A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries

Nara Rossetti, Marcelo Seido Nagano, Jorge Luis Faria Meirelles

Abstract


Purpose – This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany and Japan) from January 2000 to December 2011 by examining the interbank interest rates from each market.

Design/methodology/approach – To the volatility of interest rates returns, the study used models of auto-regressive conditional heteroscedasticity, autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), exponential generalized autoregressive
conditional heteroscedasticity (EGARCH), threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and periodic generalized autoregressive conditional heteroscedasticity (PGARCH), and a combination of these with autoregressive integrated moving average (ARIMA) models, checking which
of these processes were more efficient in capturing volatility of interest rates of each of the sample countries.

Findings – The results suggest that for most markets, studied volatility is best modelled by asymmetric GARCH processes – in this case the EGARCH – demonstrating that bad news leads to a higher increase in the volatility of these markets than good news. In addition, the causes of increased volatility seem to be more associated with events occurring internally in each country, as changes in macroeconomic policies, than the overall external events.

Originality/value – It is expected that this study has contributed to a better understanding of the volatility of interest rates and the main factors affecting this market.

Propósito – Este estudio analiza la volatilidad del mercado de renta fija de once países (Brasil, Rusia, India, China, Sudáfrica, Argentina, Chile, México, Estados Unidos, Alemania y Japón) de enero de 2000 a diciembre de 2011, mediante el examen de las tasas de interés interbancarias de cada mercado.


Diseño/metodología/enfoque – Para la volatilidad de los retornos de las tasas de interés, se utilizaron modelos de heteroscedasticidad condicional autorregresiva: ARCH, GARCH, EGARCH, TGARCH y PGARCH, y una combinación de estos con modelos ARIMA, comprobando cuáles de los procesos eran más eficientes para capturar la volatilidad de interés de cada uno de los países de la muestra.

Hallazgos – Los resultados sugieren que para la mayoría de los mercados estudiados la volatilidad es mejor modelada por procesos GARCH asimétricos—en este caso el EGARCH—demostrando que las malas noticias conducen a un mayor incremento en la volatilidad de estos mercados que las buenas noticias. Además, las causas de una mayor volatilidad parecen estar más asociadas a eventos que ocurren internamente en cada país, como cambios en las políticas macroeconómicas, que los eventos externos generales.

Originalidad/valor – Se espera que este estudio contribuya a un mejor entendimiento de la volatilidad de las tasas de interés y de los principales factores que afectan a este mercado.


Keywords


Volatility; emerging countries; ARCH-GARCH models; fixed income; ingreso fijo; volatilidad; países emergentes; modelos ARCH-GARCH

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Copyright (c) 2018 The bi-annual academic publication of Universidad ESAN

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

The Universidad ESAN, with more than 50 years of experience in the higher education field and post graduate studies, desires to contribute to the academic community with the most outstanding pieces of research. We gratefully welcome suggestions and contributions from our readers in order to help
us hit our goals.