A set of RLS-type models with ARMA and ARFIMA dynamics is estimated and compared in a forecasting exercise with ARFIMA, GARCH and FIGARCH models. It is an extension of Rodríguez (N Am J Econ Financ 42:393–420, 2017) but using more countries and working with squared returns in the forecasting exercise. The estimation results show: (i) existence of RLS; (ii) measurement errors except in Chile and Colombia. Regarding the fractional parameter, the estimates are quite small indicating the possible absence of long memory with possible exceptions of Chile and Colombia. The forecast exercise using the 10% MCS of Hansen et al. (Econometrica 79:453–497, 2011) and the ratios of MSFE indicate absence of the RLS-ARFIMA models while RLS-ARMA models are selected. In general, the results of the estimations and forecasts indicate probable absence of long memory or its small magnitude, which would makes this characteristic not only unnecessary but also irrelevant to capture the variations of the low frequencies of the series.

中文翻译：

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关于估计和预测拉丁美洲外汇收益波动的经验性说明：长期记忆和随机水平移动成分的作用

在带有ARFIMA，GARCH和FIGARCH模型的预测练习中，估计并比较了一组具有ARMA和ARFIMA动力学的RLS类型模型。它是Rodríguez（N Am J Econ Financ 42：393–420，2017）的扩展，但使用了更多的国家，并在预测工作中使用平方收益。估计结果表明：（i）存在RLS；（ii）除智利和哥伦比亚外的测量误差。关于分数参数，估计值很小，表明可能没有很长的记忆力，但智利和哥伦比亚可能例外。使用Hansen等人的10％MCS进行预测。（Econometrica 79：453–497，2011）和MSFE的比率表明缺少RLS-ARFIMA型号，而选择了RLS-ARMA型号。通常，估计和预测的结果表明可能没有长记忆或记忆强度较小，这将使此特性不仅不必要，而且与捕获序列低频变化无关。