Fundamentals Models Versus Random Walk: Evidence From an Emerging Economy

IF 2.7 3区 经济学 Q1 ECONOMICS
Helder Ferreira de Mendonça, Luciano Vereda, Luan Mateus Matos de Araújo
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Abstract

We analyze the predictive power of fundamentals versus random walk models for horizons from 1 to 24 months in an emerging market. Specifically, we investigate what fundamentals models outperform random walk during periods of appreciation and depreciation of the exchange rate. Furthermore, we analyze whether the fundamentals models that beat random walk contain information not considered by market expectations. Based on data from the Brazilian economy, the findings point out that some fundamentals models are useful for forecasting the exchange rate. The predictive power of fundamentals models increases in periods marked by a trend of currency appreciation or depreciation. In particular, the PPP-type fundamentals models have greater predictive power than the random walk and add information to market expectations for different time horizons and periods of exchange rate appreciation and depreciation.

Abstract Image

基本面模型与随机漫步:来自新兴经济体的证据
我们分析了基本面与随机游走模型在新兴市场1至24个月期间的预测能力。具体来说,我们研究了哪些基本面模型在汇率升值和贬值期间优于随机漫步。此外,我们分析战胜随机漫步的基本面模型是否包含市场预期未考虑的信息。基于巴西经济的数据,研究结果指出,一些基本面模型对预测汇率是有用的。在货币出现升值或贬值趋势的时期,基本面模型的预测能力会增强。特别是,ppp类型的基本面模型比随机漫步具有更大的预测能力,并为不同时间范围和汇率升值和贬值时期的市场预期增加了信息。
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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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