Nonlinear Behavior of Latin American Stock Markets: The Economic and Political Events Explanation
Rafael Romero-Meza Business School Adolfo Ibanez University Av. Diagonal Las Torres 2640 Santiago de Chile, Chile
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Claudio A. Bonilla (corresponding author) Faculty of Economics and Business Universidad del Desarrollo Av. La Plaza 700, Las Condes Santiago de Chile, Chile Phone: (56 2) 2999372 Fax: (56 2) 299 9241
[email protected]
Joaquin Santibañez Faculty of Economics and Business University of Chile Diagonal Paraguay 265 Santiago de Chile, Chile
[email protected]
Nonlinear Behavior of Latin American Stock Markets: The Economic and Political Events Explanation
Abstract
This study examines economic and political events that could explain episodes of nonlinearity detected in major Latin American stock markets. The methodology employed is that of a reverse event study. After applying a bicorrelation test in combination with a windowed test procedure as developed by Hinich (1996) and Hinich and Patterson (2005) to detect non-linear episodes, we investigate the causes of this behavior. We find that a series of political and economic events are associated with non-linear periods in Latin America, and that no single event leads to contemporaneous non-linearities in all of the region’s markets.
JEL Classification: C12, G14 Key words: Latin American stock market, episodic nonlinearity, Hinich portmanteau bicorrelation test, event detection
1. Introduction
Ever since the groundbreaking work of Hinich and Patterson (1985) there has been growing evidence that stock market returns experience episodes of non-linear behavior. Other studies have reported non-linearity in the American market (Hinich and Patterson, 1985; Scheinkman and LeBaron, 1989; Hsieh, 1991; Brock et al., 1992; Hsieh, 1995; Kohers et al., 1997; Patterson and Ashley, 2000; Skaradzinski, 2003), in European markets (Panunzi and Ricci, 1993; Abhyankar et al., 1995; Brooks, 1996; Afonso and Teixeira, 1998; Opong et al., 1999; Brooks and Hinich, 2001; Kosfeld and Robé, 2001; Escot et al., 2002), in Asian markets (Ahmed et al., 1999; Ammermann and Patterson, 2003; Lim et al., 2003; Lim and Hinich, 2005a), and also in Latin American markets (Bonilla et al., 2006).
Despite this ample empirical evidence for non-linear behavior in financial markets, little is yet known about the underlying causes.1 In this paper we will investigate various factors that might account for episodes of non-linearity in the markets of Latin America (hereafter also LA or “the region”). The method we use is a reverse form of event study in the spirit of Brooks et al. (2000), Lim and Hinich (2005b) and Romero-Meza et al. (2007). We begin by applying a bicorrelation test in combination with a windowed test procedure as developed in Hinich (1996) and Hinich and Patterson (2005). We then investigate the main political and economic events that could explain the non-linear behavior.
1
Some explanations have been proposed by Antoniou et al., (1997) and Sarantis (2001).
Interest in Latin American capital markets has developed considerably due to a series of economic crises that have struck the region over the last fifteen years,2 including the Mexican crisis (1982), the tequila effect (1994), the Asian crisis (1997), the Russian crisis (1998), the Brazilian crisis (1999) and the Nasdaq crash (2000). The importance of these markets stems from their role as the motor of growth in the region, particularly in the nineties (Taylor, 2003).
Given the volatility of Latin American markets, detected episodes of non-linearity may be the result of market adjustments as it is highly likely that financial asset prices are affected by events of a political, social and economic nature. Furthermore, a series of studies3 have revealed the existence of relationships between the region’s markets and other markets such as those of the U.S. and Asia. We would therefore expect to find that LA stock indices exhibit similar periods of non-linearity linked to some common event that had a contemporaneous effect on all of them.
A number of recent works by Brooks et al. (2000), Skaradzinski (2003), Lim and Hinich (2005b) and Romero-Meza et al. (2007) have applied the same method employed here.4 Brooks et al. (2000) studied the exchange rates of ten countries relative to the pound sterling, discovering a non-linear period that was similar for all series and ascribable to a change in the accounting rules for foreign transactions adopted by American companies. Skaradzinski (2003) analyzed 60 NYSE stocks for odd years between 1993 and 2001, and found that the non-linear
2
See Forbes and Rigobon (2000) See Fujii, 2005; Climent and Meneu, 2003; Fernández-Serrano and Sosvilla-Rivero, 2003; Johnson and Soenen, 2003; Gong-Men et al., 2002; Edwards and Susmel, 2001; and Pagan and Soydemir, 2000 and 2001. 4 Aggarwal et al. (1999) use a different methodology that nevertheless employs the same reverse event concept. They examine whether the volatility of the ten most important emerging markets in Asia and Latin America is associated with political, economic and social events. Their main results are that (a) the high volatility of these markets is marked by sudden changes in variance, and (b) periods of high volatility are associated with important events at the local rather than the international level. 3
periods most commonly replicated were those associated with a series of economic news items appearing in The Wall Street Journal. Finally, the stock market studies by Lim and Hinich (2005b) for Malaysia and Romero-Meza et al. (2007) for Chile identified various political and economic events that could explain periods of non-linearity.
