Republic of Poland
Technical Note on Stress Testing the Banking Sector
Author:
International Monetary Fund. Monetary and Capital Markets Department
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Publication Date:
15 Aug 2013
eISBN:
9781484331163
Language:
English
Keywords:
ISCR; CR; bank; banking system; capital adequacy ratio; liquidity; central bank; Tier 1; capital requirement; return on assets; trigger bank; parent bank; capital base; conservation buffer
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This Technical Note discusses results of stress testing of the banking sector in Poland. The Polish banking system is well capitalized and liquid, as confirmed by stress tests results. Polish banks are, in aggregate, resilient even under severe adverse scenarios. Some small banks could fail to meet minimum regulatory capital and liquidity requirements in these scenarios, but with little impact on the overall banking system. Tests showed that only small banks, together representing up to 30 percent of the assets in the system, may have problems meeting the Basel III capital requirements in the recession scenarios.

Abstract

This Technical Note discusses results of stress testing of the banking sector in Poland. The Polish banking system is well capitalized and liquid, as confirmed by stress tests results. Polish banks are, in aggregate, resilient even under severe adverse scenarios. Some small banks could fail to meet minimum regulatory capital and liquidity requirements in these scenarios, but with little impact on the overall banking system. Tests showed that only small banks, together representing up to 30 percent of the assets in the system, may have problems meeting the Basel III capital requirements in the recession scenarios.

I. Introduction

1. The Polish banking system is dominated by foreign-owned banks, which account for about two thirds of the system by assets. The largest bank is a domestic bank that is partly owned by the state. The state also has controlling shares in three other banks. The banking system is not highly concentrated; the top 5 banks account for about 44 percent of system assets. Foreign banks have retrenched somewhat, however, and this deleveraging has led to some consolidation.

2. Poland’s banking system weathered the global financial crisis well. Inevitably, though, the crisis was a period of intense stress for the banking system. The zloty depreciated sharply, raising the debt servicing burden on foreign currency-denominated mortgage loans, which were popular in Poland as they allowed borrowers to take advantage of lower interest rates elsewhere particularly in Swiss francs.1 The broader economic deterioration weighed on asset quality of consumer and corporate loan portfolios. Liquidity strains emerged, as banks found it more difficult to hedge their portfolio of FX loans on the market. The Polish banking system is well-capitalized and liquid, and much of the capital is of high quality. Profits in 2011 and 2012 were historically high, and regulatory guidelines limiting dividends have also aided capital building. Should banks’ own buffers be insufficient, foreign-owned banks can, albeit to varying extents, rely on support from their parent banks. Poland also has a deposit insurance scheme operated by the Bank Guarantee Fund (BFG).

3. Although conditions have improved, several factors could contribute to pressure banks’ profits and asset quality. External developments, coupled with weaker internal drivers of growth, have caused growth to slow sharply. Rising unemployment coupled with falling house prices and potential weakness in the zloty would translate into weaker asset quality and lower profitability. The uncertain outlook emphasizes the importance of evaluating the resilience of the banking system to potential adverse scenarios.

4. Regulatory stress tests are regularly used by the authorities to assess the resilience of the banking sector to adverse shocks. Twice a year the central bank (NBP) conducts a top-down macro stress test, including market risk shocks, and publishes the results in its semi-annual financial stability report (FSR). The macro stress test is complemented by a liquidity risk test and several sensitivity tests designed to evaluate the loss absorption capacity of banks to isolated credit risk and market risk events. Figure 1 illustrates the stress testing framework of the NBP. The Polish financial supervisory agency (KNF) has conducted an annual bottom-up stress test for the past three years. The test results are used to guide supervisory decisions such as the authorization to distribute dividends. In contrast to the central bank’s stress tests, the results of the bottom-up tests are not generally made public.

Figure 1.
Figure 1.

Poland: National Bank of Poland Stress Testing Framework

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: NBP.

