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Interdependence between USA, Western European and CEE Stock Markets

THE ACADEMY OF ECONOMIC STUDIES BUCHAREST THE FACULTY OF FINANCE, INSURANCE, BANKING AND STOCK EXCHANGE DOFIN - DOCTORAL SCHOOL OF FINANCE AND BANKING. Interdependence between USA, Western European and CEE Stock Markets. MSc Student: Elena-Manuela Tocilă

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Interdependence between USA, Western European and CEE Stock Markets

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  1. THE ACADEMY OF ECONOMIC STUDIES BUCHAREST THE FACULTY OF FINANCE, INSURANCE, BANKING AND STOCK EXCHANGE DOFIN - DOCTORAL SCHOOL OF FINANCE AND BANKING Interdependence between USA, Western European and CEE Stock Markets MSc Student: Elena-Manuela Tocilă Supervisor: PhD. Professor Moisă Altăr Bucharest, July 2010

  2. Dissertation paper outline • Importance of studying interdependence • Literature Review • Aims of the Paper • Data • Methodology and Results • Conclusions • References

  3. Importance of studying interdependence • Examining interdependence during crises is an important step in understanding market efficiency and information flows. • Investigating interrelationships among international stock markets provide useful information for portfolio managers: tight market linkages that appear during turmoil periods limit the international portfolio diversification benefits and should be taken into consideration when deciding how to form portfolios.

  4. Literature Review • Studies about the linkages between CEE and developed countries: • Syrioupoulus (2004) finds that CEE markets tend to display stronger long-run linkages with the mature markets than with their neighbours. • Serwa and Bohl (2005) analyze changes in interdependence for the CEE countries and finds that CEE markets are not more prone to contagion than more developed stock markets. • Egert and Kocenda (2007) find that there are no long-run links between Western and Eastern stock markets but they conclude that there are signs of spillover effects (both in terms of returns and volatility) among CEE markets, among Western markets and from Western to CEE markets. However, no spillover seems to occur from East to West markets.

  5. Literature Review • Studies regarding interrelationships between stock markets during crises: • Forbes and Rigobon (1999) examine the stock-market co-movements during the following periods: the 1997 East Asian crisis, the 1994 Mexican peso collapse and the 1987 US stock market crash; they find that during the three crises there was no contagion, only interdependence between the markets that “generated” the crises and those from East Asia, Latin America, OECD. • Gklezakou and Mylonakis (2009) depicted that South European markets that are loosely related in periods of normal economic activity, exhibit strong interrelationships under conditions of the current economic recession. They also found that the USA market continued to exert dominant influence to the other stock markets. • Chung et al. (2010) present the impact of 2007-2009 global financial crisis on the interdependence between US market with respect to UK, Hong Kong, Japan, Australia, Russia and China markets. Their conclusion is that the interdependence among global stock markets become stronger during the crisis.

  6. Aims of the Paper • This paper aims at contributing to the analysis of the linkages between international stock markets during the current financial crisis through the following aspects: • to determine the extent in which the subprime crisis influences the developed and the emerging countries of Europe; • to find out how interdependence between equity markets could change during crisis.

  7. Data • We use the following markets in our analysis: - US market: S&P 500 - three Western European markets: FTSE (United Kingdom), DAX (Germany) and CAC (France) - five CEE markets: WIG 20 (Poland), PX (Czech Republic), BUX (Hungary), SOFIX (Bulgaria) and BET10 (Romania). • Data used: weekly indices in logarithm, weekly indices transformed into continuously compounded returns and the volatilities for each of the series (determined using GARCH models). Ri,t = log(Pi,t-1/Pi,t), where Pi,t represents the index value at time t • The two analyzed time intervals are: October 2004 – June 2007(142 weeks) and July 2007- March 2010 (142 weeks). • The estimations and tests were performed in EViews 6.

  8. Methodology and results 1. Evidence for the crisis period Summary statistics of the returns before and during the crisis • Almost all market indices returns have dropped significantly since July 2007, as their average weekly returns turned into negative returns during the crisis; • The volatilities during the second period are higher than those characterizing the stability period; • SOFIX (Bulgaria) returns experienced the largest decline, while FTSE (UK) experienced the least.

  9. Methodology and results 1. Evidence for the crisis period Pairwise correlations between S&P and other market indices before and during the crisis • Using the Fisher r-to-z transformation (procedure developed by R. A. Fisher in 1921), we calculate a value of z that can be applied to assess the significance of the difference between two correlation coefficients: • During the financial crisis all correlation coefficients are significantly higher comparing to those for the previous period.