Our results partly confirm our hypothesis. On the one hand, we find that non-linear episodes in Latin America are related to a series of political and economic events, but on the other hand, the evidence is not sufficient to infer the existence of a particular event that leads to a similar non-linearity in all of the stock indices studied. The only exception is the Asian crisis in the second half of 1997, which appears to have affected four of the seven markets examined in systematic fashion.
The remainder of this paper is organized as follows. Section 2 outlines the methodology employed, Section 3 provides a statistical description of the data, Section 4 presents the results together with explanations for the non-linearities encountered, and finally, Section 5 offers a number of conclusions.
2. Methodology In this section we briefly review the windowed test procedure and the bicorrelation test developed by Hinich (1996).5 Let sequence {x(t )} denote the sample data process in which the time unit t is an integer. The test procedure uses non-overlapping windows such that if n is window length, then the kth window is
5
{x(t k ), x(t k + 1),..., x(t k + n − 1)} .
The mathematical derivation is given in Hinich (1996) and Hinich and Patterson (2005).
The next non-
overlapping window, k+1, is thus {x(t k +1 ), x(t k +1 + 1),..., x(t k +1 + n − 1)}. The null hypothesis for each window is that the x(t ) are occurrences of a white noise stationary process whose bicorrelation is 0. The alternative hypothesis, on the other hand, is that the generator process in each window is random, with some non-zero correlations Cxxx(r , s ) = E [x(t ) x(t + r ) x(t + s )] on the set 0 < r < s < L , where L is the number of lags defining the window. The H test statistic and its distribution are given by H =
L
s −1
s=2
r =1
G 2 ( r , s ) ≈ χ 2 ( L −1)( L / 2 )
1
where G ( r , s ) = ( n − s ) 2 C zzz ( r , s ) and C zzz ( r , s ) = ( n − s ) −1
n−s
Z (t ) Z (t + r ) Z (t + s ) for 0 ≤ r ≤ s .
t =1
The Z (t ) are standardized observations obtained by subtracting the window’s sample mean and dividing by its standard deviation. The number of lags L is specified as L = nb on the interval 0 < b < 0.5 , where b is a parameter to be chosen by the user. On the basis of Monte Carlo simulations, Hinich and Patterson (2005) recommend that b = 0.5 in order to maximize the power of the test while also ensuring a valid approximation in terms of asymptotic theory. A window is significant if the H statistics reject the null hypothesis of white noise at the specified confidence level.
3. Data description and analysis The data consist of daily closing prices from seven Latin American stock indices. For six of the seven – BOVESPA (Brazil), MERVAL (Argentina), IPC (Mexico), IGPA (Chile), IGBC
(Colombia) and IGBVL (Peru) – the information was obtained from Economatica, while for IBC (Venezuela) the source was ISI Emerging Markets.
Table 1 presents the total number of data items and the period studied for each index.
Table 1: Index by period studied and number of data items. Index BOVESPA MERVAL IPC IGPA IGBC IGBVL IBC
Start date 04/1993 10/1996 11/1991 01/1990 01/1991 01/1986 11/1990
End date 10/2004 10/2004 10/2004 09/2002 10/2004 10/2004 01/2006
Data items 2,839 1,977 3,218 3,175 3,137 4,511 2,903
The prices are converted into daily returns by means of the equation rt = ln ( pt / pt −1 ) , where rt
is the return on a given stock in period t, and pt is the closing price in period t.
Table 2 summarizes the principal descriptive statistics for each stock index.
