Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis

Joao Caldeira, Rangan Gupta, Tahir Suleman and Hudson Torrent
Additional contact information
Joao Caldeira: Department of Economics, Universidade Federal do Rio Grande do Sul and CNPq, Brazil
Tahir Suleman: School of Economics and Finance, Victoria University of Wellington & School of Business, Wellington Institute of Technology, New Zealand
Hudson Torrent: Department of Statistics, Universidade Federal do Rio Grande do Sul, Brazil

No 201911, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper, we develop a non-parametric functional data analysis (NP-FDA) model to forecast the term-structure of Brazil, Russia, India, China and South Africa (BRICS). We use daily data over the period of January 1, 2010 to December 31, 2016. We find that, while it is in general difficult to beat the random-walk model in the shorter-horizons, at longer-runs our proposed NP-FDA approach outperforms not only the random-walk model, but also other popular competitors used in term-structure forecasting literature. Our results have important implications for both policymakers aiming to stabilize the economy, and for optimal portfolio allocation decisions of financial market agents.

Keywords: Functional data analysis; yield curve forecasting; performance evaluation; BRICS (search for similar items in EconPapers)
JEL-codes: C53 E43 G17 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2019-02
New Economics Papers: this item is included in nep-cis, nep-for and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Journal Article: Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis (2021)
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