The Effect of Basel IV on the Value of European Banks
ABSTRACT
In December 2017 the Basel IV framework was finalized, which introduced among
others a new risk sensitive framework for determining the credit risk of real estate
under the Standardized Approach (SA) and improved the Internal Rating-Based
Approach (IRB). This study aims to research the effect of Basel IV on the value of
European banks, by conducting an Event Study and a multiple regression. The Event
Study results found 10 out 12 significant abnormal returns, which the majority is
negative. The results of regression suggest that Mortgage and Global-Systematic
Important Banks (G-SIBs) are parameters for the abnormal returns. Mortgage has a
significant positive effect and G-SIBs an ambiguous effect.
negative.
Finding: found significant negative and positive abnormal returns, majority negative By conducting an event study
University of Amsterdam, Amsterdam Economics of Business, track Finance and Organization, BSc.
Name: Samira Habbani (10737030) Supervisor: I. Sakalauskaite
Statement of Originality
This document is written by Student Samira Habbani who declares to take full
responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that
no sources other than those mentioned in the text and its references have been used
in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of
completion of the work, not for the contents.
Table of Contents
1. Introduction………..…...4
2. Literature review...5
2.1 The theory of Bank regulation………..…...5
2.2 Capital regulation………...7 2.3 Basel Regulation……….…...9 2.4 Hypothesis………....17 3. Methodology………..18 4. Data………....22 5. Results………24 6. Conclusion……….28 7. References……….29 8. Appendix………...31
1. Introduction
Banks play an important role in the economy as they are the most important source of external finance (Mishkin, 2004). The economic importance can be derived from the purpose of a bank. Banks are financial intermediations that hold issued loans as assets and deposits as liabilities. They reduce the cost of asymmetric information by screening and selection the right borrowers. A research by King and Levine (1993) shows a strong positive relation of the degree of financial development and the GDP growth, concluding that the development of the financial sector plays a crucial role for the increase in the economy. Caldéron and Lui (2003) agree with King and Levine (1993), that in general a developed financial sector leads to economic growth but add that this relation exist in both ways.
The global financial crisis of 2007-2009 has shown the vulnerability of the financial sector, as well as the linkage between the financial sector and the real economy. The recent financial regulation did not prevent the financial crisis of happing. Therefore, after the crisis new financial regulations were introduced such as directives for Credit Risk Agencies and Insolvency. December 7th 2017 the Group of Central Bank Governors and Heads of Supervision (GHOS) of the Basel Committee, the international body that sets capital requirements, finalized a new framework for the exposure of credit risk. Even though, the official name is Basel III: finalizing post-crisis reforms, bankers refer to it as Basel IV1. For the reason, that the changes under the new framework could lead to an increase of 10% till 15 % of the RWA, which leads to an increase of the minimum required assets (Neisen, 2017). Continuing that this effect will be significant for European banks, because of the characteristics of the European banking industry.
The purpose of this study is to research if Basel IV has an effect on the value of the European Banks.
The remainder of this paper is organized as follows. Chapter 2 reviews the literature. Chapter 3 the methodology is discussed. Chapter 4 the Data is provided. Chapter 5 the results are disused. Finally, in Chapter 6 the conclusion is found.
Chapter 2: Literature review
This chapter aims to provide a general view on the reasons behind the heavily regulated and highly leveraged banks and their focus on the relationship between capital and bank value. Also, it will provide an overview of the Basel Accords, focusing on the Risk Weighted asset and the Internal 2.1 The theory of Bank regulation
The banking sector is one of the heaviest regulated sectors because banks are important for the economic growth (Mishkin, 2004). There are several types of banking regulations such as capital requirement, deposit guarantees, lender of last resort and restrictions on asset holdings. This paper will focus on capital requirement which is linked to deposit guarantees. The next paragraph explains why banks are heavily regulated. To provide more insight into the dynamic of the banking sector, the other determinants of heavy bank regulation are also provided.