Table 2: Descriptive statistics for Latin American stock indices. Mean St. Dev. Skewness Kurtosis JB LM
BOVESPA 0.002409 0.027750 0.52 11.52 87178.7 123.5
MERVAL 0.000365 0.024474 -0.13 7.91 1996.4 126.01
IPC 0.000637 0.016986 -0.004 8.27 3735.3 206.6
IGPA 0.000572 0.008311 0.24 6.25 1435.5 448.2
IGBC 0.001107 0.012366 1.07 12.69 12884.09 60.4
IGVBL 0.003374 0.017912 1.06 8.49 6526.015 1369.944
IBC 0.001063 0.019157 0.83 15.19 18326.74 529.6
The data in Table 2 display clear signs of non-normality. All of the indices except MERVAL and IPC show a positive skewness coefficient, meaning that returns are more likely to be above the mean than below it. As regards the shape of the tails, the indices all exhibit kurtosis values
greater than 3, which indicates that the distributions are leptokurtic and therefore more peaked than a normal distribution. The results of the JB test, meanwhile, confirm that the returns are not generated by normal distributions. Finally, we performed the LM test6 developed by Engle (1982) which is designed to detect the presence of autoregressive conditional heteroskedasticity (ARCH). The null hypothesis was rejected for all of the series, indicating that every Latin American series displays nonlinearities. To corroborate this result we also carried out a BDS test (Brock et al., 1996), which can be used on series with either type of dependency (linear or non-linear). This test was applied to the residuals of an adjusted AR(p) model, the results confirming the existence of non-linearities in the LA series. To gather information on the major economic and political events that might explain these nonlinearities, recourse was had to the Public National Library of Chile.
4. Results Once the linear dependencies in the data were eliminated through the application of an AR(p) model to the original series, the Hinich bicorrelation test was utilized to check for non-linear episodes. This was done to ensure that the rejection of the white noise null hypothesis was due exclusively to non-linear dependencies. To carry out the test we divided up the sample into a set of non-overlapping windows each of which contained 25 observations. The length of the window must be large enough for the test to be valid yet short enough that the data-generating process is not affected by this division.
6
The same as TR2 (number of observations multiplied by the coefficient of determination of the last regression). It has a chi-square distribution with p degrees of freedom on the null hypothesis of “no ARCH effects”.
The results of the bicorrelation test on the adjusted AR(p) model residuals for each Latin American series are summarized in Table 3. The dates for the periods in which non-linearities appear are given in Table 4. The Appendix contains the political and economic events that occurred during periods of non-linearity for each LA stock markets. These findings are consistent with those reported in the previous section. The stock returns exhibit non-linearities in a manner that is not stable over time, and thus behave much of the time like a white noise process. Though the non-linearities appear only on occasion and are of short duration, they are of such significance that the LM and BDS tests reject the independence hypothesis for the entire sample. Similar results are found in Bonilla et al (2006).7
Table 3: Results of bicorrelation test for Latin American stock indices. BOVESPA MERVAL AR(p) Total number of windows Non-linear windows
IPC
IGPA
IGBC
IGBVL
IBC
AR(1)
AR(2)
AR(0)
AR(0)
AR(1)
AR(1)
AR(1)
113
79
128
127
125
180
116
5 (4.35%)
2 (2.53%)
1 15 1 (0.78%) (11.81%) (0.8%)
4 5 (2.22%) (4,31%)
We now consider a series of events that may have played an important role in the appearance of non-linear episodes (see Appendix). For our purposes, events will be assumed to be classifiable as (1) domestic events, (2) world events occurring outside of Latin America, and (3) events in Latin American countries that spread to others in the region. With the exception of Argentina and certain periods for Venezuela, all non-linear stock index episodes are marked by at least one domestic event that could be the underlying cause. Episodes in Brazil, Chile, Peru and Venezuela are associated with political and economic
7
GARCH models assume that the series-generating process is stationary. For more on the stationarity of nonlinearities, see Lim et al. (2005) and Romero-Meza et al. (2006b).
events, while for Mexico and Columbia the events are strictly economic. The foregoing leads us to suspect that domestic economic events play the most important role in explaining the existence of non-linear behavior in stock markets. Among these events we may mention changes in central bank monetary policy, privatization processes, changes in economic regulation and changes in the prices of commodities exported by certain LA countries.
At the world level, there is a string of events that could explain in large measure the appearance of non-linear episodes now that Latin American markets are widely integrated with the rest of the world due to the reforms of the nineties that liberalized the region’s product and financial markets. Argentina is an extreme case in the sense that its periods of non-linearity are related solely to international happenings. The event most commonly manifested in the various indices is the Asian crisis and its effects during the second half of 1997. Recall that in the wake of Thailand’s devaluation in July 1977, capital abandoned emerging markets, and particularly those of Latin America. Other important events include Iraq’s invasion of Kuwait in 1990, unexpected movements on U.S. stock exchanges, the Barings Bank scandal, the Kosovo Conflict, the 9/11 attacks, and the Madrid train bombing.