5. The regulatory stress tests are well designed, helping to identify risks and vulnerabilities. Discussions with the authorities and market participants indicate that staff on both sides is highly knowledgeable about the functioning of the banking and financial system, a knowledge that is reflected in the design of the tests, the interpretation of the results, and the identification of vulnerabilities in the system. Market participants noted that regulatory stress tests were useful for checking the consistency of their risk management practices and for guiding their medium-term business strategy.

6. In the context of the 2013 FSAP Update, the authorities worked with the FSAP team to conduct top-down stress tests. The tests aimed to assess the resilience of the banking system to severe but plausible macroeconomic scenarios. These scenarios are hypothetical, and serve to guide the authorities in thinking about risks to the banking system and in preparing mitigating measures. The NBP conducted top-down solvency and liquidity stress tests based on scenarios agreed with the FSAP team. These tests were complemented with sensitivity tests to large isolated shocks affecting counterparty risk, credit risk, and market risk. The FSAP team also conducted a top-down stress test that inferred the risk of default from market data. While no bottom-up solvency stress tests were conducted in connection to the FSAP Update, the KNF made available to the FSAP team the results of its latest regulatory bottom-up stress test.

Summary of Recommendations

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“Immediate” is within 1 year; “near-term” is 1–3 years; and “medium-term” is 3–5 years.

II. Solvency Stress Tests

7. The NBP and the FSAP team conducted separate top-down solvency stress tests to assess the resilience of the banking system under different adverse scenarios. Four different macroeconomic scenarios, in consultation with the FSAP team and the IMF country desk, were considered over a five-year horizon: a baseline scenario consistent with the IMF country desk projections, a V-shape recession, a U-shape recession, and a L-shape recession. The paths of the macroeconomic and financial variables in each scenario were calculated using the NBP’s NECMOD macroeconomic model (Table 1). The scenarios entail growth rates well below the historical average for Poland.2 The V-shaped scenario sees a sharp decline in year-on-year GPD growth, while the U-and L-shaped scenarios entail two consecutive years of negative growth. Given that growth in Poland stayed positive in 2009 after the Global Financial Crisis, these assumptions represent substantial stress.

Table 1.

Poland: Macro-Stress Test Scenarios

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Source: NBP; and Fund staff estimates.

8. Capital requirements in the stress tests corresponded to those specified in the Basel III implementation timeline. According to the NBP, there were no substantive differences between Tier 1 capital and core Tier 1 capital, while total capital was only moderately higher than Tier 1 capital due to low use of subordinated debt in capital. Hence, the relevant minimum capital requirement in the stress tests were set at 8 percent of RWA for the years 2013 to 2015; 8.625 percent of RWA for 2016; and 9.25 percent of RWA for 2017. The minimum Tier 1 capital requirement was set at 4.5 percent in 2013; 5.5 percent in 2014; 6 percent in 2015; 6.625 percent in 2016; and 7.25 percent in 2017. Both these requirements encompass the capital conservation buffer, at 0.625 percent in 2016; and 1.25 percent in 2017. Additionally, the results were also calculated without the capital conservation buffer. The minimum core Tier 1 capital requirements were used only to determine the dividend payout ratio (Table 2).

Table 2.

Poland: Dividend Payout Ratio Conditional on Capital Buffers

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Source: IMF staff estimates.

9. The composition of the balance sheet of the banks was assumed static during the stress test. Loans were classified into three categories: corporate loans, consumer loans, and mortgages. The balance sheet of a bank was assumed to grow at the nominal rate of GDP (if positive) provided it meet the minimum capital requirement.

10. Dividend payouts were possible only when banks fulfilled capital adequacy requirements. The dividend payout ratio depended on the bank’s buffer over the minimum core Tier 1 capital requirement, and was set equal to the maximum payout ratio shown in Table 2 (in the range of buffer over 2.5 the dividend payout ratio was set at 75 percent).

