Policies and Sustainable Economic Development | 631 Measuring Contagion Risk among Vietnam’s Listed Commercial Banks NGUYEN THI MINH HUE National Economics University - minhhuektqd@gmail.com/huenm@neu.edu.vn NGUYEN THE TUNG National Economics University TRAN DANG MINH National Economics University NGUYEN HUU QUANG National Economics University LAM HONG PHONG National Economics University TRAN MINH KHOI National Economics University Abstract Commercial banking system is a dominant sector in the Vietnamese economy The weakness and failure of one particular bank may have a big impact on the banking system as well as the economy Given the case study of Lehman Brother Holding Inc (2008) beyond the United State and the worldwide economies, contagion risk among commercial banks has been an intriguing issue in the literature During the recession period of Vietnam, there is a need to restructure the banking system and to discover potential risks among commercial banks Due to the data unavailability, we follow Gropp and Moerman (2004) to raise awareness of the contagion risk across eight listed commercial banks of Vietnam Particularly, we try to measure how other banks are affected when one bank falls into the extreme event and finds the signal of contagion risk The result of this paper may lead to implication of the overall picture of the banking system The names of the listed bank are coded randomly to protect the confidential information of the banks Three of them (D, E, H) are showing extraordinary vulnerability, whereas two others (B, C) are more stable While the strongest resistance to contagion is found for the case of Bank F, showing the lowest interconnectedness for both “co-exceedances” and “Granger” test, the other banks in the sample reveal controversial results To conclude, banks are susceptible to others’ operating situation, and the research should be expanded throughout the whole system with the legal enhancement of data transparency and adequacy Keywords: contagion risk; banks; Vietnam; signal Introduction 632 | Policies and Sustainable Economic Development In recent year, contagion risk is becoming a hot trend globally and has been debated intensely ever since The world economic are getting more and more integrated, financial institutions increased their interconnectedness to each other It is needless to say that this integration provides us with huge advantages of labor, information and cost savings, which ultimately leads to improvement of the liquidity and depth of the market However, with great advantages come great obstacles to overcome In this situation, it is the case of “contagion” in the system The collapse of the Lehman Empire which led to 2008 crisis is one example of contagion effect If this is the situation of countries in the first world-group, it becomes direr when it comes to developing countries such as Vietnam Thus, in this paper, we attempts to make a contribution to measure the contagion risk among bank of Vietnam We will be discussing a methodology by Gropp and Moerman (2004) to locate the direction of contagion from one institution to another We propose to use market data, especially the distance to default, to examine bank contagion The approach based on the use of “co-exceedance” and extreme value theory in examining contagion risk among institutions In this paper, for the first part, we will discuss about different literature on the subject of contagion and methods to measure contagion risk In the second part, we will show the detail method that was applied in this paper The third part will be focused on analyzing result of the research, and for the final part: conclusion and implication for stakeholders Literature review The term financial contagion has created controversy throughout the past years Until now, there has not been an official announcement or mutual agreement upon this matter Thus, to what degree responsibility should be assigned to contagion in financial crisis is still ambiguous Some analysts even believe that there is no contagion but only the worsening economic conditions that cause depositors to take their money out of weak banks and put it into healthier ones Taking the situation of this research into concern, we decide on the definition of contagion as “one bank being hit by an idiosyncratic shock that is also transmitted to other banks” as suggested in the work of Gropp in 2004 to be likely the most feasible term to use for the purpose of investigating the regional contagion We will not specify channel of transmission, but one could imagine money markets, payment systems, equity (ownership) links and “pure” contagion The definition could avoid problem of overstate or understate the effects of contagion Its advantages allow us to develop a method to identify the direction of contagious influence among banks rather than the degree of contagion effects on financial system As such, in this paper, we avoid talking about the exact quantities but only try to measure the extent to which Vietnamese banking system has become interconnected and how a problem of an individual bank could spread across our market The methods debated bellows will follow what we have previously stated as definition Policies and Sustainable Economic Development | 633 In some papers, contagion is time to time referred to the interconnectedness as these two terms is closely related even when