Rui Dias – Polytechnic Institute of Setúbal, School of Business and Administration, Esce, Campus do Instituto
Politécnico de Setúbal, Estefanilha, 2914-503 Setúbal, Portugal
Paula Heliodoro – Polytechnic Institute of Setúbal, School of Business and Administration, Esce, Campus do Instituto
Politécnico de Setúbal, Estefanilha, 2914-503 Setúbal, Portugal
Paulo Alexandre – Polytechnic Institute of Setúbal, School of Business and Administration, Esce, Campus do Instituto
Politécnico de Setúbal, Estefanilha, 2914-503 Setúbal, Portugal

 

DOI: https://doi.org/10.31410/LIMEN.S.P.2019.91

 

5th International Scientific-Business Conference – LIMEN 2019 – Leadership, Innovation, Management and Economics: Integrated Politics of Research – SELECTED PAPERS, Graz, Austria, December 12, 2019, published by the Association of Economists and Managers of the Balkans, Belgrade; Printed by: SKRIPTA International, Belgrade, ISBN 978-86-80194-27-1, ISSN 2683-6149, DOI: https://doi.org/10.31410/LIMEN.S.P.2019

 

Abstract

The main goal of this research work is to analyse risk transmission, in a dynamic context,
between stock markets of the Latin American Countries (LAC) region, in the context of the subprime
and European sovereign debt crises. Specifically, we intend to evaluate the volatility transmission between
markets, as well as the respective asymmetric effect. For this purpose, we use a volatility measure
based on opening, closing, maximum and minimum daily prices. We intend to answer the following
questions: do Latin American stock markets show higher levels of volatility resulting from the financial
crises of 2008 and 2010? The results suggest there is a risk transmission resulting from the subprime
crisis. However, the empirical evidence points to a decrease in risk during the sovereign debt crisis of
2010, i.e. the high volatility during the subprime crisis tends to decrease in the period 2010-2012.

 

Keywords

Volatility, Stock markets, GARCH models.

 

 

References

Baba, N., & Packer, F. (2009). From turmoil to crisis: Dislocations in the FX swap market before
and after the failure of Lehman Brothers. Journal of International Money and Finance,
28(8), 1350–1374. https://doi.org/10.1016/j.jimonfin.2009.08.003
Bekaert, G., Harvey, C. R., Lundblad, C. T., & Siegel, S. (2011). What segments equity markets?
Review of Financial Studies, 24(12), 3841–3890. https://doi.org/10.1093/rfs/hhr082
Ben Rejeb, A., & Arfaoui, M. (2016). Financial market interdependencies: A quantile regression
analysis of volatility spillover. Research in International Business and Finance, 36,
140–157. https://doi.org/10.1016/j.ribaf.2015.09.022
Bollerslev, T. (1990). Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate
Generalized Arch Model. The Review of Economics and Statistics. https://doi.
org/10.2307/2109358
Bollerslev, T., Engle, R. F., & Wooldridge, J. M. (1988). A Capital Asset Pricing Model with
Time-Varying Covariances. Journal of Political Economy. https://doi.org/10.1108/eb043389
Brock, W. A., & de Lima, P. J. F. (1996). 11 Nonlinear time series, complexity theory, and finance.
Handbook of Statistics. https://doi.org/10.1016/S0169-7161(96)14013-X
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Predictability of Asset Returns. In
The Econometrics of Financial Markets (pp. 27–82).
Cardona, L., Gutiérrez, M., & Agudelo, D. A. (2017). Volatility transmission between US and
Latin American stock markets: Testing the decoupling hypothesis. Research in International
Business and Finance, 39, 115–127. https://doi.org/10.1016/j.ribaf.2016.07.008
Chuliá, H., Guillén, M., & Uribe, J. M. (2017). Spillovers from the United States to Latin American
and G7 stock markets: A VAR quantile analysis. Emerging Markets Review, 31, 32–
46. https://doi.org/10.1016/j.ememar.2017.01.001