Upon analyzing whether a given event occurring in a Latin American country affects other stock markets in the region, we find that presidential elections appear to have a significant impact on market agent behavior. The Mexican elections for president coincide with non-linear periods in Brazil and Peru, while the Argentinian presidential contest is contemporaneous with such periods in Chile and Peru. Given that Brazil and Argentina are Latin America’s largest economies, the end of the Petrobras oil monopoly and Argentina’s 2001 crisis may be related to the non-linearities in the LA countries.
Table 4: Non-linear periods. Index / Year
87
90
92
BVSP (Brazil)
93
94
95
97
98
99
20/06/97 25/07/97
17/09/93 22/10/93
MERVAL (Argentina)
2000
2001
29/06/00 12/08/00
03/07/01 08/08/01
2002
20/02/04 29/03/04
24/06/97 29/07/97 04/09/97 08/10/97
IPC (Mexico)
28/05/92 02/07/92
IGPA (Chile)
19/04/90 25/05/90
14/08/92 21/09/92
26/10/93 30/11/93
08/08/90 13/09/90
IGBC (Colombia) IGBVL (Venezuela) IBC (Peru)
10/08/94 14/09/94
08/02/95 14/03/95
08/07/97 11/08/97
20/04/95 25/05/95
23/03/99 27/04/99
16/02/01 22/03/01
27/09/99 26/10/99
20/08/01 26/09/01
27/10/99 01/12/99
27/09/01 02/11/01
27/10/99 01/12/99
27/09/01 02/11/01
08/03/93 16/04/93 13/11/87 21/12/87
06/04/95 17/05/95 28/09/95 03/11/95
04/11/97 10/12/97
14/06/00 0/07/00 11/03/98 17/04/98 27/05/98 03/07/98 25/11/98 31/12/98
14/07/99 17/08/99
2004
10/12/01 16/01/02
A quick review of Table 4 confirms that no single non-linear period appears in every one of the Latin American series. The Asian crisis is the only event that appears to have systematically affected agents in the majority of Latin American markets, as evidenced by the non-linearities in the stock return indices in the second half of 1997 for Brazil, Argentina, Chile and Venezuela. Two possible explanations for the preceding results come to mind. The first is that the majority of Latin American markets are not efficient,8 and prices therefore do not adjust rapidly to reflect new information. Certain markets such as Chile that do respond immediately (non-linear) to a given event are the relatively efficient ones, and therefore exhibit more non-linear periods. The second potential explanation it that it is not clear whether or not a contagion effect among Latin America countries actually exists. For example, Verma and Ozuna (2005) show that LA stock markets do not react to changes in certain macroeconomic variables occurring in other countries of the region. Furthermore, Bailey and Chung (1995), Bekaert and Harvey (1997), Susmel (1998), and Aggarwal et al. (1999) all find that world events explain only a small part of emerging market movements, particularly those of Latin America. In a similar vein, Aggarwal et al. (1999), in their study of the volatility of Asian and Latin American markets, found that the 1987 stock market crash was the only event that seemed to influence the volatility of a majority of the markets.
8
Bekaert and Harvey (1995) assert that returns on assets in emerging markets are predictable. Worthington and Higgs (2003), in their study of certain Latin American markets, conclude that none of them satisfy the hypothesis of weak-form market efficiency.
5. Conclusions In this study, LM and BDS tests were used together with the bicorrelation test developed by Hinich (1996) to investigate economic and political events that might have been responsible for non-linear episodes detected in the stock returns indices of seven Latin American countries. A reverse event procedure was employed in the spirit of Brooks et al. (2000), Lim and Hinich (2005b) and Romero-Meza et al. (2007). Our research found that all Latin American markets display non-linear episodes but that the phenomenon is not stable over time, the appearance of significant windows tending to be sporadic and brief. We have attempted to shed some light on the factors that may cause non-linearities in Latin American economies, and have pointed up a series of events of a political and economic nature that are associated with these episodes. Such events include changes in central bank monetary policies, privatization processes and changes in commodity export prices in certain countries of the region. Events occurring outside Latin America also played a role in the appearance of non-linearities, the Barings bank debacle, the Kosovo conflict and the 9/11 attacks all being specific examples.
A particularly noteworthy result of our research is that no single event led to simultaneous non-linear behavior in all markets, although the Asian crisis does seem to have systematically affected the majority of them.