A. Top-Down Balance Sheet Stress Tests3

11. For the 2013 FSAP Update, the NBP used its stress testing framework to conduct a top-down solvency stress tests following guidelines agreed upon with the FSAP team. The stress tests included the 20 largest banks comprising about 85 percent of the total assets in the banking system. The scenarios included a baseline scenario and three adverse scenarios (see Table 1).

12. Satellite models mapped the scenarios into credit losses and net income. The NBP used panel data models for interest income on loans, interest expenses, and credit losses (expressed as a ratio of loans, interest bearing liabilities, and credit portfolios respectively), and were estimated using quarterly data for the period 1997–2012. For credit losses, the loan portfolio was divided into three major categories: commercial loans, mortgage loans, and consumer loans. Model projections were subject to judgment-based adjustment to account for regulatory and market changes in lending standards.

13. Changes in RWA were calculated following an approximate Basel II standardized approach. The standardized approach was used to determine the initial RWA weights, which were kept fixed during the stress scenarios. The RWAs were adjusted to account for losses under the stress test horizon.

14. In the NBP top-down stress tests, up to 30 percent of the analyzed group of banks may not meet Basel III capital requirements in the recession scenarios. The erosion of capital buffers is mainly concentrated in the period up to 2015 and affects small banks (Table 4). The most severe scenario is the L-shape recession, which leads to total capital needs of about PLN 10.5 billion (out of which 2.5 billion would result from capital conservation buffer kicking in), equivalent to less than one percent of the assets in the banking system.

Table 3.

Poland: Central Bank Top-Down Solvency Stress Tests—CAR Distribution by Percentile Buckets

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Source: NBP.
Table 4.

Poland: Characteristics of Representative Banks used in FSAP Top-Down Stress Tests

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Source: NBP.

15. The methodology of the FSAP top down stress test was based on a simple model of income and capital dynamics. Namely, capital one period ahead was set equal to capital in the current period plus current period net income after subtracting credit losses and dividend payouts. The probability of default (PD) for each loan category was approximated as the ratio of the flow of nonperforming loans (NPLs) to total loans in the category. As with any accounting measures, NPLs may not reflect all forward looking information on losses.

Estimates of the loss-given-default (LGD) for each loan category, calculated as the NPL coverage by loan loss provisions, as well as the NPL flows were provided by the central bank. Changes in RWAs were calculated in according to Basel II (BCBS, 2006, International Convergence of Capital Measurement and Capital Standards, paragraph 272).

16. The FSAP top down stress test was performed using representative banks in each scenario. Aggregation was necessary owing to data confidentiality constraints faced by the authorities.4 For each scenario, the representative bank were defined by first dividing the sample of banks into six percentile buckets based on the regulatory capital adequacy ratio (CAR) test distribution at the end of the NBP stress test. Each representative bank was then constructed by aggregating the capital, credit risk exposures, and risk-weighted assets (RWAs) of all the banks in the corresponding bucket. Table 4 summarizes the characteristics of the representative banks for each scenario.

17. Some caution is required when interpreting the results of the FSAP top-down balance-sheet solvency tests. The tests were conducted using representative banks since data confidentiality constraints prevented conducting them using individual bank data. The impact of the adverse shocks on the representative banks, however, may not necessarily reflect the reaction of the individual banks.

18. The results of the FSAP top-down stress test are consistent with the NBP top-down stress test. Table 5 shows the evolution of CARs under each scenario. Overall, the representative banks corresponding to the bottom three buckets could face problems meeting CAR in the first two years of the recession scenarios. The strong rebound in net income experienced after the third year helps banks in the top three buckets to make up for earlier losses. These representative banks represent around 30 percent of total loans.5

Table 5.

Poland: IMF Top-Down Solvency Stress Tests—CAR Distribution by Percentile Buckets

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Source: Staff calculations.