Traditional theory about bank regulations suggests that the financial sector is regulated for three purposes. Brunnemeier et al. (2009), p. 2 summed them up as follows:
‘(1.) to constrain the use of monopoly power and the prevention of serious distortions to competition and the maintenance of market integrity;
(2.) to protect the essential needs of ordinary people in cases where information is hard or costly to obtain, and mistakes could devastate welfare; and
(3.) where there are sufficient externalities that the social, and overall, costs of market failure exceed both the private costs of failure and the extra costs of regulation.’
Of which the second purpose helps explaining the existence of deposit guarantees and capital regulation. The position of banks as intermediary makes it possible that deposits are booked as liabilities, meaning that if a bank defaults, deposit holders lose their money. Deposit holders monitor the bank and punish banks that do not behave in their interest by redrawing their deposit. To avoid financial panics most governments, guarantee deposits to a certain amount if a bank goes bankrupt. Brunnemeier et al. (2009) argues that these deposit guarantees lead to moral hazard of
both bank and deposit holders, which could influence the risk valuation of banks. Due to the insurance, deposit holders do not have an incentive to monitor banks on their risk taking and therefore deposit holders do not punish banks that behave detriment in their interest. In other words, the existence of deposit guarantees makes banks dismiss bank-run risk which results of the engagement in risky investments.
Capital requirements exist to incentive banks to take investment decisions that are in line with the interest of deposit holders and to reduce moral hazard. Morrison and White (2005) explain that holding sufficient capital while taking an investment decision will mitigate the incentive to make an investment decision that is optimal for the equity holders but not for the deposit holders. The required amount of capital provides as a buffer and as collateral if banks engage in risky investments. If losses are made equity has to be redrawn before depositors hypothetically lose their money. In line with this reasoning, Dow (1996) states that regulation is needed because the liabilities of banks and liquidity creation is a public good and therefore regulation is needed as a warranty.
The other two purposes explain why the banking industry has large and/or significant important banks, how banks are linked and why the banking sector has regulation that focus on the macro-aspect of the sector.
Brunnemeier et al. (2009) explains that the first purpose does not hold in reality for the banking sector. They argue that bank regulation aims to strengthen banks in order to survive crises, which leads to a market of oligopolies. The market will exist of banks of significant size and importance, where small banks do exist but do not have significant market share. Intuitively, the competition within the banking sector will lead to bankruptcy for the weaker banks, which can lead to negative externalities financial crises, which regulators try to avoid. More about this in the explanation of purpose 3. Furthermore Brunnemeier et al. (2009) argues that these kinds of regulation, which create entry barriers, are the reason for the existence of banks that are too big and too important to fail. Those banks will be bailed-out because of their importance, which creates the problem of Moral Hazard. Hellmann, Murdock and Stiglitz (2000) argue that deregulation is also a determinant of the Moral Hard problem. They reason that deregulation increases competition, which means that profits are getting lower and undertaking risky investments is more desired than a safe investment.
While the first two reasons are micro prudential, the third reason focuses on the macro effect of banks. Banks differ from other industries because of the linkage between one and another. Whereas the fall of one competitor will on average have a positive effect on the competition in other sectors, this is not the case with banks. Due to the inter-banking and the international character of the industry, the fall of one bank can lead to insolvency of the other (Brunnemeier et al., 2009). On day-to-day basis, banks are confronted by liquidity inflows and outflows. To be able to meet their liabilities, they could keep reserves or borrow money from banks that have an excess of inflows. If a bank is in distress, other banks do not want to lend money to this distressed bank and will be more hesitant to lend out to other banks. Banks that are exposed to outflows do not have the possibility to meet their liabilities and will distress. For example, the fall of the Lehman Brothers led to financial instability and even to a global economic instability. Without faith in the banking sector deposit holders will withdraw their money, which leads to a decrease of liquidity. Gradually it will affect the economy as a whole. This is the reason why banks are bailed-out if they are large and/or of significant importance. Before this financial crisis in 2007-2009, prudential regulations focused mainly on the micro aspect of bank regulation, while after the crisis the macro aspect is taken into consideration as well.