  10. Methodology and results 2. Testing for contagion Pairwise correlations between S&P and other market indices before the crisis and during the entire period considered • Comparing the correlation coefficients during the crisis with those calculated for the entire period, we find that there is no significant difference between them (z-test). According to Kristin Forbes and Roberto Rigobon (1999), this fact suggests that there is no contagion between the markets; there is only a continuation of the strong cross-market linkages (interdependence).

  11. Methodology and results 3. Testing for Stationarity • Unit Root tests used: Augmented Dickey Fuller (ADF) and Phillips Perron (PP); • Stationarity test: Kwiatkowski-Phillips-Schmidt-Shin (KPSS) • All series of indices considered in logartihm are non stationary and integrated of order 1 (the first difference is stationary); • For the series obtained from GARCH models (variances) we calculate the standard deviations and apply the unit root tests. We find that all volatilities series are stationary.

  12. Methodology and results 4. VAR models VAR model (returns to returns) between S&P500 and developed countries of Western Europe • Returns on the English and French markets are significantly influenced by developments on the American market during the crisis, a fact which cannot be validated for the period before the crisis; • The significant relationship between American and German returns before the crisis is not maintained for the other period, a fact which can be explained by the good economic results of the German economy that offered the needed stability for the local stock market. This stability decoupled the DAX index from the high decreases of the American market.

  13. Methodology and results 4. VAR models VAR model (volatility to volatility) between S&P500 and developed countries of Western Europe • During the crisis, the coefficients between S&P and the volatilities on the European developed stock markets become significant. • The trend is valid even for Germany if we consider the interpretation of the investors’ behavior during a crisis period: they will take rushed decisions, without any fundamental analysis; all financial decisions will be based on “intuition”, alarming news and other fellow investors’ reactions to these. This type of behavior determines a high volatility on any market, irrespective of the listed companies’ economic status and prospects.

  14. Methodology and results 4. VAR models VAR models (returns to returns) between each developed market and the group of five countries of Central and Eastern Europe • The close relationship between emergent markets and USA (before and during the crisis) can be explained by observing investors’ behavior: when all markets were going up (S&P500 is seen like a “benchmark”), they invested in emerging markets; then, when the crisis started in USA in July 2007, the first thing they did was to withdraw their funds from developing countries, the most liable to confront with economical problems. • European developed markets – UK, Germany and France – seem to have a close connection with Hungary in both time intervals, which we interpret as a proof that the Hungarian market has the tightest relationship with the leading markets on our continent, as opposed to the rest of the emerging economies from CEE.

  15. Methodology and results 4. VAR models VAR models (volatilities to volatilities) between each developed market and the group of five countries of Central and Eastern Europe • The German market has a small influence on the developing markets, considering the non-significant coefficients from the estimate; there is an apparent connection between the Polish market and the German composite index before the crisis; • For S&P, as opposed to the period before the crisis, the coefficients become significant during the turmoil, showing the existence on an influence for the cases of Hungary and Poland; the relation with the Czech market remains significant in both intervals; • There is no major influence from the part of FTSE on the developing markets during the crisis, with the exception of the Hungarian one; before the crisis, coefficients are significant in relation with BET, PX and WIG. • A high volatility of the French index determines a significant change in the evolution of the Hungarian and the Polish markets before the crisis.

  16. Methodology and results 4. VAR models VAR models with two variables (returns to returns) between S&P and the other indices • The impact of SP returns on FTSE and CAC (marked with red in the table) returns is positive and significantly greater during the crisis, suggesting an increasing spillover effect from US market to UK and France markets. • Almost all coefficients for emerging markets are statistically different from zero (before and during crisis) but they are not significantly different in the first time interval compared to the second one. We conclude that the close relations between S&P and developing markets are maintained during the crisis. • Interestingly, in the case of Hungary, the second lag of S&P has a significant positive influence during the crisis, which shows that current returns of the BUX index are determined by the evolution of the American market two weeks before. This is somewhat surprising, since during a crisis the rapid flow of information and news determines quick reactions from the investors’ side and trends which occurred weeks ago have almost no impact on their current decisions.

  17. Methodology and results 4. VAR models VAR models with two variables (volatilities to volatilities) between S&P, CEE and Western European countries • In terms of volatility we observe that most of the coefficients become statistically significant during the crisis. Using Wald test we find out a significantly increasing spillover effect from US market to the markets from UK, Germany and Poland (marked with red in the table).

