Ebook Volatility Contagion and East Asian Equity Markets: A Markov-Switching SWARCH Analysis
During the last two decades a new concept has had a huge influence on economic thinking, namely contagion. Contagion represents a new field of economic study and has attracted the attention of many economists, econometricians and policy makersaround the globe. The Mexican debt crisis in 1982, the 1987 stock market crash, the “tequila effect” in 1994 originating in Mexico, the “Asian Flu” starting in 1997, thereafter the “Russian Cold” in 1998 where the Russian Ruble was devalued and Russia defaulted on parts of its foreign debt, the “Brazilian Fever” in 1999 accompanied by a steep depreciation of the Brazilian Real, the NASDAQ rash of 2000 and the Argentina crisis in 2001/2002 are the best known and most important financial crises in the last two decades.
Several authors have argued that a highly unstable international financial system, caused by excessive capital mobility, lies at the heart of the problem of crises spreading across countries. One specific proposal formulated by Edwards (1999) is to impose a Tobin tax on foreign exchange transactions and to apply capital controls on capital inflows in order to slow down international flows of capital.
Figure 1 in appendix A shows the stock market indices of the countries Hong Kong, Malaysia, Thailand and Singapore in terms of US-Dollars. This graph indicates that during periods of financial turmoil stock returns seem to show an increased volatility and to move together across countries. Therefore, crises have appeared to bunch together, so that they often appear to originate in one country and then spread over to other previously unaffected countries. According to Rigobon (1999) these affected countries are either locally close to the “ground-zero countries”, economically related through trade and/or financial links, similar in their structure of the economies etc., or have been virtually distinct and locally apart from those. Many theories emerged trying to explain the phenomena of these apparently very different sources and causes of those “contagious” crises in the world swashing sometimes from country to country around the world.
Refer for example Obstfeld (1996), among others, who developed a full-fledged model introducing expectations which would make jumps across model-equilibria possible. Here, the idea is that even if countries’ economical fundamentals are not to be expected to cause a crisis by themselves, a change in expectations about this particular country, caused by any international event, would make a crisis feasible. So, self-fulfilling expectations could cause international spreading of financial turmoil. These experiences of crisis spreading like illnesses or epidemics inspired economist to create a new term for these economic phenomena, namely “contagion”.
In this paper, the author uses data from a group of East Asian countries to explore more closely the development of these countries’ stock markets returns and volatilities. An investigation takes place as to whether periods of increased stock market volatility coincide with the main international financial crises within the sample period. Creating more insights into these economic phenomena would be highly valuable and could have important implications for policy and investment decisions. Any evidence for a possible transmission of crises across countries borders would favour arguments to reduce short-term bi- or multilateral financial capital flows by capital controls or other means.
The author tackles these issues, departing from other work in this area done by Edwards and Susmel (2001), by conducting first a univariate analysis of the individual stock market indexes by using a variant of the SWARCH model developed by Hamilton (1989) and Hamilton and Susmel (1994). This methodology makes it possible to identify breakpoints in an ARCH model of the conditional variance process. Thus, the sample period can be split into phases with different stock market return volatilities and thereby identify periods with an unusually high conditional variance suggesting market uncertainty and/or financial crisis. Evidence in the data is found for volatility changes through time and across countries. In a second step the author examines more closely whether there tend to be co-movements in volatility, and if so how strong they are, by utilizing different indicators of (de-) synchronization proposed by Beine, Candelon and Sekkat (2003). It is found that these periods of high volatility tend to almost coincide across most of the countries in my sample. So, taking these statements into account the question arises whether there has been spill-over of financial crises among countries and whether it can be demonstrated that this volatility spill-over exists.
This approach is in line with other studies analysing the effects of financial crises “on assets” volatilities across countries. Examples of papers on this subject include Bennett and Kelleher (1988), King and Wadhwani (1990), Engle, Ito, and Lin (1990, 1992) and Hamano, Ng, and Masulis (1990). Other papers dealing with possible spill-over of financial markets’ volatility are Edward and Susmel (2000, 2001) investigating interest rate volatilities and stock market returns in emerging markets respectively.
This thesis is organized as follows. Section I is the introduction. Section II focuses on the concept of contagion and different point of views and definitions of it. Further, different possible transmission channels across countries for financial crises are presented and there is an overview of the most recent existing empirical literature analysing contagion. In Section III the statistical methodology utilized along with indicators of (de-) synchronization are presented and explained. Section IV reports the results obtained and Section V concludes the paper.
Contents
I. Introduction
II. Contagion – Concept, Transmission and Empirical Evidence
II.1 Concept of Contagion
II.2 Transmission Channels
II.3 Empirical Evidence for Contagion
II.4 Contagion in Mean and in Volatility
II.5 Summary of Section II
III. Methodology
III.1 Estimation Procedure
III.1.1 General
III.1.2 Construction of the SWARCH Model
III.2 Indicators of (De-) Synchronization
III.3 Monte Carlo Simulation
IV. Empirical Results and Discussion Part
IV.1 Data description
IV.2 Preliminary Data Analysis
IV.3 Stock Market Volatility and Breakpoints
- IV.3.1 General
IV.3.2 Country-by-Country Analysis
IV.4 Indicators of (de-)synchronization
IV.5 Discussion of the Results
V. Conclusion
Reference List
Appendix A
Appendix B
Appendix C
Appendix D
Appendix E
Appendix F:
Appendix G
Appendix H
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