B. Top-Down Market-Based Stress Tests

19. To complement the balance sheet stress tests, the FSAP team also conducted market-based top-down stress tests. The tests were based on models capturing the effects of changes in economic growth on the dynamics of the default risk of a bank. The default risk corresponded to expected default frequencies (EDF) implied from equity prices and obtained from Moody’s analytics. The EDF can be linked to the capital structure of the firm using a structural credit risk model. As a result, it is possible to map the stress scenarios into changes of the capital asset ratio of a bank. The annex describes the methodologies in detail.

20. The results suggest some banks could face substantial declines in their capital-asset ratios. Furthermore, the default of a few institutions cannot be ruled out under the adverse scenarios. The problems, however, are concentrated among smaller institutions and the high capital adequacy ratios in the system suggest that despite large declines, capital adequacy ratios could remain above regulatory minimum levels. There are some caveats in interpreting the results, though. Information from equity prices may be unreliable for many of the banks analyzed owing to the lack or scarcity of secondary market liquidity. Additionally, in many cases foreign parent banks hold controlling shares of the listed Polish banks, so that the information value included in the equity prices in free-float may be limited.

III. Bottom-up Solvency Stress Tests

21. No specific bottom-up stress tests were conducted in connection with the FSAP update but the authorities shared the results corresponding to the latest annual regulatory test. As with the top-down stress tests, results were provided in aggregate or in distributions to maintain confidentiality.6 The test covered 32 banks accounting for 90 percent of the assets in the system; the KNF has gradually increased the coverage of the banking system over the three years the test have been conducted. Three 1½-year scenarios were considered: a baseline scenario incorporating the central bank’s economic projections; an adverse scenario triggered by negative external shocks; and another adverse scenario driven by domestic shocks. Additional macroeconomic parameters, including unemployment rate, inflation, exchange rate, short and long term interest rates and residential real estate prices were specified as well (Table 6).

Table 6.

Poland: Bottom-Up Stress Test Scenarios

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Apply to deposits and loans of the financial sector (non-resident) and derivatives.

Source: KNF.

22. Compared to top-down stress tests, the bottom-up test factor in banks’ measures and policy responses to the shocks. Banks were allowed to factor in the impact of measures aimed at mitigating the shocks. The scenarios also accounted for policy responses by the authorities.7 Banks were asked to use their own internal models to map the scenarios to the impact on credit risk parameters, and then evaluate the resulting impact on their financial condition and compliance with regulatory requirements. Banks submitted in some cases quite lengthy justification for their models and assumptions. In a limited number of cases, the KNF amended banks’ responses using supervisory judgment.

23. Like the top-down stress tests, the KNF’s 2012 bottom-up stress tests indicate that the banking system will be resilient in an adverse scenario. However, the two sets are not directly comparable because of the aforementioned differences in the scenarios. The bottom-up stress tests find that no more than two banks, representing about 1 percent of total banking system assets, fall below the regulatory minimum capital ratio in the adverse scenarios (Figure 2). These results were qualitatively similar to those reported by the NBP in its December 2012 Financial Stability Report (FSR).

Figure 2.
Figure 2.

Poland: KNF Bottom-Up Stress Tests—CAR Distribution

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: KNF.

24. The KNF complements the information from the bottom-up stress tests with onsite and offsite supervisory knowledge and peer analysis. Onsite bank inspections are infrequent, though, so it is not clear if onsite expertise is up to date. The KNF also conducts a peer analysis across banks. However, there is substantial heterogeneity in the banking system and the lack of natural peers for some banks makes it difficult to draw conclusions from a comparison of their results with those of other banks.

25. Banks indicated that the bottom-up stress testing exercise was useful for their internal strategic planning, complementing their own internal stress tests. The tests highlight risks that they might have overlooked. Banks also conduct their own internal stress tests as a cross check. Internal practices vary considerably across banks depending on their size, business models, and how long they have had operations in Poland, which determines the amount of data available for calibrating their models.

