IJPAM: Volume 114, No. 1 (2017)

Title

SYNCHRONIZATION AND CHANGES IN VOLATILITIES IN
THE LATIN AMERICAN'S STOCK EXCHANGE MARKETS

Authors

G. Cabrera$^1$, S. Coronado$^2$, O. Rojas$^3$, F. Venegas-Martínez$^4$
$^{1,2}$Departamento de Métodos Cuantitativos
Centro Universitario de
Ciencias Económico Administrativas
Universidad de Guadalajara, MÉXICO
$^3$Escuela de Ciencias Económicas y Empresariales
Universidad Panamericana
Campus Guadalajara, MÉXICO
$^4$Escuela Superior de Economía
Instituto Politécnico Nacional
MÉXICO

Abstract

In this paper we study a possible synchronization in volatility changes for some Latin America's stock exchange indexes. We also add the S&P 500 index to the analysis. We suggest a heterogeneity Markov switching model to capture changes in volatilities over time. To solve the problem of uncertainty in modeling each index, we suggest the Bayes Factor to identify the best Markov switching specification as the number of states, if any. We found that, all the daily growth rates for each index are well characterized by low, medium and high volatilities in different periods of time. We suggest some measures of synchronization based on the concordance by the changes in volatilities between the indexes. We show that, the Mexican, Chilean and the S&P 500 indexes are closer to each other than the rest

History

Received: February 7, 2017
Revised: March 21, 2017
Published: April 21, 2017

AMS Classification, Key Words

AMS Subject Classification: C22, G15
Key Words and Phrases: synchronization, Markov process, financial markets

Download Section

Download paper from here.
You will need Adobe Acrobat reader. For more information and free download of the reader, see the Adobe Acrobat website.

Bibliography

1
M.L. Aiolfi, A.V. Catão, and A. Timmermann
Common factors in Latin America's business cycles, Journal of Development Economics 95 2 (2011), 212-228.

2
G. Bekaert, C.R. Harvey, Emerging markets finance,Journal of Empirical Finance 10 1-2 (2003), 3-55.

3
G. Canarella, S. Pollard, A switching ARCH (SWARCH) model of stock market volatility: some evidence from Latin America, International Review of Economics 54 4 (2007), 445-462.

4
C.K. Carter, R. Kohn, On Gibbs sampling for state space models, Biometrika 81 3 (1994), 541-553.

5
S. Chib, Marginal Likelihood from the Gibbs Output, Journal of the American Statistical Association 90 432 (1995), 1313-1321.

6
R. Cont, Empirical properties of asset returns: stylized facts and statistical issues, Quantitative Finance 1 (2001), 223-236.

7
P.F. Diamandis, Financial liberalization and changes in the dynamic behaviour of emerging market volatility: Evidence from four Latin American equity markets, Research in International Business and Finance 22 3 (2008), 362-377.

8
D.A. Dickey, W.A. Fuller, Likelihood ratio statistics for autoregressive time series with a unit root, Econometrica 49 4 (1981), 1057-1072.

9
G. Dufrénot, V. Mignon, A.Péguin-Feissolle, The effects of the subprime crisis on the Latin American financial markets: An empirical assessment, Economic Modelling 28 5 (2011), 2342-2357.

10
S. Edwards, J.G. Biscarri, F. Pérez de Gracia, Stock market cycles, financial liberalization and volatility, Journal of International Money and Finance 22 7 (2003), 925-955.

11
S. Edwards, R. Susmel, Volatility dependence and contagion in emerging equity markets, Journal of Development Economics 66 2 (2001), 505-532.

12
S. Frühwirt-Schnatter, Finite Mixture and Markov Switching Models by S. FR�HWIRTH-SCHNATTER (First ed.), New York, (2006).

13
S. Frühwirth-Schnatter, Markov Chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models, Journal of the American Statistical Association 96 453 (2001), 194-209.

14
S. Frühwirth-Schnatter, Estimating marginal likelihoods for mixture and markov switching models using bridge sampling techniques, Econometrics Journal 7 1 (2004), 143-167.

15
S. Frühwirth-Schnatter, Finite Mixture and Markov Switching Models (Springer Series in Statistics), (1 ed.) New York: Springer, (2006).

16
L. Gagnon, G.A. Karolyi, Price and volatility transmission across borders, Financial Markets, Institutions and Instruments 15 3 (2006), 107-158.

17
J.D. Hamilton, A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica 57 2 (1989), 357-84.

18
D. Harding, A. Pagan, Macroeconomics and the Real World-Volume 1: Econometric Techniques and Macroeconomics, Chapter Knowing th, Oxford. (2000), 23-42.

19
D. Harding, A. Pagan, Dissecting the cycle: A methodological investigation, Journal of Monetary Economics 49 2 (2002), 365-381.

20
D. Harding, A. Pagan, A comparison of two business cycle dating methods, Journal of Economic Dynamics and Control 27 9 (2003), 1681-1690.

21
C.R. Harvey, Predictable Risk and Returns in Emerging Markets, Review of Financial Studies 8 3 (1995), 773-816.

22
K.S. Im, J. Lee, M.A. Tieslau, Festschrift in Honor of Peter Schmidt, Chapter More powerful unit root tests with non-normal errors, New York, Springer (2014), 315-342.

23
S. Kaufmann, Measuring business cycles with a dynamic markov switching factor model: an assessment using bayesian simulation methods, Econometrics Journal 3 1 (2000), 39-65.

24
C.J. Kim, Dynamic linear models with markov-switching, Journal of Econometrics 60 1-2 (1994), 1-22.

25
C.J. Kim, C.R. Nelson, Business cycle turning points, a new coincident index, and tests of duration dependence based on a dynamic factor model with regime switching, The Review of Economics and Statistics 80 2 (1998), 188-201.

26
D. Kunovac, Asymmetric correlations on the Croatian equity market, Financial theory and practice 35 1 (2011), 1-24.

27
X.l. Meng, W.H. Wong, Simulating ratios of normalizing constants via a simple identity: A theoretical exploration, Statistica Sinica 6 4 (1996), 831-860.

28
S.B. Ramos, J.K. Vermunt, J.G. Dias, When markets fall down: Are emerging markets all the same, International Journal of Finance and Economics 16 4 (2011), 324-338.

29
O. Rojas, C. Trejo-Pech, Nonlinear Time Series and Finance, Chapter Financial Time Series: Stylized Facts for the Mexican Stock Exchange Index Compared to Developed Markets, Mexico: Universidad de Guadalajara (2014), 228-245.

30
N. Shephard, Partial non-gaussian state space, Biometrika 81 1 (1994), 115-131.

31
R. Susmel, Extreme observations and diversification in Latin American emerging equity markets, Journal of International Money and Finance 20 7 (2001), 971-986.

32
M. Zouhair, C. Lanouar, A.N. Ajmi, Contagion versus Interdependence: The Case of the BRIC Countries During the Subprime Crises, Elsevier Inc, (2013).

How to Cite?

DOI: 10.12732/ijpam.v114i1.10 How to cite this paper?

Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2017
Volume: 114
Issue: 1
Pages: 113 - 132


Google Scholar; DOI (International DOI Foundation); WorldCAT.

CC BY This work is licensed under the Creative Commons Attribution International License (CC BY).