there are certain differences between them Therefore in this work we will not specifically clarify the two of them but to use them interchangeably We employ the Model taken from the study of Gropp and Moerman (2004) as the basis for this paper The work is based on Longin and Solnik’s (2001) and Bae et al.’s (2003) evidence that the observed coexceedances (i.e the presence of two or more banks in the tail of the distribution simultaneously) are consistent with a different simulated distribution which suggests it could be a reliable method to measure contagion risk The co-exceedances mentioned in the paper is calculated on the basis of Distance to Default (DD), which in Gropp et al (2003), was shown as a particularly suitable way to measure bank risk The DD is outstanding from other risk measurement as it could avoid problems such as subordinated debt spreads The distance to default combines information on stock price returns with asset volatility and leverage and represents the number of standard deviations away from the default point The default point is defined as the point at which the liabilities of the bank are just equal to the assets For the case of Vietnam, we choose this method as we deemed it to be the most suitable considering our situation Not only is it proved to be a relatively effective way of measuring contagion, there are high chances that this method can be applied on the market of Vietnam Our domestic stock market has developed enough for data and information in full disclosure to be found Furthermore, most of the biggest banks domestically have been listed on the stock market It is possible for us to collect sufficient data for calculation of the co-exceedance Through the studying from other studies, we were able to get some insight and by conducting our own one, we can say that it is different from the previous papers First of all, the researches in Vietnam only focus on systemic risk but the one focusing on contagion risk is nearly nowhere to be found In a developing country such as our, the new term of contagion risk may be deemed as a relative new concept Through gathering information, in our knowledge, this paper may be the first research that tries to measure the effect of contagion in the system of Vietnam banking Secondly, the method we would be using to measure bank risk is called the distance to default This combines the information on leverage, asset volatility with data of full exposure which is superior to those measurements of risk that have previously been done domestically Methodology and research model We employ the model taken from the study of Gropp and Moerman (2004) as the basis for this paper The approach is related to the suggestion of Bae et al (2003) that the behavior of tail observations for financial market data is quite different from the behavior of other observations (extreme value theory) We empirically examine contagion in sample of eight listed commercial banks in Vietnam These banks were coded ramdomly as A, B, C, D, E, F, G and H For each bank, we will calculate their 634 | Policies and Sustainable Economic Development distances-to-default (DD) by days using market data The distance to defaults was chosen, as in Gropp et al (2002) argued that specifically with respect to banks, DD may be a particularly suitable and all-encompassing measure of bank risk As it combines both the information about stock returns with leverage and volatility information, it could avoid problems of other measures (like subordinated debt spreads or unadjusted stock returns) The distance to default of each bank can be calculated following the Black-Scholes model After calculating the distance to default of each bank, we then obtain the change in DD by taking ln(ddt/ddt-1), using the weekly first different to default which in the following will be denoted as ln(∆dd) Hence, ln(∆dd) measures the percentage change in the number of standard deviations away from the default point For the next part, we will test the banks contagion risk using a concept called “co-exceedance” (Bae et al., 2003) We define a co-exceedance as period (in this paper: a week) during which two or more banks first difference in the distance to default was in “extreme value” The more times a bank in a co-exceedance, the more likely it can create contagion risk on others We will implement the test for the “extreme value” of 5% bottom tail As our database is quite small, we decided to extend the test to 10th percentile to provide a more comprehensive view about the contagion risk in banks of Vietnam While the 5% bottom tail has significant implication in predicting the effect of the risk in recession period, the co-exceedances of the 5% top tail of the distribution could give us an overview about the trend of contagion Thus, we also perform the calculation for and 10% top tail (also known as 90th and 95th percentile) In order to test whether the result of co-exceedances can explain the contagion risk, we then use the Granger-causality (GC) method suggested in Chan-Lau et al (2007) as the robust of the model We implement a set of pairwise tests on the banks to determine the broad trends in the ln(ΔDD) relationships between pairs of banks “While this could be captured by calculating the rolling correlations between the ln(ΔDD)s, GC tests go beyond standard correlations; they show whether the past ln(ΔDD)s of a particular