This chapter introduces the reader to key concepts such as stress test, credit ratings and bank capitalization. Moreover, I present previous findings on the CR-CS relationship and introduce concepts such as the Basel framework, the trade-off theory and the CR-CS hypothesis which will serve as a framework for further analysis and interpretation of the results
The stress test is a tool implemented by the European and American regulators to assess and address the solvency conditions of the financial systems in adverse unexpected outcomes (Basel Committee on Banking Supervision, 2009; Acharya, Engle, & Pierret, 2014). After the financial crisis in 2008 the aim of the test became to strengthen banks and supervisory practices and to prevent financial distresses to spread in the economy (Acharya et al., 2014). The stress tests provide forward looking information on risk assessment and how much capital banks are required to hold in order to be able to cover losses if large economic shocks occur. The stress test provides results based on two different scenarios, namely baseline and adverse scenario. The baseline scenario considers situations in which banks perform in a favourable economic situation with a relatively moderate economic growth. The stress tests usually focus on the adverse macroeconomic scenario which occur when there are some deviations from the baseline (Acharya et al., 2014).
According to Greenlaw et al. (2012) and Acharya et al. (2014) the stress tests are not only macro but also micro prudential in nature because they focus on the wealth of individual banks. Generally, the stress tests are outcomes of macroeconomic scenarios defined by the European Central Bank presenting an overall assessment of the systematic risk in the financial system of the European Union.
The European Banking Authority (EBA) stress test exercise takes into consideration several risk dimensions.
- The credit risk is the one affecting both the profit and loss account (P&L) and the risk-weighted assets (RWA), because it is measured based on macroeconomic scenarios on default and loss parameters (ECB, 2014).
- The market risk which occurs from changes in the market prices (ECB, 2014).
Key stress test figures are the banks’ capital ratios and factors that influence them such as profit and loss figures and key capital position data. The purpose of the stress is to identify capital shortfalls and require recapitalization plans from those banks failing to meet the minimum capital requirements. Among the key stress test figures are:
- Common Equity Tier 1 Capital (CET1) – the capital that the bank has readily available in the beginning of the stress test and based on which are evaluated the baseline and adverse scenarios.
- Common Equity Tier 1 Ratio (CET1 ratio) – the funds bank has readily available expressed in terms of the total exposure.
- Total Risk Exposure – includes the total bank exposure such as cash and equities, which are subject to a certain risk. For example, the cash is perceived as less volatile and hence less risky than the equities. Referred also to as RWA in the EBA stress test, the total exposure is derived upon Basel II and covers credit, operation and market risk components (Acharya et al., 2014). The best way for assessing credit risk to bank’s exposure and assigning their corresponding risk weights is to use the CET1 ratio (BIS, 2014).
- Core Tier 1 Capital (CT1) – composed primarily of permanent shareholders’ equity (Alfriend, 1988; Acharya et al., 2014). The Core Tier 1 consists of CET1 capital and Additional Tier 1 capital (AT1), which can be contingent convertible bonds(CoCo-Bonds) or other non-redeemable and non-cumulative preferred stocks.
The Basel Committee on Banking Supervision, established in 1988, published a set of regulations which provide a strong base for the macro prudential stress tests when defining banks’ financial performance measures i.e. the capital ratios (Acharya et al., 2014). The new regulations would stabilize the international banking system by removing the source of competitive inequality raised by the different national capital requirements (BIS, 2015). Basel I established a minimum capital ratio of 8% of the RWA, however more advanced framework was needed in order to be able to address not only the credit risk but also risk arising from banks’ foreign market exposure, traded debt, equities, commodities and equities.
Basel II framework was introduced in 2004, almost six years after the first Committee proposal (BIS, 2015). One of the Basel framework’s prescriptions is the use of external credit ratings when banks are about to determine risk weights of exposures (BIS, 2014). However, despite the valuable credit rating assessments on banks credit risk exposure, it is apparent that a significant proportion of banks’ exposure remains unrated (BIS, 2014). Hence, it is needed an alternative solution to the external ratings for the risk diversification. Under Basel II, banks have two alternatives to determine the capital requirements for credit risk, namely standard approach and internal rating based approach. The former measures credit risk supported by external credit assessments, while the latter one allows banks to use their internal rating systems for credit risk (Joosen, 2016).
