Dynamic Linkages between Stock Market and Exchange Rate in mila Countries: A Markov Regime Switching Approach (2003-2016)

Abstract

This paper aims to analyse the dynamic relationship between the stock market returns and exchange rates movements for the mila (Mercado Integrado Latinoamericano) countries: Colombia, Chile, México and Peru, over the period 01:2003 to 09:2016. Univariate (Markov Switching-Autoregressive) and multivariate (Markov Switching-Vector Autoregressive) regime-switching models approach are used. The univariate analysis offers evidence indicating that stock returns of the mila countries evolve according to two different regimes: a low volatility regime and a high volatility regime. The Markov Switching Vector Autoregressive models point out that stock markets have more influence on exchange rate than exchange rate has on stock markets. Results for the Peruvian and Chilean markets contribute evidence about contagion between the stock and the exchange rate markets. * Profesora, Facultad de Economía. unam.

A Two-Regime Markov-Switching GARCH Active Trading Algorithm for Coffee, Cocoa, and Sugar Futures

“…) in this number of iteration or step (i), the analyst returns to the first stage in the estimation algorithm, as this set is the new prior. Then, she updates the filtered probabilities, Equation (6) or Equation (7), with the new parameter set, (θ i ), calculates the LLF i with Equation (8), and updates, with Equations ( 9) to (11), the parameter set with the new filtered probabilities. This numerical method continues until the LLF i values between the current iteration (i) and the previous one (i − 1) have a difference lower than a δ threshold value…”

“…Other papers test the spillover effect between stock and currency markets of developed and developing countries. Examples of these are the works of Mouratidis et al [43], Miles and Vijverberg [44], Lopes and Nunes [45], Kanas [46], Álvarez-Plata and Schrooten [47], Parikakis and Merika [48], Girdzijauskas [49], Dubinskas and Stungurienė [50], Kutty [51], Ahmed et al [52], and Sosa, Ortiz, and Cabello [11].…”

“…The use of Markov-switching (MS) models [1][2][3] has spread to several applications such as the forecast of recessions [1,4,5] or distress periods in financial markets [6][7][8][9][10][11][12]. Their basic rationale is that the performance of a time series, such as the one of stock indexes or commodities, can be modelled with a stochastic process that has a k number of regimes.…”

A Test of Using Markov-Switching GARCH Models in Oil and Natural Gas Trading

“…By using the model in the U.S., the U.K., Brazil, and South Korea, they found that their model was appropriate to model the volatility clustering effect, due to the time-varying properties of the correlation among markets, but also given their tested regime-switching framework. With respect to emerging stock markets, we mention the works of Cabrera et al [47] and Sosa, Ortiz and Cabello [48] who tested the use of either MS or MSGARCH models in Latin American stock markets. Their results were in agreement in that it was appropriate to use either two regime MS models [48] or three regime MSGARCH models [47] in order to characterize the performance of these markets.…”

“…With respect to emerging stock markets, we mention the works of Cabrera et al [47] and Sosa, Ortiz and Cabello [48] who tested the use of either MS or MSGARCH models in Latin American stock markets. Their results were in agreement in that it was appropriate to use either two regime MS models [48] or three regime MSGARCH models [47] in order to characterize the performance of these markets. In addition, they suggested that these models could be useful to measure the spillover effect and the potential presence of a "Latin American stock market common cycle".…”