All of the reasons above explain that due to the major influence that banks have on the economics, the banking sector is one of the heaviest regulated sectors. Banking regulation is needed to prevent moral hazard of banks, by decreasing the incentive to take risky investments that are not in line with the interest of deposit holders and to reduce the probability of bankruptcy, which can lead to a financial crisis.
2.2 Capital regulation
Regulation regarding capital requirements means that banks need to hold a certain percentage of capital. Modigliani and Miller (1958) argued that the capital structure does not have an effect on the firm value. However, this proposition has strong assumptions such as no taxes, no bankruptcy and no transaction costs. These strong assumptions will be relaxed later on, where the cost of bankruptcy and revenue of taxes are included in the calculating. Choosing the right capital structure is a trade-off between cheap debt and relative expensive equity. This tradeoff exists because of the ductility of debt interest and the increase of bankruptcy cost by increasing leverage.
The preference for debt or equity can vary within industries, when focusing on the banking industry, there are several other reasons why debt is preferred over equity.
First of all, the deposit insurance makes debt cheaper, because depositors do not bear the risk of default and therefore, this risk is not adjusted in the interest price, even though banks are still exposed to this risk. Secondly, in general a bank that is significant in size or/and of significant importance is bailed-out to prevent a systematic crisis (Brunnemeier et al., 2009). This means that bankruptcy costs are reduced, which makes debt more desirable than equity. Thirdly, the asymmetric information between investors and the management makes debt more preferable (Myers & Majluf,1984). Investors do not have insights over the value. Assuming the management is rational, the shares will only be sold if they are equal or higher than true value. For this reason, the Lemons problem occurs, which means that only low valued banks will issue their shares. As a result, debt is preferred over equity for raising capital. Lastly, holding capital means that this amount cannot be used to create liquidity. Diamond and Rajan (2001) argue that holding equity is a tradeoff between liquidity creation and financial distress. Stating that some equity is hold helps prevent financial distress, however at the same time this decreases the ability of creating liquidity. In addition, Berger and Bouwman (2009) created a measure to compare liquidity creation of banks in the US from 1993 to 2003. They conclude that liquidity creation and bank value are positive correlated. Hanson et al. (2011) add that liquidity creation for large banks is more important due to the competition between large banks, where an increase in equity could lead to a competitive disadvantage.
The cost of the implementation of capital regulation has a negative impact on the value of banks (Demirgüç-Kunt, Laeven and Levine 2004). Benston and Kaufman (1996) even argue that the margin cost of implementation of this kind of regulation does not exceed the margin safety that it adds to the banking system. Benston and Kaufman (1996) continues and state that the additional costs lead to an inefficient outcome for the banking system as a whole.
Even though, debt is in general preferred over equity, some theories exist about why it is not preferable that banks are high leveraged. The cost of distress is not limited to only banks, there are social cost attached to, see the third condition of Brunnemeier et al. (2009). Furthermore, holding capital helps to incentive banks to make less risky decisions, because of the existence of deposit insurance. Although, Berger and Bouwman (2009) found a positive correlation between
liquidity creation and bank value, they found out as well that capital and liquidity are correlated. This correlation is positive for large banks and negative for small banks.
2.3 Basel Regulation The Basel Committee2
The international body that sets capital requirements is the Basel Committee. The goal of the Basel Committee is establishing an international playing field regarding capital requirement, this aims to provide fair international competition between banks and at the same time helps the banks to be resilient to shock by holding sufficient capital. This Basel Committee consist now of 45 institutions from 28 jurisdictions, where the European Union counts for one third of the members. The oversight body of the BCBS is the Group of Governors and Heads of Supervision (GHOS), responsible controlling and approving major decisions of the Committee. The prudential legislation produced by the BCBS is soft law and therefore can only be enforced if endorsed by the members.