Basel III is a framework introduced in response to the financial crisis in 2008 which main idea is to strengthen banks’ capital basis, hence, improving the whole economy (BIS, 2010). According to this framework, a way to assure consistency in the liquidity risk supervision is to develop a set of monitoring tools used in the process of tracking banks’ liquidity risk exposures. It concentrates on the implementation of new quantitative and qualitative requirements concerning the liabilities side of the banks’ balance sheets (Joosen, 2016). Moreover, the Basel III is introduced in order to fill the gaps of the already existing frameworks and contribute to the overall financial stability by strengthening the regulatory capital framework, and it is expanding on Basel II three pillars (Basel Committee, 2010; Krug, Lengnick & Wohltmann, 2015). These new regulations promote enhanced quality and quantity of the capital base for banks and strengthened risk coverage of the capital framework.
Basel III minimum capital requirements are constantly increasing throughout the years. The minimum common equity ratio raised from 2% to 3.5% in 2013 and to 4% in 2014. The Core Tier 1 capital ratio also increased from 4% to 4.5% in 2013. The most recent thresholds of the Basel III capital requirements include even higher CET1 ratio equal to at least 4.5% of the RWA, Tier 1 Capital at least 6.0% of the RWA and Total Capital (Tier 1&2) of at least 8.0% of the RWA (Basel Committee, 2010). The EBA would be monitoring the impact of the Basel III capital requirements on samples of European banks since June 2011.
Slovik and Cournède (2011) found in their study that some banks in US, Japan and EU have already increased their capital ratios as a pre-crisis measure from the market pressure by the end of 2009. Hence, their recommendation is that Basel III capital requirements for Tier 1 should be reduced by the increase already obtained. Moreover, by 2019, on average, banks will increase their CET 1 by 3.7% and Tier 1 capital ratio by about 3.0% in order to meet the capital requirements
Banks capital serves two main purposes. Similarly, to any other business, the capital is an input to the production process and the capital investments should correspond to banks capital rate of return. Also, the capital is a tool used to attract deposit funds, which are essential part of the production process, and they provide insurance to depositors against a drop in banks assets (Mingo, 1975; Peltzman, 1970). The capital is viewed as a residual which is able to absorb losses (Dietrich & James, 1983). Bank regulators examine the riskiness of banks assets and banks capital capacity to overcome periods of declines without incurring losses for the depositors (Peltzman, 1970). Banks balance sheet can undergo changes depending on whether the asset portfolio is considered to be risky or capital inadequate, and hence, a bank can choose to hold more capital or less risky assets. Banks should also strive to achieve an appropriate balance between holding less risky portfolios and more adequate capital, which is also the main focus of the regulators in their examination activities. The better capitalized banks experience smaller decline in their equity value during periods of economic downturns (Demirgüç-Kunt, Detragiache & Merrouche, 2010). Moreover, with more capital banks would be able to absorb loses which reduces the possibility of a liquidity problem (Moody’s, 2016).
Banks equity capital accounts for about 10 percent of the total bank’s resources (Peltzman, 1970). However, the owners rarely use capital directly to buy assets, but instead they use it to attract deposits with which to purchase capital later. Moreover, the equity financing incentives are different in banks and nonfinancial firms primarily due to the deposit insurance, which transfers the risk from the depositor to the insurer (Dietrich & James, 1983).
Peltzman (1970) concludes that no significant evidence can support the statement that banks investment behaviour conforms to the regulatory standards. Dietrich and James (1983) also support the evidence that regulatory capital standards are not efficient. Mingo (1975), on other hand, contradicts other researchers that banks investments capital is not affected by regulators desires. His findings are that the lower the ratio of actual capital to desired capital is, the more likely bankers are to add capital over the next period, to satisfy regulators desires. The contradicting results might be raised from the assumption made by Peltzman that there is a linear regression between the capital investment and the regulator’s capital adequacy standards and because of the aggregated data he used in the analysis (Dietrich & James, 1983).
