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

Author

Listed:
  • Rossetti, Nara

    (Department of Production Engineering, Federal University of São Carlos, Sorocaba, Brazil)

  • Seido , Marcelo

    (Department of Production Engineering, Universidade de São Paulo, São Carlos, Brazil)

  • Faria , Jorge

    (Department of Production Engineering, Federal University of São Carlos, Sorocaba, Brazil)

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.

Suggested Citation

  • Rossetti, Nara & Seido , Marcelo & Faria , Jorge, 2017. "A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 22(42), pages 99-128.
    • Handle: RePEc:ris:joefas:0110
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    Citations

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    Cited by:

    1. Muhammad Niaz Khan & Suzanne G. M. Fifield & David M. Power, 2024. "The impact of the COVID 19 pandemic on stock market volatility: evidence from a selection of developed and emerging stock markets," SN Business & Economics, Springer, vol. 4(6), pages 1-26, June.
    2. Aslam, Faheem & Hunjra, Ahmed Imran & Memon, Bilal Ahmed & Zhang, Mingda, 2024. "Interplay of multifractal dynamics between shadow policy rates and energy markets," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    3. Cangrejo Esquivel, Álvaro Javier & Tovar Cuevas, José Rafael & García, Isabel Cristina & Manotas Duque, Diego Fernando, 2022. "Estimación clásica y bayesiana de la volatilidad en el modelo de Black-Scholes [Classical and Bayesian estimation of volatility in the Black-Scholes model]," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 34(1), pages 237-262, December .

    More about this item

    Keywords

    Volatility; Emerging countries; ARCH-GARCH models; Fixed income;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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