bank help to explain the current ln(ΔDD)s of another bank, after also taking into account the past ln(ΔDD)s of the latter” (Chan-Lau et al., 2007) The Granger-causality test may not as reliable as the Monte Carlo test, as correlations in bank soundness during normal times provide little information on the likelihood of contagion However, it could give us an overview look about the Vietnam market Contagion risk results 4.1 Co-exceedances and identification of contagion risk Through the use of co-exceedances, there are possibilities to apprehend the direction of contagious influence among banks For the research purpose of clearly understood the situation, we will proceed to calculate and analyze the result for co-exceedances of the eight selected banks in the quantile of 5% and 10% respectively Policies and Sustainable Economic Development | 635 Table Overall descriptive statistics of the research Distance to Default Log-differenced DD (weekly 1st different) Number of observations (weeks) Number of tail observations (5%) Number of tail observations (10%) Table Summary statistics of (co-) exceedances for weekly log-differenced distance to defaults for individual banks (5% bottom tail) >6 A B C D E F G H Table shows the number of times one bank co-exceedances with other banks in the whole period For example, looking at second column of Bank A, it means that during the period of observation, the bank has two weeks exceedance with five banks, including itself The table indicates the number of co-exceedances at the 5th quantile among banks As we expected, the bank G, with the highest standard deviation of ln(∆dd), is the bank with the most exceedances in the bottom tails with 20 weeks in the tail distribution This means that the bank G is rather unstable relative to others, its changes in distance to default has declined below the 5th quantile more than any other banks has However, when taken contagion into account, the bank G is not the most vulnerable bank Half of the time of its exceedances, there is only one bank that is also in the tail event at the same time with the bank G, ultimately it leads to only 10 weeks of co-exceedances between the bank G and the other two and more banks Besides, the bank D, with the record of 12 exceedances, there are 11 times the bank in the tail event when three or more banks are also in the same situation (co-exceedances), which is relatively high compared to the result of others This suggested the high level of interconnectedness of the bank D with other banks which means the need for its extra regulation in term of contagion 636 | Policies and Sustainable Economic Development The result for the bank B and C are also match with what we predicted Among six banks with about 300 observations, those banks witness the two low numbers of weeks of co-exceedances, only co-exceedances of more than banks for seven times Notably, the bank C, although is one of the three banks with the largest total assets; ranked last position among the six banks This could hint that the size of the bank isn’t the main source of contagion From all banks, bank F is the bank that most unlikely to be involved in contagion, with the lowest number of both exceedances and coexceedances, and respectively Some may argue that this low record is the result from the fact that their number of observations is only 193 compare to approximately 300 of other banks Nevertheless, taking note that its’ counted number of co-exceedances is even lower than that of the bank I, which is only observed for 76 weeks Only observed for such a short period, the observation time for the bank A is quite low compare to other banks, thus the result may be not much of significant Despite that, the bank A still shows itself as an influential bank Considering the five times co-exceedances in only less than a quarter period of observation of other banks, we believe this bank shows a potential risk for contagion In conclusion, the tables illustrate that there is significant interconnectedness among banks although the magnitude of it is rather unsubstantial In order to make up for this shortcoming one way or another, we also conducted the test on the 10% tails However, as it represents smaller shock, the result for the risk of contagion could not be varied and not as precise as the 5% threshold Result for the 10% test is available in Appendix The following part will examine the specific bank-to-bank contagion using the cross-table for number of pair co-exceedances The result shown in the cross table could give us a better view about the direction of contagious influence among Vietnamese banks Table Cross table for number of times banks in 5% bottom tails of individual banks Number of times banks in 5% bottom tails A A - B C D E F G H Total We can see the details in Table For example, bank B and A has two weeks that they are both in the 5% bottom tail Still, from the table, it seems like bank D is showing potential in creating 19 Policies and Sustainable Economic Development | 637 contagion on a large scale as the bank are co-exceeded with others for no least than three times each It also holds the record for the highest time that the bank co-exceeded with others For instance, seven weeks with the bank H As the average number of pair co-exceedances is four, it suggests a very close relationship between the two banks The only other pair that has the