Sensitivity tests

26. Sensitivity tests suggest the banking system can withstand single adverse shocks. The top-down stress tests were complemented with sensitivity tests modeled after those conducted by the NBP on a semiannual basis. These tests, performed by the NBP, included counterparty risk shocks, credit risk shocks, a sharp depreciation, housing price shocks and interest rate shocks. Equity price shocks were ruled out since banks are little affected by stock market developments. Table 7 describes the sensitivity tests carried out for the FSAP Update, comparing them with the regular NBP’s tests.

Table 7.

Poland: National Bank of Poland and FSAP Update Sensitivity Tests

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Source: NBP.

27. The results of the sensitivity tests validate the results of the solvency stress tests, suggesting that problems arising from the recession scenarios could be manageable. Under the most severe counterparty risk shock, a number of banks representing 14 percent of total assets in the system could breach minimum capital requirements (Figure 3). In the case of credit risk shocks, if one out of five performing loans becomes impaired, banks representing 30 percent of assets in the system would not meet the minimum CAR (Figure 4, left panel). Were LGDs to increase to 75 percent, banks with an asset share of 10 percent would breach the minimum CAR provided that neither collateral nor profits can be used to cover the losses (Figure 4, right panel). Market risk sensitivity tests had little impact on profits and losses and liquidity.

Figure 3.
Figure 3.

Poland: Counterparty Risk Shock

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: NBP.
Figure 4.
Figure 4.

Poland Credit Risk Shock

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: NBP.

IV. Liquidity Stress Tests

28. The central bank conducted a liquidity stress test. The test included the same twenty banks analyzed in the top-down stress tests. The test considered the simultaneous realization of several shocks as listed in Table 8 and their impact on the ratio of liquid assets to liquidity needs.

Table 8.

Poland: Liquidity Stress Test—Shocks and Impact Channels

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Source: NBP.

29. The results suggest the banking system is resilient to liquidity shocks though asset liquidation could put some pressure on secondary markets. The average weighted coverage of liquidity needs by liquid assets exceeded 100 percent, with just four banks experiencing liquidity shortages amounting to about PLN 29 billion. These banks controlled slightly more than 10 percent of the total assets in the system (Figure 5). In the liquidity stress test scenario, banks would be forced to liquidate PLN 36 billion of money bills and PLN 10½ billion of government bonds. Given that the average daily market turnover for government bonds is about PLN 30 billion, asset liquidation could lead to some turmoil in secondary markets.

Figure 5.
Figure 5.

Poland: Liquidity Stress Test Results

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: NBP.

30. The central bank conducts top-down contagion or domino-effect simulations on a semiannual basis. The simulations cover both commercial banks and cooperative banks and detailed data on interbank claims and liabilities, including the names of all counterparties to a bank. The simulation assumes the netting of mutual assets and liabilities, i.e., should a troubled bank fail to repay its debt to another bank, then the latter, in order to minimize its losses, will likewise fail to repay its debt to the troubled bank. The simulation accounts for all types of loans and interbank deposits, regardless of their maturity, with insolvency defined as the breaching a capital adequacy ratio of 4 percent. Only commercial banks are allowed to fail in the first round of defaults.

V. Interconnectedness Risk

31. The simulations indicate that interconnectedness risk is low with potential second round contagion effects affecting only small institutions. The latest simulation results, reported in the bank’s December 2012 FSR showed that there were three commercial banks that could trigger a domino effect in the system, with the second round of defaults comprising up to 14 commercial and cooperative banks. These institutions have a share of total assets in the banking system of less than 1¼ percent (Figure 6). Furthermore, the failure of one of the trigger banks did not affect the other trigger banks. The limited interconnectedness risk arises from small transactions in the interbank market as banks have become more concerned with counterparty risk in the aftermath of the global financial crisis of 2008. However, even before the global financial crisis 2008 usage of interbank market as a funding source was rather limited. This is partly due to lower costs of attracting clients deposits or intragroup funding from foreign parent entities.

Figure 6.
Figure 6.

Poland: Interconnectedness Risk—CAR Distribution Before and After the Failure of Trigger Banks

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: NBP.

