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

Caldeira, João Frois; Gupta, Rangan; Suleman, Muhammad Tahir; Torrent, Hudson S.

doi:10.1080/1540496x.2020.1808458

Cited by 11 publications

(9 citation statements)

References 76 publications

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“…It is worth mentioning that prior to the pandemic outbreak, the literature on the yield termstructures for both developed and developing economies has experienced a significant expansion; see [36][37][38][39][40][41][42][43] among many others. A number of studies have analyzed the interrelationship between the macro-economic parameters and the shape of the sovereign debt curves in US [35,36,41,[44][45][46], Canada [38,47]] and in the European Union [37,39,48].…”

Section: Forecasting the Term-structure Of Interest Ratesmentioning

confidence: 99%

“…A number of studies have analyzed the interrelationship between the macro-economic parameters and the shape of the sovereign debt curves in US [35,36,41,[44][45][46], Canada [38,47]] and in the European Union [37,39,48]. Other researchers have focused on forecasting the shapes of the yield curves for BRICS [42].…”

Section: Forecasting the Term-structure Of Interest Ratesmentioning

confidence: 99%

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The impact of the Covid-19 related media coverage upon the five major developing markets

2021

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This paper analyses the influence of the Covid-19 coverage by the social media upon the shape of the sovereign yield curves of the five major developing countries, namely Federative Republic of B razil, Russian Federation, Republic of India, People’s Republic of China, and the Republic of South Africa (BRICS). The coherenc e between the level, slope, and the curvature of the sovereign yield term structures and the Covid-19 medi a coverage is found to vary between low and high ranges, depending on the phases of the pandemic. The empirical estimations of the yield-curve factors a re performed by means of the Diebold–Li modified version of the Nelson–Siegel model. The intervals of low coherence reveal the capacity of the two latent factors, level and slope, to be used for creating cross-factor diversification strategies, workable under crisis conditions, as evidenced on the example of the ongoing pandemic. Diverse coherence patterns are reported on a per-country basis, highlighting a promising potential of sovereign debt investments for designing cross-country and cross-factor fixed-income strategies, capable of hedging downside risks.

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Section: Forecasting the Term-structure Of Interest Ratesmentioning

confidence: 99%

Section: Forecasting the Term-structure Of Interest Ratesmentioning

confidence: 99%

The impact of the Covid-19 related media coverage upon the five major developing markets

2021

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“…This, in turn, can have deep impact on the exposure to country risk: the economic, political and social contexts can eventually cause losses to foreign investors. After all, BRICS countries inspired many research strands Bekiros and Avdoulas (2020), de Boyrie and Pavlova (2016), Zeb and Rashid (2019), Salisu et al (2021); however, with the exception of El-Shagi and Jiang (2019) and Caldeira et al (2020), to the best of our knowledge, there aren't other works analyzing altogether BRICS yield curves and at the same time investigating on them the interpolation capabilities of various techniques. Such an investigation can be useful under various viewpoints: many central banks use to interpolate yield curves to assess monetary policy measures; in addition such models have an economic interpretation and they can be useful for measuring risk in fixed income portfolios.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Yield Curve of BRICS Countries: Parametric vs. Machine Learning Techniques

Castello

Resta

2022

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We compare parametric and machine learning techniques (namely: Neural Networks) for in–sample modeling of the yield curve of the BRICS countries (Brazil, Russia, India, China, South Africa). To such aim, we applied the Dynamic De Rezende–Ferreira five–factor model with time–varying decay parameters and a Feed–Forward Neural Network to the bond market data of the BRICS countries. To enhance the flexibility of the parametric model, we also introduce a new procedure to estimate the time varying parameters that significantly improve its performance. Our contribution spans towards two directions. First, we offer a comprehensive investigation of the bond market in the BRICS countries examined both by time and maturity; working on five countries at once we also ensure that our results are not specific to a particular data–set; second we make recommendations concerning modelling and estimation choices of the yield curve. In this respect, although comparing highly flexible estimation methods, we highlight superior in–sample capabilities of the neural network in all the examined markets and then suggest that machine learning techniques can be a valid alternative to more traditional methods also in presence of marked turbulence.

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“…Even though the main focus of the worldwide academy research currently remains centered on US Treasury yield curve, it is worth mentioning some studies that address the interrelationship of economic drivers and the shape of the sovereign debt curves in other geographies (Nyholm, 2015 ; Nymand-Andersen, 2018 ; Barunik & Fiser, 2019 , and Umar et al, 2020 ). Ojo et al, ( 2017 ), study the components of the term structure in Canada, while (Vieira et al, 2017 , and Caldeira et al, 2020 ), are focused on emerging market countries from the bloc known as BRICS (Brazil, Russia, India, China, and South Africa).…”

Section: Introductionmentioning

confidence: 99%

Oil price shocks and the term structure of the US yield curve: a time–frequency analysis of spillovers and risk transmission

et al. 2022

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This paper investigates the influence of oil demand, oil supply, and risk-driven shocks on the yield curve in the US between 1995 and 2020. The US term-structure shape is modeled by three structural factors, the level, slope, and curvature. Their empirical analysis is performed according to the Diebold-Li modified variant of the widely used Nelson-Siegel model. The technique of wavelet analysis allows investigating the interrelation of shocks in oil prices and the US yield curve along time and frequency domains, simultaneously. We report on low, medium, and high coherence zones, relative to the oil price movements and the changes in the three yield-curve factors. The low coherence intervals indicate the potential for the three latent factors to be used for creating diversification strategies capable of hedging adverse dynamics in the oil market, potentially workable through global crises. We document the variability of dynamic patterns observable for the US sovereign yield factors on per-type-of-shock basis, evidencing the potential role of the US sovereign debt investments for designing cross-asset hedge strategies for commodity and fixed-income markets.

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

Cited by 11 publications

References 76 publications

The impact of the Covid-19 related media coverage upon the five major developing markets

The impact of the Covid-19 related media coverage upon the five major developing markets

Modeling the Yield Curve of BRICS Countries: Parametric vs. Machine Learning Techniques

Oil price shocks and the term structure of the US yield curve: a time–frequency analysis of spillovers and risk transmission

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