The Yield Curve Factors and Economic Surprises in the Chilean Bond Market

Ceballos, Luis

doi:10.4067/s0718-88702014000200001

Cited by 7 publications

(6 citation statements)

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“…The author concludes that the dynamics of yields are explained by two latent factors, but no identification of term premia was examined. Finally, the economic iteration between the term structure and macroeconomic variables has been reported extensively in Chile (see Ochoa (2006), Morales (2010), Alfaro et al (2011) and (Ceballos 2014)) although there is no term premia derivation. Thus, to the best of our knowledge, this is the first paper attempting to decompose and analyze the term premia in the nominal interest rates in Chile.…”

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confidence: 96%

Nominal term structure and term premia: evidence from Chile

2016

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The downward trend exhibited in Chile's nominal term structure since 2003 has been a common pattern shared by other developed and developing economies. To understand the behavior of the nominal yield curve in Chile, we rely on an affine dynamic term structure model (DTMS) which allows to decompose the term structure into the expected short-term premium (related to the monetary policy expectation) and a term premia. We show that most of the fall of long-term interest rates as well as its dynamics are related to the term premia rather than the expected short-term interest rate. With this, we report that the term premia is driven primarily by nominal uncertainty, i.e. the uncertainty for expected inflation and the US term premia.

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Nominal term structure and term premia: evidence from Chile

2016

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“…Para as economias chilena e mexicana, alguns trabalhos recentes destacam-se, como os de Morales (2010), Ceballos (2014), e Cortés Espada e Ramos-Francia (2008;2009). No caso do Chile, Morales (2010) utilizou de um modelo VAR, com aplicação de filtro de Kalman, de forma que as estimações realizadas dão suporte à interação dinâmica entre os fatores latentes da curva de juros e variáveis macroeconômicas.…”

Section: Estrutura a Termo Da Taxa De Jurosunclassified

“…No caso do Chile, Morales (2010) utilizou de um modelo VAR, com aplicação de filtro de Kalman, de forma que as estimações realizadas dão suporte à interação dinâmica entre os fatores latentes da curva de juros e variáveis macroeconômicas. Ceballos (2014), estimando o modelo NS e análise de componente principal, sugere que anúncios de resultados macroeconômicos possuem impacto na determinação dos movimentos da curva de juros do Chile, por ambas as abordagens metodológicas empregadas.…”

Section: Estrutura a Termo Da Taxa De Jurosunclassified

“…As variáveis macroeconômicas também determinam o movimento e o formato da curva de juros, de acordo com os achados de Morales (2010) e Ceballos (2014) para economia chilena, e de Cortés Espada e Ramos-Francia (2008) e Cortés Espada e Ramos-Francia (2009) para o México. Ceballos (2014) examinou qual o impacto de anúncios nacionais e internacionais, relativos com a macroeconomia, sobre a curva de juros do Chile.…”

Section: Introductionunclassified

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Title: analysis of term structure of interest rates in Latin America countries from 2006 to 2014

et al. 2015

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This article aims to investigate the relationship between the term structure of interest rates and macroeconomic factors in selected countries of Latin America, such as Brazil, Chile and Mexico, between 2006 and 2014, on an autoregressive vector model. Specifically, we perform estimations of Nelson-Siegel, Diabold-Li and principal component analysis to test how the change of macroeconomic factors, e.g. inflation, production and unemployment levels affect the yield curves. For Brazil and Mexico, GDP and inflation variables are relevant to change the yield curves, with the former shifting more the level, and the latter with greater influence on the slope. For Chile, inflation had the greatest impact on the level and, specifically for Mexico, the unemployment variable also changed the slope of the yield curve.

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“…Study of yield curve behavior has been an import part of financial market research as it provides us important information about the future expectation of growth, inflation, recession, etc. Modeling interest rates for the purposes of pricing of interest rate dependent cash flows and hedging the interest rate risk have been a topic of much interest to actuaries over recent decades (see for example [8], [4], [7] and [1]). These studies demonstrate both similarities and differences in international bond markets.…”

Section: Introductionmentioning

confidence: 99%

On the Risk Factors of the Yield in the Cryptocurrencies Market

Kozubík¹,

Žilina²

2018

Recent Advances in IT, Tourism, Economics, Management and Agriculture

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A cryptocurrencies are considered as digital assets that use strong cryptography to secure financial transactions, control the creation of additional units, and verify the transfer of assets. Bitcoin was released as the first and the most popular cryptocurrency in 2009. Since its release, over 4000 alternative cryptocurrencies have been released. After a period of gradual growth of the Bitcoin value, we were able to observe a dramatically increasing in its value at the beginning of this year. This was followed by a subsequent rapid decline to the value it keeps to this day. A similar development we can, however, observe with other cryptocurrencies. This paper presents the results of an empirical analysis of the nature of the factors that explain changes in yields of the ten most traded cryptocurrencies. Consistent with the analysis of the current currencies yield curves, the principal component method has shown that two or three factors are sufficient to explain most of the yield variation. These results are essential for hedging purposes.

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The Yield Curve Factors and Economic Surprises in the Chilean Bond Market

Cited by 7 publications

References 13 publications

Nominal term structure and term premia: evidence from Chile

Nominal term structure and term premia: evidence from Chile

Title: analysis of term structure of interest rates in Latin America countries from 2006 to 2014

On the Risk Factors of the Yield in the Cryptocurrencies Market

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