A. Other Monitoring Tools

32. In addition to the regulatory stress tests conducted by the central bank and the supervisor, the BFG has developed an early warning system (EWS). This system is designed with a view to detect stress in individual institutions early to anticipate preparation for payout. The system adopts a multidimensional approach, designed to take advantage of a granular and flexible database. It then combines the indicators from the database by applying a unique methodology that draws on reliability theory. However, more back-testing is required to reduce the risk of type II errors and enhance the credibility of the model in preparing for payout.

VI. Conclusion and Recommendations

33. The domestic banking system is well capitalized, contributing to its resilience to large credit, liquidity, and market shocks. Currently, capital levels at banks are well above those required by Basel III and capital is of high quality, reflecting the conservative stance of the KNF. Regulatory guidelines limiting dividend repayments have contributed to the substantial accumulation of capital buffers. Notwithstanding the ample capital base, banks enjoy high return on equity (ROE) and return on assets (ROA), partly owing to the strong growth of the Polish economy in recent years and the low level of bank penetration relative to other countries in the region.

34. Stress tests, including those regularly conducted for supervisory purposes and in the context of the FSAP update, reflect banks’ strong capital base. Adverse scenarios would affect mainly small banks accounting for a limited share of assets in the system. Given the low level of interconnectedness in the system, second round defaults would be limited even in the remote event that a large bank defaults. Liquidity buffers appear adequate against the shocks but their realization and the ensuing sale of liquid assets could lead to volatility and downward price pressure on government securities markets.

35. The FSAP team considers that there are natural synergies arising from the stress tests and the EWS. Each system has advantages that can complement the other two. The authorities could develop a clearer understanding of the risks in the banking sector by enhancing cooperation and information sharing between the departments in each agency responsible for stress testing. Since the information from bottom-up stress tests is complemented with on-site supervision information, the KNF could examine whether it is appropriate to conduct on-site inspections more frequently.

Appendix I. Stress Test Matrix: Solvency Risk 1/

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Appendix II. Stress Test Matrix: Liquidity Risk1/

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Annex. Top-Down Market-Based Stress Test

36. The FSAP team conducted a top-down market-based stress test to complement its own balance sheet top-down stress test and that performed by the NBP. The market-based test used as data input market estimates of the default risk of Polish banks to obtain implied changes of their capital-asset ratio under the macroeconomic scenarios.

37. The results suggest some banks could face substantial declines in their capital-asset ratios. Furthermore, the default of a few institutions cannot be ruled out under the adverse scenarios. The problems, however, are concentrated among smaller institutions and the high capital adequacy ratios in the system suggest that despite large declines, capital adequacy ratios could remain above regulatory minimum levels. The methodology and results are described in detail below.

Methodology

38. Market-based top-down stress tests can complement standard stress tests. The latter build on detailed and granular information on the sources of income of a bank, and its loan and trading books. In contrast, market-based tests use market information on the default risk of a bank to assess the impact of different stress scenarios on the bank’s capital base. These types of tests factor in market participants’ views on the soundness of a bank. Since banks are vulnerable to self-fulfilling runs, which need not be triggered by weak fundamentals but rather by market perceptions, the use of market-based stress tests is desirable. The methodology is explained concisely in the next section.

Linking the probability of default to the capital structure of the bank

39. The starting point for the analysis is the link between the probability of default of a bank and its capital structure (Merton, 1974). Specifically, the probability of default of a bank, p, over a time horizon T, is related to the capital structure of the firm by:

( 1 ) p = Φ ⁢ ( − ln ( V / D ) + ( μ − σ 2 ⁢ T / 2 ) σ ⁢ T ) ,

where V/D is the inverse of the debt-to-asset ratio of the bank, μ and σ are the growth rate and volatility of the asset value of the bank, respectively. Therefore, if the probability of default is known, the debt to asset ratio can be calculated from equation (1) assuming reasonable estimates for the growth rate and the volatility of the asset value of the firm. Once the debt to asset ratio is known, the capital to asset ratio, K/V, follows simply from:

(2)K/V=1−D/V⁢.