Dahl and Shrieves (1990) explain in their research how the capital standards influence the infusion of equity in commercial banks which builds on previous researches on how bank regulations affect the capital structures. Central issue concerns whether the capital structures arise from natural capital market forces or they result from the minimum capital adequacy standards imposed by regulators. Some changes in capital or capital ratios might be caused by factors which are only partially controllable such as modification of dividend policies or asset size. Hence, a heavy reliance on those ratios as a metric for bank capital adjustments and modification might lead to misleading interpretations. However, equity issue is important for the banks’ capital structures, outsiders, and regulators as a proof that banks are committed to improve their capital positions (Dahl & Shrieves, 1990).
The equity infusion is positively correlated with growth rate, market concentration and location in urban market areas but only for the well capitalized banks (Dahl & Shrieves, 1990). However, better capitalized banks have higher probability to issue equity than lower capitalized banks. The infusion of equity has significantly larger proportion in the presence of regulation than it would have had in the absence. Hence, minimum capital requirements are to some extend impacting the bank’s equity issuance (Dahl & Shrieves, 1990).
Holding equity comes at a higher price for banks due to the information asymmetry, hence the equity capital is expected to be negatively correlated to the cost (Angora, et al., 2009). For example, under Basel II requirement banks are required to hold more capital if they are about to imply riskier plans or hold riskier assets (Angora, et al., 2009)
The credit ratings are not only examining the current financial performance and stability of the issuer, but they also incorporate forward looking expectations regarding the overall vulnerability of default of the issuer, industry and overall economy (Moody’s, 2006; Ueda & di Mauro, 2013). The most widespread category is the overall credit rating which assess the issuer’s ability to meet its financial obligations and cope during adverse business and economic crisis (Ueda & di Mauro, 2013).
Cantor and Packer (1996) explain the quantitative indicators taken into consideration in the credit rating determination such as per capita income, GDP growth, inflation, fiscal balance, external balance, and external debt. According to Hand, Holthausen and Leftwich (1992) the credit rating announcements by two of the big agencies S&P and Moody’s directly affect the corporate bond and stock prices.
The credit rating agencies list a number of economic, social and political factors which could possibly influence the credit rating. For example, the overall long-term ratings are lower after the crisis period in 2009 than they are before the crisis in 2007 (Ueda & di Mauro, 2013). For the investors, a potential downgrade would lead to losses, increased capital costs and restricted capital access for issuers which might result in default (Fons, Cantor & Mahoney, 2002). On other side, an upgrade is very favourable for the issuer, allowing for greater capital market access and interest cost savings, as well as enhanced security prices for the investor (Fons, Cantor & Mahoney, 2002). Credit ratings determine the creditworthiness of the issuers, which can also be expressed as the expected loss rate, which is a sum of the expected default rate and the loss-severity rates (Fons, Cantor & Mahoney, 2002).
Kisgen (2004) reveals that the credit rating agencies might have access to information besides the publicly available one, since they take advantage of the information asymmetries. Also, they might be provided with information that firms are reluctant to disclose publicly, therefore their creditworthiness assessments are considered as highly reliable.
The credit ratings usually represent not only the quality of the debt obligations but also the overall frim situation. Companies in the same rating category are often pooled together and all firms will be assessed similarly disregarding the extreme values (Kisgen, 2004). Hence, firms near a potential change in the rating will have more incentives to keep the higher grade and be pooled with highly rated companies
CR-CS hypothesis and Trade-off theory
Kisgen (2004) bases his paper on the Credit Rating Capital Structure hypothesis (CR-CS), which is built upon the belief that managers’ decisions on the capital structures are influenced by the credit rating announcements mainly due to costs and benefits associated with the differences in the ratings.
Those firms near a potential downgrade would issue less debt relative to equity than the ones which are not near a change in the rating or elsewise face the cost associated with a change in the rating (Kisgen, 2004).
The trade-off theory argues that the firm will balance its leverage ratio close the optimum (Kisgen, 2004). Applying that into the the CR-CS hypothesis have the implication that banks’ capital structures would change accordingly
The pecking order theory
The pecking order theory is quite similar to the trade- off theory and plays an important role in the capital structures decision making. Firms usually prefer not to issue equity because it is a costly source of funding, and instead search either for internal source of financing or debt (Frank Goyal, 2003; Kisgen, 2004). The equity has higher risk premium than debt and retained earnings, therefore investors would demand higher returns on equity. The standard pecking theory suggests that firms avoid issuing equity as a source for project financing but instead issue debt when the internal cash flows are scarce for the investment (Shyam -Sunder & Myers, 1999). Equity is issued in cases then there is a junk debt or the financial distress costs are extremely high.