An interesting line of future research would be to extend this analysis to individual actions in Latin American markets.
Appendix Political and economic events that occurred during periods of non-linearity Brazil 17/09/93 – 22/10/93
Suspension of tax on checks approved. Federal Supreme Court declares that a capital tax surcharge collected by 21 of the country’s 26 state governments since 1981 is illegal.
20/06/97 – 25/07/97
Second-biggest point drop in the history of the Dow Jones average. Asian crisis effects.
29/06/00 – 12/08/00
OPEC agrees to increase crude oil production. Vicente Fox is elected president of Mexico, ending 41 years of PRI government. Unprecedented privatization process is launched with the sale of 16.6% of Petrobras.
03/07/01 – 08/08/01
World markets on alert due to financial weakness of Argentina.
20/02/04 – 29/03/04
Bomb attacks in Madrid. Jose Luis Rodriguez Zapatero is elected president of Spain. Market surprised by central bank’s lowering of reference interest rate.
Argentina 24/06/97 – 29/07/97
Second-biggest point drop in the history of the Dow Jones average. Asian crisis effects.
04/09/97 – 08/10/97
Tension in Persian Gulf causes market reaction. Asian crisis effects.
México 28/05/92 – 02/07/92
Mexico buys back 9% of its external debt. Surprise announcement of new Mexican currency.
Chile 19/04/90 – 25/05/90
New currency exchange rules go into operation.
Change in direct foreign investment policy. 08/08/90 – 13/09/90
Kuwait is attacked by Iraq. Price of oil rises above US$30 a barrel.
14/08/92 – 21/09/92
Central bank raises interest rate. Reserve requirements increased, restrictions on capital remittances lifted and private pension funds authorized to invest abroad.
26/10/93 – 30/11/93
Price of copper reaches six-year high.
10/08/94 – 14/09/94
Foreign exchange transaction restrictions reduced. Fast-track procedure for Chile-U.S. free trade agreement rejected.
08/02/95 – 14/03/95
Barings Bank scandal: Asian markets provoke fall in markets around the world.
20/04/95 – 25/05/95
New rules for private pension fund investments abroad. Carlos Menem reelected president of Argentina.
08/07/97 – 11/08/97
Effects of Asian crisis.
23/03/99 – 27/04/99
NATO launches military action in Yugoslavia due to Kosovo conflict.
27/09/99 – 26/10/99
Concern over bubble in American market.
27/10/99 – 01/12/99
Oil price reaches highest level in 9 years. Iraq announces suspension of petroleum exports.
16/02/01 – 22/03/01
U.S. attacks Iraq.
20/08/01 – 26/09/01
9/11 attacks in the U.S.
27/09/01 – 02/11/01
Afghanistan attacked by the U. S. New capital market legislation announced.
10/12/02 – 16/01/02
Federal Reserve reduces interest rates to lowest level in 40 years. President De La Rua of Argentina resigns.
Colombia 08/03/93 – 06/04/93
Andean Group (Grupo Andino) approves common external tariff. World Bank announces US$250 million for agricultural sector. End of voluntary restrictions on metals exports between Colombia and Venezuela.
Peru 13/11/87 – 21/12/87
Prices rise almost 20% in wake of 50% devaluation.
06/04/95 – 17/05/95
Alberto Fujimori is reelected president of Peru. New wave of privatizations launched. Sale of Banco Continental de Perú. Menem reelected president of Argentina.
04/11/97 – 10/12/97
Law regulating monopoly formation in electricity sector approved. Effects of Asian crisis.
14/06/00 – 20/07/00
OPEC agrees to increase crude oil production. Vicente Fox elected president of Mexico, ending 41 years of PRI government.
Venezuela 28/09/95 – 11/03/95 11/03/98 – 17/04/98
Oil price reaches highest level in 9 years. OPEC approves record cuts in crude oil production.
27/05/98 – 03/07/98
Korea and Japan rattle stock markets. Oil prices at lowest level in 12 years ($US13.27 a barrel) OPEC approves cuts in crude oil production. Brazil puts an end to 45 years of Petrobras monopoly.
25/11/98 – 31/12/98
Hugo Chavez elected president of Venezuela. U.S. and Britain attack Iraq after the latter impedes work of arms inspectors. Oil price falls ($US9.41) in wake of suspension of military action. U.S. renews attacks on Iraq.
14/07/99 – 17/08/99
Decline of interest rates and increase in rate on bank reserve requirements. Oil price reaches highest level in 2 years.
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