A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
Keywords:
Volatility, Emerging countries, ARCH-GARCH models, Fixed incomeAbstract
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.
Downloads
References
Acioly, L., Chernavsky, E. and Leão, R. (2010), “Crisis internacional: medidas de políticas de países selecionados [International crisis: policy measures of selected countries]”, Brasília: Boletim de Economia e Política Internacional [Brasília: International Economy and Policy Bulletin], IPEA, p. 1.
Alberg, D., Shalit, H. and Yosef, R. (2008), “Estimating stock market volatility using asymmetric GARCH models”, Applied Financial Economics, Vol. 18, pp. 120-1208.
Alexander, C. (2005), Modelos De Mercado: um Guia Para Análise de Informações Financeiras [MarketModels: a Guide for Financial Information Analysis], BM&F/Saraiva, São Paulo.
Andritzky, J.R., Bannister, G. and Tamirisa, N. (2007), “The impact of macroeconomic announcements on emerging market bonds”, Emerging Markets Review, Vol. 8 No. 1, pp. 20-37.
Baillie, R.T., Bollerslev, T. and Mikkelsen, H.O. (1996), “Fractionally integrated generalized autoregressive conditional heteroskedasticity”, Journal of Econometrics, Vol. 74 No. 1, pp. 3-30. Brazilian Central Bank (2012), “Interest rate history”, available at: www.bcb.gov.br/?COPOMJUROS, (accessed 15 December 2012).
BM&FBOVESPA (2011), “São Paulo stock exchange”, available at: www.bmfbovespa.com.br (accessed 7 August 2011).
Bollerslev, T. (1986), “Generalized autoregressive conditional heterocedasticity”, Journal of Econometrics, Vol. 31, pp. 307-327.
Bollerslev, T., Engle, R.F. and Wooldridge, J.M. (1998), “A capital asset pricing model with time varying covariances”, Journal of Political Economy, Vol. 96 No. 1, pp. 116-131.
Bollerslev, T. (2008), “Glossary to ARCH (GARCH)”, Creates Research Paper No. 49, pp. 1-46.
Corrêa, D. and Lima, G.T. (2008), “Reformas institucionais e crescimento econômico: a experiência Chilena [institutional reforms and economic growth: the Chilean experience]”, Revista de Desenvolvimento Econômico, Vol. 10 No. 17, pp. 83-91.
Cosgrove, M. and Marsh, D. (2010), “Lessons from Japan”, International Business & Economics Research Journal, Vol. 9 No. 5, pp. 95-101.
Dacorogna, M.M., Müller, U.A., Pictet, O.V. and Olsen, R.B. (1998), “Modelling short term volatility with GARCH and HARCH models”, in Dunis, C. and Zhou, B. (Eds), Nonlinear Modeling of High Frequency Financial Time Series, Wiley.
Desai, P. (2006), “Why is Russian GDP growth slowing?”, The American Economic Review, Vol. 96 No. 2, pp. 342-347.
Dihn, T.H. and Nguyen, D.K. (2008), “The global and regional factors in the volatility of emerging sovereign bond markets”, American Journal Finance and Accounting, Vol. 1 No. 1, pp. 52-68.
Ding, Z., Granger, C.W.J. and Engle, R.F. (1993), “A long memory property of stock market returns and a new model”, Journal of Empirical Finance, Vol. 1 No. 1, pp. 83-106.
Edwards, S. and Susmel, R. (2003), “Interest-rate volatility in emerging markets”, The Review of Economics and Statistics, Vol. 85 No. 2, pp. 328-348.
Elliot, G., Rothenberg, T.J. and Stock, J.H. (1996), “Efficient tests for an autoregressive unit root”, The Econometric Society, Vol. 64 No. 4, pp. 813-836.
Enders,W. (2004), Applied Econometric Time Series, Iowa State University: John Wiley&Sons.
Engle, R.F. (1982), “Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation”, Econometrica, Vol. 50 No. 4, pp. 987-1008.