same number is bank E-G Two pair of banks that have the lowest number of week in tails distribution together is bank F-C and bank F-G This one strengthens the evidence for low contagion risk in the bank F There is no pair that has zero co-exceedances Overall, the pair coexceedances are ranged from three to four, which in turn suggest a decent correlation of banks in Vietnam financial system As we have mentioned before, we want to closely examine whether the contagion risk among big banks is higher than the rest However, the result again seems to reject our hypothesis The pair co-exceedances for bank A, C and D not seem to show much of a problem, with three and four for bank C-A and bank C-D respectively The result for pair of bank D-A is somehow more significant, with five week of co-exceedances, which in turn suggests a real threat of contagion between these two banks Regardless of the fact, this alone is still not enough to prove for any relationship between banks size and contagion To sum things up, the average pair co-exceedances are ranged from three to four For any pair with more than four co-exceedances, we believe these two should receive extra regulation in term of contagion risk However, as same as the problem we faced in the previous part; the magnitude of co-exceedances is quite low that made the outcome shown above rather ambiguous We also conducted the test on the 10% tails However, as it represents smaller shock, the result for the risk of contagion could not be varied and not as precise as the 5% threshold Result for the 10% test is available in Appendix 4.2 Robustness test: Granger-causality During the Granger test, it appears that the bank D is showing quite substantial “causality” with significant of less than 1% with all other banks Once again, bank D is showing proof to be the bank that to be the most likely to succumb to contagion risk among the others documented in the sample While the bank D seems to be in the red light, the bank E is also not in the safe zone either The bank has “causality” with six other banks, following closely to the bank D and taking the second out of those banks to be the most exposed to the danger We could not deny the vulnerability of the bank to contagion With the result almost identical to the previous one, the bank H is causing “granger” to four banks and at the same time, being “caused” by the rest of the banks taken into the test 638 | Policies and Sustainable Economic Development The pairs of bank C-D and bank H-D show result not out of our expectation These two pairs witness the two-way “causality”, which in turn point out that these banks are having high chances of causing contagion to each other The test also suggests the bank A is not so likely to expose to contagion which is close to the result in 10% but opposite to our study in the 5% tail On the other hand, the case of bank G emerges to be the most interesting The finding in the Granger test gives out rather different comparing to what we have discovered throughout the previous testing which gradually suggests a low risk of contagion In addition, the test also implies that the contagion risk could only be transferred from the bank E to bank G but not in versa This case should be considered further in future studies Table Pairwise Granger-Causality between Commercial banks of Vietnam December 2009 – January 2016 Banks A A B C D X E F G H Factors in the columns are Granger-caused by factors in the rows The Granger-causality test used 30 lags The F-statistic of the joint significance of the lags of bank in explaining bank is noted in the matrix, an “X ” is noted if the F-statistic shows significant GC at percent or less In short, “X” denotes that “the row” Granger-cause “the column.” Implication and conclusion 5.1 Implication about the contagion risks among Vietnamese commercial banks Throughout our examination, the eight banks are showing phenomenon signs The financial system is showing trend of interconnectedness domestically, though vividly The evidence concluded from the result can only be verified by testing with difference assumption of the distribution (we suggest the use of Monte Carlo model) However, throughout the research we can still see the hint of movements from contagion Despite that as the fact, some banks are showing extraordinary vulnerability The bank D is taking the lead as the bank to be the most easily to be affected by contagion Closely standing beside it is the bank E, showing intense weakness to the risk The bank H, while being not as in danger as the two previous banks, is also not in the clear either These three banks would better be preparing for further measurements and attention Policies and Sustainable Economic Development | 639 The bank G and bank A are proving to be the most interesting cases The bank G is showing quite dangerous result during the use of the model but through the Granger test, the bank tends to be not as much being in the danger area We recommend further research being done on the matter as for now, the situation is uncertain The bank A is showing significant result to be in the red as much as the rest of them During the 5% quantile, contagion tends to be the most likely to be in concern However, during the 10% threshold and in “Granger causality”, it said to be otherwise There is hardly any sign of contagion for the bank For this reason, we conclude that