Basel I
The BCBS first act of prudential regulation is the Basel Capital Accord, later renamed Basel I, introduced in July 1988 and implemented end 1992. This is the first international regulator accord, that introduced regulations for banks, that even not members later on implemented for their banks. The main regulation of Basel I is the introduction of minimum capital requirement. This prudential regulation aims create an international level playing field and to strengthen the stability of the financial sector, Basel Committee (1988). This Minimum Capital Requirement is calculated in the following way:
!"#"$%$ '()%"*(+ ,-."/-0
'12 = 8% (1)
2 All general information in this article about the Basel Committee are found on the official website of the BIS: Basel Committee Charter (2016). Retrieved from https://www.bis.org/bcbs/charter.htm
Hence, the capital requirement needs to be 8% of the Risk-Weighted Assets (RWA). The RWA in Basel I was calculated in a quite straightforward way. By distinguishing 4 categorize of riskiness of holding a certain asset, with each their own weight, see table 1. The RWA is the cumulative of the assets’ worth times the weight that was determined.
Table 1: Credit risk weight
European Parliament 2016
Even though Basel I is simple and straightforward in usage, it is not always accurate in measuring the risk that banks are exposed to. Basel I lacks risk sensitivity. This because of the fact that within categorize risk varies, a flat risk-weights does not reflect those differences. Besides, this one-size-fits all approach does not take into account the different bank types and markets. Furthermore, Basel I only takes into consideration the credit risk and with doing so excluding market and operational risk.
Basel II
Basel II 3 was introduced by the BCBS in 1999, finalized in 2004 and almost fully implemented by all the members in 2008. This new regulation is based on Basel I and aims to improve the shortcomings of the first Accord, like the lack of risk sensitivity and the one-size-fits all approach, (Basel Committee,2004). Basel II is based on three pillars. The first named Minimum Capital Requirement, the second named Supervisory Review Process and the third one named Market Discipline. Below only Pillar one will be discussed.
Pillar 1 is named Minimum Capital Requirement and builds on the way Capital Requirement is calculated in Basel I, only aims to provide a more accurate representation of the actual risk of holding certain assets. Again, the Minimum Capital Requirement is calculated as in
3 Basel II: International Convergence of Capital Measurement and Capital Standards: A Revised Framework (2004). The main subjects where addressed in 2004, however the detailed final version came out in 2006 named: Basel II: International Convergence of Capital Measurement and Capital Standards: A Revised Framework
formula xx, only differs in the way the RWA is calculated. The RWA is the sum of credit, operational and market risk. This study will focus on the credit risk component and especially on the real estate exposure (most of the time mortgage). In the appendix the risk weights of corporate and bank exposure are provided. The risk weight of real estate is shown in table 2. Both the residential and commercial real estate are weighted with a flat risk under the SA. Basel II introduced the LTV ratio, where LTV ratio above 80% the risk weight increases from 35% to 80%. The Basel IV provides further elaborate on those two types of exposure and the LTV ratio. The next paragraph will provide an explanation what SA and IRBA are. The IRB weights are find on the right side of the table.
Table 2: real estate risk weight under SA and IRB
Latham & Wathing retrieved: https://www.lw.com/presentations/regulatory-capital-requirements-for-european-banks
In Basel II the Basel Committee introduced the Internal rating-based approach (IRB), to improve the risk sensitivity of the Basel framework and therefore provide a more accurate estimation of the credit risk a bank is expose to, (Basel 2004). Only banks that comply with the standards of the Basel Committee and national authorities are allowed to use IRB. All the members and users of the Basel Accords are required to use the Standardized Approach (SA) for calculating the RWA. In reality, only large banks use the IRB, because the setup and maintenance of the usage is costly (European Parliament, 2016). There are two ways of using the IRB, the Foundation and Advanced IRB. The F-IRB is more limited in calculation their own measurement to determine the risk weight that the A-IRB. The SA under Basel II reliance on the credit rates of credit rate agencies, which intend to improve the risk sensitivity for calculating credit risk.
reliance of credit rate agencies, to less focus on the macro aspect of the banking sector and the pro-cyclic of the of the capital requirement.