Engle, R.F. (1990), “Discussion: stock market volatility and the crash of ’87”, Review of Financial Studies, Vol. 3 No. 1, pp. 103-106.
Engle, R.F. and Kroner, K.F. (1995), “Multivariate simultaneous generalized ARCH”, Economy Theory, Vol. 11 No. 1, pp. 122-150.
Engle, R.F. and Lee, G.G.J. (1999), “A permanent and transitory component model of stock return volatility”, in Engle, R.F. and White, H. (Eds), Cointegration, Causality, and Forecasting: A
Festschrift in Honor of Clive W.J. Granger, Oxford University Press, pp. 475-497.
Fabozzi, F.J. (2000), Bonds Markets: Analysis and Strategies, Prentice Hall, New Jersey, NJ.
Fama, E.F. (1965), “The behavior of stock-market prices”, The Journal of Business, Vol. 38 No. 1, pp. 34-105.
Gertler, M. and Karadi, P. (2010), “A model of unconventional monetary policy”, Journal of Monetary Economics, Vol. 58 No. 1, pp. 17-34.
Girard, E. and Biwas, R. (2007), “Trading volume and market volatility: developed versus emerging stock markets”, The Financial Review, Vol. 42 No. 3, pp. 429-459.
Glosten, L.R., Jagannathan, R. and Runkle, D. (1993), “On the relation between the expected value and the volatility of the nominal excess return on stocks”, Journal of Finance, Vol. 48 No. 5, pp. 1779-1801.
Goeu, P. and Marquering, W. (2004), “Modeling the conditional variance between bonds and stock returns: a multivariate GRACH approach”, Journal of Financial Econometrics, Vol. 2 No. 4, pp. 531-564.
Gujarati, D.N. (2006), Econometria Básica [Basic Econometrics], 4th ed., PearsonMakron Books, São Paulo.
Haugen, R.A. (1997), Modern Investment Theory, Prentice Hall, New Jersey, NJ.
Higgins, M.L. and Bera, A.K. (1992), “A class of nonlinear ARCH models”, International Economic Review, Vol. 33 No. 1, pp. 137-158.
Hoshi, T. and Kashyap, N.K. (2004), “Japan’s financial crisis and economic stagnation”, Journal of Economic Perspectives, Vol. 18 No. 1, pp. 3-26.
IMF (International Monetary Fund) (2012), “World economic outlook database”, available at: www.imf.org (accessed 12 October 2012).
IMF (International Monetary Fund) (2013), “World economic outlook database”, available at: www.imf.org (accessed 10 January 2013).
IPEADATA Brazilian Institute of Applied Economic Research (2013), “Macroeconomic, regional and social database”, available at: www.ipeadata.gov.br (accessed 15 January 2010, 18 June 2011 and 16 December 2013).
Jarque, C.M. and Bera, A.K. (1987), “A test for normality of observations and regression residuals”, International Statistical Review, Vol. 55 No. 2, pp. 163-172.
Karagiannis, S.K., Vlamis, P. and Panagopoulos, Y. (2010), “The emerging BRIC economies: evidence from the interest rate transmission mechanism”, Eurasia Business and Economic Society (EBES). Conference, Athens.
Ke, J., Chen, Z. and Zhang, R. (2008), “Comparative analysis of international stock market volatility with ARCH model”, Anais: International Seminar on Future Information Technology and Management Engineering, pp. 494-497.
Krugman, P.R. and Obstfeld, M. (1999), Economia Internacional Teoria e Política [International Economy: Theory and Policy], 4th ed.,Makron Books, São Paulo.
Kwiatkowski, D., Phillips, P.C.B., Schmidt, P. and Shin, Y. (1992), “Testing the null hypothesis of stationarity against the alternative of a unit root”, Journal of Econometrics, Vol. 54, pp. 159-178.
Macit, F. (2012), “Who responds more to monetary policy, conventional banks or participation banks?”, Journal of Economics, Finance and Administrative Science, Vol. 17 No. 33, pp. 10-14.