the banks’ exposure is still unclear The two banks B and C are proving to be most stable Healthy as they are, their resistance is quite remarkable The last but not least, the bank that has the strongest resistance to contagion must be bank F, showing a lowest contagion risk for both “co-exceedances” and “Granger” test Throughout the research, we could conclude that, the risk of contagion in Vietnamese banking system is a certain possibility According to the tests result, the selected banks have shown quite a number of coexceedances However, the experiences of measuring contagion risk have not being clear in other countries, which leads to the lack of benchmark for Vietnam This ultimately put the situation of Vietnam regarding contagion was still in the mist 5.2 Implication to Commercial Banks in Vietnam From our study, we figure out that among banks, bank D is the bank that vulnerable to contagion the most It has the potential to create contagion on most of the others Thus, I believe the bank should receive extra regulation for their activities Bank D should be more cautious with it banking business to prevent any cause of contagion The same thing should be applied for the bank H and bank E as these two are also shown a high risk of contagion These banks should be more careful about its activities as well as keep a close eye to their counterparties As the result for the bank G and bank A is rather inconsistence, we cannot clearly say anything about these two However, they should not let their guard down or else, somehow in the future, they may find themselves as the victims of the contagion The overall studies suggest a low risk of contagion for bank B and bank C, so currently, these bank don’t have to worry much about the issue Although the bank C is in the safe zone regarding contagion, we found some other aspect worth looking into It is shown in the result that the distance to default of the bank is decreasing The risk of bankruptcy is coming closer and closer as we are discussing and the bank would better focus on this problem for now The bank B is doing quite well compare to its recent past The distance to default of this bank used to be seen as the lowest and it had been struggling to get out of this situation However, nowadays it appears that the bank B is improving its performance day by day The case of bank F is also quite good Its standing among eight banks is safest from the risk of contagion Though the bank is not likely to face the problem 640 | Policies and Sustainable Economic Development anytime soon, it brings no harm to come up with some prevention methods to minimize the damages if needed 5.3 Conclusion In conclusion, we believed this paper has achieved our initial goal of making a contribution to recognize the contagion risk among banks of Vietnam There are some syndromes for contagion that can only be verified by testing with difference assumption of the distribution, which we suggest the use of Monte Carlo model Throughout the research, we can see some sign of the risk direction The result varies among banks, which suggests bank D, H, and E with a high risk of contagion and bank B, C and F with low one For the two banks A and G, the result is inconsistent and need to be examined in further studies From what have been done, we apprehended contagion risk in Vietnam as a real threat However, its magnitude and influence is uncertain The cross-border contagion risk is also ignored The model need to be more developed, which need to have the result more comprehensively In the near future, we hope to improve our work in order to provide a better view about the contagion risk in Vietnam Appendix Appendix 1: Co- exceedances for weekly log-differenced distance to defaults for individual banks (10% bottom tail) Number of (co-) exceedances in the bottom tail (10%) >6 A B C D E F G H Appendix 2: Cross-Table for pair co-exceedances (10% bottom tails) Number of times banks in 10% bottom tails - A A - B C D E F G Policies and Sustainable Economic Development | 641 H Total 24 References Bae, K., Karolyi, G., & Stulz, R (2003) A new approach to measuring financial contagion Review of Financial Studies, 16, 717-763 Blank, S., Buch, C., & Neugebauer, K (2009) Shocks at large banks and banking sector distress: The 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A ninety-year perspective Review of Financial Studies, 1(1), 403-425 Longin, F., & Solnik, B (2001) Extreme correlation of international equity markets Journal of Finance, 56(2), 649-676 Rogalski, R J (1984) A further investigation of the weekend effect in stock returns: Discussion Journal of Finance, 39(3) 835-837 Taylor, J., & Williams, J C (2011) Further results on a black swan in the money market Financial Crisis, 66 J.FIN.1109 SIEPR Discussion Paper No 07-46  ... Implication and conclusion 5.1 Implication about the contagion risks among Vietnamese commercial banks Throughout our examination, the eight banks are showing phenomenon signs The financial system... Vietnam regarding contagion was still in the mist 5.2 Implication to Commercial Banks in Vietnam From our study, we figure out that among banks, bank D is the bank that vulnerable to contagion the... see some sign of the risk direction The result varies among banks, which suggests bank D, H, and E with a high risk of contagion and bank B, C and F with low one For the two banks A and G, the