$$

    This equivalence means that regardless on whether the regression uses \(d'\) or \(d''\) as the base day, the estimated \(\delta \)s (other than \(\delta _{d'}\) and \(\delta _{d''}\)) will be identical. Thus, \(\delta _{d'}\) and its standard error can be estimated directly from the output of an auxiliary regression using \(d''\) as a base day.

  2. The actual jackknife estimator of the variance measures the dispersion of the T delete-one estimators (i.e., the estimators of \(\varvec{\beta }\) after removing one observation from the sample) around its sample average. In the HC3 estimator, the dispersion is measured around the least squares estimate. In our empirical work, the average delete-one estimates turned out to be almost identical to the least squares estimates, pointing out to negligible finite sample biases. An implication is that HC3 provides a very accurate approximation to the actual, computationally more demanding, jackknife estimator. Details on this comparison are available upon request.

  3. An exception is Kristjanpoller and Muñoz (2012), who provide evidence for significant weekend effects in all Latin American markets under study. Their approach, however, is based on nonparametric tests of stochastic dominance and is not directly comparable to our parametric, regression-based approach.

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Authors and Affiliations

  1. Universidad del Pacífico (Lima, Perú), Av. Salaverry 2020, Lima 11, Peru

    Diego Winkelried & Luis A. Iberico

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  1. Diego Winkelried
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  2. Luis A. Iberico
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Correspondence to Diego Winkelried.

Additional information

We thank Mauricio Barriga for valuable research assistance and insight. We are also indebted to Alejandro Sancho, Mauricio Zevallos, Eduardo Walker, to participants at the II Annual Congress of the Peruvian Economic Association and at the XXXIII Economists Meeting of the Central Reserve Bank of Peru for useful comments, and to two anonymous referees for helping us improving the content and clarity of this article. The financial support of the Universidad del Pacífico Research Center is gratefully acknowledged. We alone are responsible for the views expressed here and for any errors that may remain.

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Winkelried, D., Iberico, L.A. Calendar effects in Latin American stock markets. Empir Econ 54, 1215–1235 (2018). https://doi.org/10.1007/s00181-017-1257-y

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