Basel III and Basel IV
The financial crisis has shown that the Basel II was not able to prevent a financial crisis. The Basel Committee proposed in 2010 a new Accord named: Basel III: A global regulatory
framework for more resilient banks and banking systems, (Basel Committee 2010). The Basel
Committee (2010) describes the aim of this Accord as followed:
‘reforms to strengthen global capital and liquidity rules with the goal of promoting a more
resilient banking sector. The objective of the reforms is to improve the banking sector’s ability to absorb shocks arising from financial and economic stress, whatever the source, thus reducing the risk of spillover from the financial sector to the real economy.’ (p.1)
Summarized, having sufficient capital will provide a buffer if times are bad. Compared to Basel I and II, Basel III does not only focus on micro regulation but also on the macro one. Which this Accord the Basel Committee increased the total minimum required capital from 8% to 10.5%. This total capital exists 4.5% of minimum common equity capital and must consist of 6% Tier 1 capital. Further, the Basel Committee compile a list of banks that are of global systemic importance (G-SIBs). These banks regulation are under stricter regulation.
However, the Basel Accord of 2010 did not change the credit risk framework. Only couple of years later (in December 2017) this framework is changed and is named: Basel III: Finalising
post-crisis reforms. The GHOS and the Basel Committee have approved this accord on December
the 7th ,2017 and will be fully implement in 2027. Nevertheless, the new credit risk framework substantial changes the way the RWA are calculated. As a result, banks refer to renamed it ‘Basel IV’, this name is now common if speaking about Basel III reforms. Below the changes regarding the standardized Approach and the Internal Rating-based Approach are discussed. The increase of the leverage ratio of G-SIB’s is not discussed, likewise the changes in the operational risk framework and CVA-risk framework are not discussed.
Enhance Standardized approach (SA)
The improved SA intents to give an accurate representation of the credit risk a bank is expose to and provide a framework that offers an alternative for the credit rates provided by credit rate agencies (CRA). RWA aims to reflect the credit risk a bank is exposed to. The RWA determines the amount of required capital a bank needs to hold, see formula (1). So, in which manner the RWA is calculated is of importance for determining the amount of minimum required capital. As mentioned before, there are two ways of calculating the RWA, either using the SA or the IRB approach. All the members and users of the Basel Accords are required to use the Standardized approach (SA) for calculating the RWA, only banks that meet the requirements of the Basel Committee and the national authorities can deviate by use internal ratings-based approaches (IRB). This section elaborates on the SA and focus on the real estate credit risk exposure. The next section will focus on the IRB approach.
There are two ways of assessing credit risk depending if national legislation allows the use of external credit rates. If the use of external credit rates is allowed the External Credit Risk Assessment Approach (ECRA) is used. If the use of external credit rates is prohibited the Standardized Credit Risk Assessment Approach (SCRA) is used. This SCRA is introduced to provide an alternative for the credit rates that CRA provide and thereby reduces the reliance’s on the CRA for determining the credit risk and still provide risk sensitivity, (Basel Committee, 2017). The credit risk weights of covered bonds, specialized landings, banks, retail and corporations are increases, which means that banks need to hold more capital. Furthermore, as mentioned in the previous before, the Committee provided SCRA to calculate the RWA. The overview of the risk weights of these categories are provided in the Appendix.
Regarding real estate credit exposure, Basel IV provides a more risk-sensitive approach comparing with Basel I and Basel II. Basel I flat risk weight of for real estate credit risk exposure (see table 1). Basel II uses a flat weight as well but decrease the risk weight from 50% to 35% for residential exposure (see table 2). Only, Basel II introduced the LTV ratio (see formula (2), where LTV above 80% the risk weight increases from 35% to 80%. Under Basel IV the LTV is used for the risk exposure of real estate. The LTV ratio is now the main component determine the credit risk. The result is that under Basel IV holding residential real estate is more expensive if the LTV ratio is higher than 80% or criteria are not met, but in case of Commercial real estate it seems that it became cheaper, 85%<100%, see table 3.