Engle, R. (2002). Dynamic Conditional Correlation. Journal of Business & Economic Statistics,
20(3), 339–350. https://doi.org/10.1198/073500102288618487
Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance
of United Kingdom Inflation. Econometrica, 50(4), 987. https://doi.org/10.2307/1912773
Forbes, K. J., & Rigobon, R. (2002). No Contagion, Only Interdependence: Measuring Stock Market
Comovements. The Journal of Finance, 57(5), 2223–2261. https://doi.org/10.2307/3094510
Gamba-Santamaria, S., Gomez-Gonzalez, J. E., Hurtado-Guarin, J. L., & Melo-Velandia, L. F.
(2017). Stock market volatility spillovers: Evidence for Latin America. Finance Research
Letters, 20, 207–216. https://doi.org/10.1016/j.frl.2016.10.001
Garman, M., & Klass, M. (1980). On the Estimation of Security Price Volatilities from Historical
Data. The Journal of Business, 53(1), 67–68. https://doi.org/10.1086/296072
GLOSTEN, L. R., JAGANNATHAN, R., & RUNKLE, D. E. (1993). On the Relation between the
Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of
Finance, 48(5), 1779–1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.x
Güloğlu, B., Kaya, P., & Aydemir, R. (2016). Volatility transmission among Latin American stock
markets under structural breaks. Physica A: Statistical Mechanics and Its Applications, 462,
330–340. https://doi.org/10.1016/j.physa.2016.06.093
Hassan, S. A., & Malik, F. (2007). Multivariate GARCH modeling of sector volatility transmission.
Quarterly Review of Economics and Finance. https://doi.org/10.1016/j.qref.2006.05.006
Kotkatvuori-Örnberg, J., Nikkinen, J., & Äijö, J. (2013). Stock market correlations during the
financial crisis of 2008-2009: Evidence from 50 equity markets. International Review of
Financial Analysis, 28, 70–78. https://doi.org/10.1016/j.irfa.2013.01.009
Markowitz, H. M. (1952). Portfolio selection. The Journal of Finance, 7(60), 77–91. https://doi.
org/10.1111/j.1540-6261.1952.tb01525.x
Mensah, J. O., & Premaratne, G. (2014). Exploring Diversification Benefits in Asia-Pacific Equity
Markets. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2530363
Nelson, D. B., & Nelson1, D. B. (1991). Conditional Heteroskedasticity in Asset Returns:
A New Approach. Source: Econometrica Econometrica, 59(2), 347–370. https://doi.
org/10.2307/2938260
Rogers, L. C. G., Satchell, S. E., & Yoon, Y. (1994). Estimating the volatility of stock prices: a
comparison of methods that use high and low prices. Applied Financial Economics, 4(3),
241–247. https://doi.org/10.1080/758526905
Syllignakis, M. N., & Kouretas, G. P. (2011). Markov-switching regimes and the monetary model
of exchange rate determination: Evidence from the Central and Eastern European markets.
Journal of International Financial Markets, Institutions and Money, 21(5), 707–723. https://
doi.org/10.1016/j.intfin.2011.04.005
Todea, A. (2016). Cross-correlations between volatility, volatility persistence and stock market
integration: The case of emergent stock markets. Chaos, Solitons and Fractals, 87, 208–215.
https://doi.org/10.1016/j.chaos.2016.04.006
Tse, Y. K., & Tsui, A. K. C. (2002). A Multivariate Generalized Autoregressive Conditional Heteroscedasticity
Model With Time-Varying Correlations. Journal of Business & Economic
Statistics, 20(3), 351–362. https://doi.org/10.1198/073500102288618496
Yarovaya, L., Brzeszczyński, J., & Lau, C. K. M. (2016). Intra- and inter-regional return and
volatility spillovers across emerging and developed markets: Evidence from stock indices
and stock index futures. International Review of Financial Analysis, 43, 96–114. https://doi.
org/10.1016/j.irfa.2015.09.004
Zakoian, J. M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and
Control, 18(5), 931–955. https://doi.org/10.1016/0165-1889(94)90039-6

 

Download Full Paper

 

 

 

Association of Economists and Managers of the Balkans – UdEkoM Balkan
179 Ustanicka St, 11000 Belgrade, Republic of Serbia