  18. Methodology and results 5. Granger causalityWe perform Granger causality tests (Wald statistics) to investigate the causal relationships among the returns of the US and European markets analyzed. • During the crisis more causal relationships can be identified. • If before the crisis the US market caused only four markets (Hungary, Czech Republic, Poland and Germany), during the crisis, US market Granger causes all markets analyzed except for Bulgaria and Germany. • In the case of Bulgaria this analysis confirms the previous results in which its market evolution does not appear to be influenced by any of the developed markets. This could be the result of its different monetary policy (the exchange rate peg).

  19. Methodology and results 6. Cointegration relationships between US and European indices We conduct a Johansen test for the pairs (S&P-other index) to establish if the variables are cointegrated or not. Then we estimate the VECM for the cointegrated variables. The three cointegration relationships are found only during the turmoil.

  20. Methodology and results 7. Impulse-response analysis We examine the impulse-response functions based on VEC models estimated in the previous section. The shocks on S&P causes responses on BET, DAX and PX indices; the inverse relation is not sustained by the graphics. We choose two periods: one of 4 weeks and the other of 12 weeks. For both intervals, it seems that BET index responds to S&P socks in the first week and after that the response is decreasing.

  21. Methodology and results 7. Impulse-response analysis For DAX and PX indices the responses to S&P maintained during several weeks.

  22. Conclusions In terms of returns, we conclude that: • English and French markets are significantly influenced by the American market during the crisis; • The close relationships between S&P and developing markets are maintained during the crisis; • Hungarian market has the tightest relationship with the leading markets on our continent. In terms of volatility, we find that: • Although the coefficients between S&P volatilities and volatilities on the European stock markets become significant during the crisis, there is a significantly increasing spillover effect only from US market to the markets from UK, Germany and Poland; • There is no major influence from the part of FTSE, DAX and CAC indices on the developing markets during the crisis (except Hungary and Poland); • The Hungarian and the Polish markets have the strongest relations with developed markets in terms of volatility, as opposed to the Bulgarian one which is independent. Granger causality and existence of cointegartion relationships only during the crisis stands for intensified interrelationships during crisis. Our results are similar to those encountered by the recent studies. The developed stock exchanges are not influenced by smaller markets either during stability period or during crisis. Also, not all developed countries have influence on emerging markets. During the crisis US market has stronger linkages with the developed countries than with emerging ones, although we can remark that the relation of the American market with CEE countries is stronger than that between the Western European countries and CEE.

  23. References • Awokuse, O. T., A. Chopra, and D. A. Bessler (2009), “Structural Change and International Stock Market Interdependence: Evidence from Asian emerging markets”, Economic Modeling, 26, 549-559 • Bonfiglioli, A. and C. Favero (2005), “Explaining Co-Movements between Stock Markets: The case of US and Germany”, Journal of International Money and Finance, 24, 1299-1316 • Cheung, W., S. Fung, and T. Shin-Chuan (2010), “Global Capital Market Interdependence and Spillover Effect of Credit Risk: Evidence from 2007-2009 Global Financial Crises”, Applied Financial Economics, 20:1, 85-103 • Chuang, I. Y., J. R. Lu, and K. Tswei (2007), “Interdependence of International Equity Variances: Evidence from East Asian markets”, Emerging Markets Review, 8, 311-327 • Egert, B. and E. Kocenda (2007), “Interdependence between Eastern and Western Stock Markets: Evidence from Intraday Data”, Economic Systems, 31, 184-203 • Gklezakou, T. and J. Mylonakis (2009), “Interdependence of the Developing Stock Markets, Before and During the Economic Crisis: The Case of South Europe”, Journal of Money, Investment and Banking, 11, 70-78 • Grey, D. (2009), “Financial Contagion among Members of the EU-8: A Cointegartion and Granger Causality Approach”, International Journal of Emerging Markets, 4:4, 299-314 • Forbes, K. and R. Rigobone (1999), “No Contagion, only Interdependence: Measuring Stock Market Co-Movements”, NBER Working Paper Series • Ozdemir, Z. A. (2009), “Linkages between International Stock Markets: A Multivariate Long-Memory Approach”, Physica A, 388, 2461-2468 • Serva, D. and M. T. Bohl (2005), “Financial Contagion Vulnerability and Resistance: A Comparison of European Stock Markets”, Economic Systems, 29, 344-362 • Syriopoulus, T. and E. Roumpis (2009), “Dynamic Correlations and Volatility Effects in the Balkan Equity Markets”, Journal of International Financial Markets, Institutions and Money, 19, 565-587

  24. Thank you!

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