As explained in Chan-Lau (2013) among others, there are several ways to obtain probabilities of default from different financial instruments.

Linking changes in the capital structure to stress scenarios

40. The capital structure analogy suggests how to evaluate the impact of stress scenarios on the capital to asset ratio of a bank. Basically, equations (1) and (2) suggest that it suffices to specify a model linking the probability of default of the bank to one or more of the economic variables, X, and market risk factors, M, specified in the stress scenario:

( 3 ) p t = F ⁢ ( X t , M t ) ⁢ .

Given the paths of the economic and market risk factors in a stress scenario, equation (3) determines the dynamics of the probability of default, and equation (1) and (2) determine the dynamics of the capital-asset ratio. The next section applies the methodology to evaluate the performance of Polish banks under different macro stress test scenarios.

Numerical implementation and results

41. Market-based top-down stress tests were conducted for several Polish banks. For each bank, the probability of default over a one-year horizon corresponded to the one-year Expected Default Frequency (EDF) calculated by Moody’s Analytics. The EDF is the real-world probability of default obtained from a structural model conceptually similar to that of Merton (1974). The model combines observed equity prices, equity price volatility, and balance sheet data and is calibrated with historical default data (Bohn and Crosbie, 2003).

42. Simple nonlinear models were estimated to link the behavior of the EDF to year-on-year changes of real GDP. The sample data spanned the period 2006 Q3 to 2012 Q3 (Table 1 and Figure 1).8 For some banks, models were estimated using only data for the period 2010 Q3–2012 Q3. In addition, the fit of the models for two banks was somewhat counterintuitive for growth rates exceeding 7 percent. These growth values, however, did not realize in the stress scenarios.

Table 1.

Poland: Nonlinear Models for Banks’ EDFs as a Function of Year-on-Year Real GDP Changes

Three different models were fitted to link banks’ expected defaut frequencies to year-on-year regal GDP changes: (1) a one-term exponential model, y = aebx; (2) a rational polynomial, y = (ax+b)/(x+c); and (3) a second degree polynomial, y = ax2 + bx = c. The 95 percent confidence levels are shown within brackets.

article image
Source: Moody’s Analytics; and author’s calculations.
Figure 1.
Figure 1.

Poland: Fitted Nonlinear Models for Banks’ EDFs as a Function of Year-on-Year Real GDP Changes

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: Moody’s Analytics and author’s calculations.

43. Once the nonlinear models were estimated, it was possible to project changes in the capital-to-asset ratio under different macro scenarios. The scenarios are summarized in Table 2. The scenarios comprise a baseline (slow-growth) scenario, and three different recession scenarios.

Table 2.

Poland: Macro Scenarios, GDP Growth Year-on-Year

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Source: IMF staff estimates.

44. In general, banks experience a decline in their capital asset ratios in the first two years of the recession scenarios. The declines are reversed after the economy starts posting positive growth rates. Under the assumption that asset values remain flat or decline during the negative growth periods in the scenarios, the analysis shows that banks could suffer substantial capital losses ranging from 20 percent to 60 percent. In particular, it cannot be ruled out that certain banks could face recapitalization needs if the stress scenarios were to realize. As with any market-based model, some caution in interpreting the results is advised as secondary liquidity in the stock market could affect the reliability of equity-implied measures of default risk.

Figure 2.
Figure 2.

Poland: Changes in the Capital to Asset Ratio of Polish Banks under Different Macro Scenarios Relative to 2012Q3 Levels

(In percent)

Citation: IMF Staff Country Reports 2013, 261; 10.5089/9781484331163.002.A001

Source: Moody’s Analytics; and author’s calculations.

References

  • Bohn, Jeffrey, and Peter Crosbie, 2003, “Modeling Default Risk: Modeling Methodology,” Moody’s KMV.