Kisgen (2004) states that in contrast to the pecking theory, some firms near a credit rating upgrade might prefer to issue more equity than debt to avoid the corresponding risk, and likewise to avoid issuing debt when there is a foreseen downgrade
Ueda and di Mauro (2013) address the problem of the “too-systematically-important-to-fail” financial institutions which failure can be prevented through implementing tighter regulations or increased capital buffers. The authors are estimating the impact of the structural subsidy embedded in the credit ratings, since the ratings evaluate not only the institution’s own financial strength but also the external support it receives. They come to a conclusion that an increase in the government support impacts the overall long-term credit rating with an increase of up to 0.9 notches during the pre-crisis period. This impact nearly doubled in 2009. Moreover, the authors support previous findings that the credit ratings tend to overrate structural products.
One of the most important research papers in the field is written by Kisgen (2004), concluding that firms near positive rating change are more likely to adjust their capital structures in order to obtain the more favourable grade. Further investigations test different theories which are influential factor in the capital structure decision making. The pecking and the trade-off theory provide strong evidences of why companies choose to keep certain leverage ratios and why issuing equity is not a preferable option.
Greenlaw, Kashyap, Schoenholtz and Shin (2012) suggest that in order to be able to overcome banks undercapitalization, EBA’s stress test recommendations should be provided in euro amounts instead of ratios, because in order to comply with the regulations requirements banks tend to reduce their asset base (Acharya, et al., (2014). The problem with using capital ratios is that the denominator is the risk-weighted assets and its disclosure can be limited or inconsistent across banks. Demirgüç-Kunt et al. (2010) contribute to the above findings by testing whether strong capital positions are associated with strong stock market performance. If the capital is measured by leverage ratio and not risk-adjusted ratio, then the relationship between the stock and capital will be significantly stronger, because the risk-adjusted capital ratios under the Basel requirements are usually subject to manipulation.
Acharya et al. (2014) conclude in their paper that the Basel risk standards do not provide any incentives for diversification, so firms build their entire portfolios on one asset category, ignoring the risk weights which results in excess leverage. As a consequence, banks’ exposures are built upon low-weighted risk assets. Moreover, stress tests cannot capture ex ante the increased risk unless there are market-based measures, thus stress tests relying only on Basel regulation are not sufficient.
Poon and Firth (2005) examine the trend of the credit agencies to grade banks that have not requested it with significantly lower ratings. They test several banks in terms of asset quality and profitability. Firm that did not request a rating are said to receive a “shadow” rating since the agencies base their decision entirely on publicly available information. The authors come to a conclusion that the shadow banks have lower asset quality and less equity capital to absorb the losses.
The credit rating agencies and existing literature lack reporting details on what impact the credit rating determination. Mellios and Paget-Blanc (2006) find that past upgrades do not prefigure future upgrades, whereas once start downgrading a particular company, the agencies tend to overreact which presumes future downgrades as well. Therefore, it is important to determine what influences the ratings and how banks can avoid future sequence of downgrades. The expected default frequencies incorporate equity market expectations and are used my Moody’s credit rating agency as a measure or risk (Hau, et al., 2012). The stock market reacts to changes in the ratings but so far there are no evidence on whether the imposed minimum capital requirements, and in particular equity holdings, are related to favorable credit ratings
1.1 Problem Discussion
1.3 Research Questions
2 Theoretical framework
2.1 Stress test
2.2 Basel framework
2.3 Bank capitalization
2.4 Credit ratings
2.5 Literature review
3.1 Choice of method
3.2 Data collection
3.3 Data analysis
3.4 Research Quality
3.4.1 Research validity and replicability
4 Empirical findings
4.1 Excess equity to balance sheet
4.2 Assumption checking – Multivariate ordinal regression
4.3 Multivariate ordinal regression
4.4 Multivariate ordinal regression results for 2011
4.5 Multivariate ordinal regression results for 2014
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