Evaluation of exchange rate point and density forecasts: An application to Brazil

Gaglianone, Wagner Piazza; Marins, Jaqueline Terra Moura

doi:10.1016/j.ijforecast.2016.12.002

Cited by 8 publications

(3 citation statements)

References 71 publications

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“…The literature on FX rate dynamics in Brazil has also been fruitful in recent years. For instance, see Minella et al (2003), Bevilaqua and Azevedo (2005), Silva Jr. (2010), Wu (2012), Kohlscheen (2014), Gaglianone and Marins (2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Impacts of the Monetary Policy Committee decisions on the foreign exchange rate in Brazil

2022

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The purpose of this paper is to measure the impact of interest rate decisions of the Monetary Policy Committee (MPC) on foreign exchange (FX) rate in Brazil. Two new daily measures of interest rate surprises are proposed using market and survey data. The results indicate a significant effect of MPC's decisions on FX returns. In particular, the surprise variable based on market data is statistically significant to explain FX returns and has a negative sign, as expected (a positive surprise implies an appreciation of the domestic currency). Moreover, this effect is symmetric, in terms of positive or negative surprises, and does not depend on the level of Selic interest rate. Nonetheless, the surprise variable is not significant to explain FX returns in recent years, under a single-digit interest rate regime. Robustness exercises—using GARCH models or including FX market official intervention series as additional controls—corroborate the previous findings.

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Section: Literature Reviewmentioning

confidence: 99%

Impacts of the Monetary Policy Committee decisions on the foreign exchange rate in Brazil

2022

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“…The Brazilian case is interesting since its exchange rate is floating according to the IMF classification, Brazil is one of the largest emerging economies, and the Brazilian Real has shown high volatility and moments of great depreciation in recent years, with significant impacts on the macroeconomic environment. However, exchange rate forecasting papers for the Brazilian currency focus on monthly and daily frequencies, as in Gaglianone and Marins (2017) and Moura et al (2008).…”

Section: Introductionmentioning

confidence: 99%

Brazilian Exchange Rate Forecasting in High Frequency

Rossi¹,

Piccioni²,

Rossi³

et al. 2022

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We investigated the predictability of the Brazilian exchange rate at High Frequency (1, 5 and 15 minutes), using local and global economic variables as predictors. In addition to the Linear Regression method, we use Machine Learning algorithms such as Ridge, Lasso, Elastic Net, Random Forest and Gradient Boosting. When considering contemporary predictors, it is possible to outperform the Random Walk at all frequencies, with local economic variables having greater predictive power than global ones. Machine Learning methods are also capable of reducing the mean squared error. When we consider only lagged predictors, it is possible to beat the Random Walk if we also consider the Brazilian Real futures as an additional predictor, for the frequency of one minute and up to two minutes ahead, confirming the importance of the Brazilian futures market in determining the spot exchange rate.

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“…al., 2010;Zhou et. al., 2006), AR-GARCH (Gaglianone & Marins, 2017) and ARMA-GARCH (Liu & Shi, 2013;Wang et. al., 2005).…”

Section: Introductionmentioning

confidence: 99%

Multistep Forecasting for Highly Volatile Data using A New Box-Jenkins and GARCH Procedure

Yaziz¹,

Zakaria²,

Boland³

2020

ASMSJ

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The study of the multistep ahead forecast is significant for practical application purposes using the proposed statistical model. This study proposes a new procedure of Box-Jenkins and GARCH (or BJ-G) in evaluating the multistep forecasting performance for a highly volatile time series data. The promising results from one-step ahead out-of-sample forecast series using the BJ-G model has motivated the extension to multiple step ahead forecast. In order to achieve the objective, the procedure of multistep ahead forecast for BJ-G model is proposed using R language. In evaluating the performance of the multistep ahead forecast, the proposed procedure is employed to daily world gold price series of 5-year data. Based on the empirical results, the proposed procedure of multistep ahead forecast enhances the existing procedure of BJ-G which is able to provide a promising procedure to assess the performance of the BJ-G model in forecasting a highly volatile time series data. The procedure adds the value of BJ-G model since it allows the model to describe efficiently the characteristics of the volatile series up to n-step ahead forecast. Keywords: Box-Jenkins, GARCH, highly volatile data, multistep forecast; gold price

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Evaluation of exchange rate point and density forecasts: An application to Brazil

Cited by 8 publications

References 71 publications

Impacts of the Monetary Policy Committee decisions on the foreign exchange rate in Brazil

Impacts of the Monetary Policy Committee decisions on the foreign exchange rate in Brazil

Brazilian Exchange Rate Forecasting in High Frequency

Multistep Forecasting for Highly Volatile Data using A New Box-Jenkins and GARCH Procedure

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