  • Chan-Lau, Jorge A., 2013, Systemic Risk Assessment and Oversight (London: Risk Books).

  • Hamerle, Alfred, Rainer Jobst, Michael Knapp, and Matthias Lerner, 2008, “Stress-Testing Credit Value-at-Risk: A Multiyear Approach,” in Daniel Rosch and Harald Scheule, editors, Stress Testing for Financial Institutions: Applications, Regulations and Techniques (London: Risk Books).

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  • Merton, Robert C., 1974, “On the Pricing of Corporate Debt: the Risk Structure of Interest Rates,” Journal of Finance, Vol. 29, No. 2, pp. 449–70.

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    • Export Citation
1

This effect was partly offset by the decreasing interest rates, as in case of most mortgage loans the interest rate is calculated as a given market rate (e.g., LIBOR CHF 3M) plus a fixed margin expressed in percentage points.

2

The average annual real GDP growth rate in Poland between 2005 and 2011 was 4.5 percent.

3

At the request of the authorities, the note does not disclose the model details.

4

The aggregation method was chosen to parallel a bank-by-bank analysis. The reader should keep in mind that aggregation could potentially underestimate risks since the representative bank may not reflect the strengths and weaknesses of the constituent individual banks.

5

The results are consistent with the FSAP team market-based top-down stress test (see Annex).

6

The FSAP team discussed with the KNF the BU stress test methodology but did not scrutinize the individual bank results.

7

For instance, in the second scenario, interest rates are raised steeply to stem an outflow of capital.

8

The more sophisticated one-factor modeling approach of Hamerle, Jobst, Knapp, and Lerner (2008) was also used but it was not possible to fit the models to all the banks. The results for banks fitted with one-factor models were very similar to those reported here.

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Cover IMF Staff Country Reports
Republic of Poland: Technical Note on Stress Testing the Banking Sector
Author:
International Monetary Fund. Monetary and Capital Markets Department
Volume/Issue:
Volume 2013: Issue 261
Publisher:
International Monetary Fund
ISBN:
9781484331163
ISSN:
1934-7685
Pages:
34
DOI:
https://doi.org/10.5089/9781484331163.002
  • Figure 1.
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    Figure 1.

    Poland: National Bank of Poland Stress Testing Framework

  • Figure 2.
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    Figure 2.

    Poland: KNF Bottom-Up Stress Tests—CAR Distribution

  • Figure 3.
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    Figure 3.

    Poland: Counterparty Risk Shock

  • Figure 4.
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    Figure 4.

    Poland Credit Risk Shock

  • Figure 5.
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    Figure 5.

    Poland: Liquidity Stress Test Results

  • Figure 6.
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    Figure 6.

    Poland: Interconnectedness Risk—CAR Distribution Before and After the Failure of Trigger Banks

  • Figure 1.
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    Figure 1.

    Poland: Fitted Nonlinear Models for Banks’ EDFs as a Function of Year-on-Year Real GDP Changes

  • Figure 2.
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    Figure 2.

    Poland: Changes in the Capital to Asset Ratio of Polish Banks under Different Macro Scenarios Relative to 2012Q3 Levels

    (In percent)

Figure 1.

Poland: National Bank of Poland Stress Testing Framework
Figure 2.

Poland: KNF Bottom-Up Stress Tests—CAR Distribution
Figure 3.

Poland: Counterparty Risk Shock
Figure 4.

Poland Credit Risk Shock
Figure 5.

Poland: Liquidity Stress Test Results
Figure 6.

Poland: Interconnectedness Risk—CAR Distribution Before and After the Failure of Trigger Banks
Figure 1.

Poland: Fitted Nonlinear Models for Banks’ EDFs as a Function of Year-on-Year Real GDP Changes
Figure 2.

Poland: Changes in the Capital to Asset Ratio of Polish Banks under Different Macro Scenarios Relative to 2012Q3 Levels

(In percent)