Mankiw, N.G. (2005), Introdução a Economia [Introduction to Economics], Cengage Learning, São Paulo.
Miyagawa, T. (2011), “Economic slowdown in Japan and the role of intangible assets on the revitalization of the Japanese economy. Research unit for statistical and empirical analysis in social sciences (Hi-Stat)”, Discussion Paper Series 162, Institute of Economic Research-Hitotsubashi University.
Müller, U.A., Dacorogna, M.M., Davé, R.D., Olsen, R.B., Pictet, O.V. and Weizsäcker, J.V. (1997), “Volatilities of different time resolutions – analyzing the dynamics of market components”, Journal of Empirical Finance, Vol. 4 Nos 2/3, pp. 213-239.
Mulugetta, A. and Mulugetta, Y. (2009), “Labor, capital service, and productivity contributions to national economic growth: focusing on the Japanese case”, Global Economy Journal, Vol. 9 No. 3, pp. 1-19.
Nelson, D.B. (1991), “Conditional heteroskedasticity in asset returns: a new approach”, Econometrica, Vol. 59 No. 2, pp. 347-370.
Nguyen, V.B. (2015), “Effects of fiscal deficit and money M2 supply on inflation: evidence from selected economies of Asia”, Journal of Economics, Finance and Administrative Science, Vol. 20 No. 38, pp. 49-53.
Phillips, P.C.B. and Perron, P. (1988), “Testing for a unit root in time series regression”, Biometrika, Vol. 75 No. 2, pp. 335-346.
Pinheiro, J.L. (2009), Mercado de Capitais: Fundamentos e Técnicas [Capital Market: Fundamentals and Techniques], Atlas, São Paulo.
Polwitoon, S. and Tawatnuntachai, O. (2008), “Emerging market bond funds: a comprehensive analysis”, The Financial Review, Vol. 43, pp. 51-84.
Reilly, F.K., Chan, K.C. and Wright, D.J. (2000), “Bond market volatility compared to stock market volatility”, Journal of Portfolio Management, Vol. 27 No. 1, pp. 82-92.
Said, S.E. and Dickey, D.A. (1984), “Testing for unit roots in autoregressive-moving average models of unknown order”, Biometrika, Vol. 71 No. 3, pp. 599-607.
Stock, J.H. and Watson, M.K. (2004), Econometria [Econometrics], Addison Wesley, São Paulo.
Taylor, S.J. (2005), Asset Price Dynamics, Volatility, and Prediction, Princeton University Press, Princeton.
Vadell, J.A. (2006), “A política internacional, a conjuntura econômica e a Argentina de Néstor Kirchner [international policy, economic conjuncture and Nestor Kirchner’s Argentina]”, Revista Brasileira de Política Internacional, Vol. 49 No. 1, pp. 194-214.
Wet, W.A. (2006), “A structural GARCH model: an application on South African data”, Economic Modelling, Vol. 23, pp. 775-791.
Wilmott, P. (2001), Introduces Quantitative Finance, John Wiley&Sons, Chichester.
World Bank (2011), “Databank”, available at: www.worldbank.org (accessed on 10 October 2010, 4 January 2011, 25 March 2011 and 16 May).
Yang, J., Zhou, Y. and Wang, Z. (2009), “The stock–bond correlation and macroeconomic conditions: one and a half centuries of evidence”, Journal of Banking & Finance, Vol. 33,
pp. 670-680.
Young, P.J. and Johnson, R. (2002), “Bond market volatility compared with stock market volatility: evidence from the UK”, Journal of Asset Management, Vol. 3 No. 2, pp. 101-111.
Young, P.J. and Johnson, R. (2005), “Bond market volatility vs stock market volatility: the Swiss experience”, Financial Markets and Portfolio Management, Vol. 18 No. 1, pp. 8-23.
Zakoïan, J.M. (1994), “Threshold heteroskedastic models”, Journal of Economic Dynamics and Control, Vol. 18, pp. 931-955.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Journal of Economics, Finance and Administrative Science
This work is licensed under a Creative Commons Attribution 4.0 International License.