𝐿𝑇𝑉 𝑅𝑎𝑡𝑖𝑜 =?>( @-0%( <= />( .*<.(*/A2$<%#/ <= />( 0<-# (2)
the Basel Committee (2017) defines amount of the loan as followed: ‘includes the outstanding
loan amount and any undrawn committed amount of the mortgage loan’. The value of the property
is calculated based on the following way: ‘the valuation must be appraised independently using
prudently conservative valuation criteria’ p. 21. The Basel Committee made a distinction between
residential real estate4 risk weights and commercial real estate5 risk weights, where the residual real estate is valued less risky than the commercial one, see Table 3. It is worth mentioning, that the qualification of real estate under Basel IV now consist of six criterions instead of three under Basel II.6 Real estate credit risk is valued less risky than other risk exposures, because of the collateral. Which means if the borrower defaults the total loss is less than under not secured loans. Basel Committee aims to strengthen the qualification for real estate risk, so that the risk exposure matches the capital it must hold.
4The official definition of residential real estate of the Basel Committee is as followed: ‘residential real estate exposure is an exposure secured by an immovable property that has the nature of a dwelling and satisfies all applicable laws and regulations enabling the property to be occupied for housing purposes’, (Basel Committee, 2017, p. 21)
5 The official definition of commercial real estate of the Basel Committee is as followed: ’A commercial real estate exposure is an exposure secured by any immovable property that is not a residential real estate.’ Basel Committee, 2017, p.23.
6 Under Basel II the criterions are: finished property, legal enforceability and prudent value of property. Under Basel IV claim over the property, ability of borrower to repay and required documentation are added, (Basel Committee, 2017, p. 18/19)
Table 3: Real Estate Credit Risk Weights Under SA
Basel Committee, 2017
In Table 3 the most important changes of risk weights regarding real estate are summarized. The risk weights attached to the assets are based on the LTV ratio. In cases where the risk exposure is valued as an unsecured loan, the RW of counterparty is implied, this risk weight is 75% for individuals and 85% for all others. In Table 3 the residential and commercial real estate exposures are divided in three groups: the whole loan approach, the loan splitting approach and the case income-producing residential real estate (IPRRE).
If the exposure is qualifying as a residential/ commercial real estate risk in first instance the risk weight of the whole loan approach is applicable. Only, in certain circumstances the national legislation is granted the freedom to decide the weight for the first 55%(with a minimum RW of 20%) of the property value and the remaining amount of the loan must be weighted with the RW of counterparty. See BIS, 2017 paragraph 65 for detailed explanation. The RW for IPRRE is used if the repayment depends on the cash flow that the property produces, like rent or lease.
Internal ratings-based approaches for credit risk
The IRB was implemented by the Basel Committee to provide a more risk sensitive approach of the credit risk. As mentioned in the part that explains Basel II, only banks that comply with the standards of the Basel Committee and national authorities are allowed to use IRB. The IRB approach however is seen as the reason for the variance between banks RWA, what underlies the function of comparability.7 For his reason the Basel Committee tries to diminish this variance by
restraining the use of IRB approach, provide a minimum input floors and output floors.
The constraints of using IRB approach is best seen in the appendix. In appendix xxx is seen that the credit risk is divided in four categories, were the use of A-IRB approach, which allows banks to have more freedom for estimating the component that are used to calculate the credit risk exposure, is most of the time replaced for the F-IRB approach, which limits the freedom for banks for estimating the credit risk exposure. Only for calculating the specialized lending the use of A-IRB approach is allowed. For estimating the equity exposure, the use of A-IRB approach is eliminated.
Next, the Basel Committee provides minimum input floors and output floor. This should decrease the variance between banks’ RWA and provides a fair level of playing field between banks that use the SA approach and banks that use IRB approach. The minimum input floor is presented in appendix XXY, which grant different input floors for the use of A-IRB approach and F-IRB approach, this is also the case for mortgages which means that there will be banks that need to increase the risk weight. The eventual output floor set by the Basel Committee is 72.5%, which means that the RWA calculated under the IRB approach must be at least 72.5% of the RWA calculated by the SA approach.
Characteristics of European Banking regarding real estate and IRB
First of all, there exist within countries of the Europe differences regarding legislation, macro environment etc. For this reason, credit risk of holding real estate varies between countries and therefore the variance of RWA can be justified. Furthermore, the mortgage market in Europe is significantly large, issued mortgages by banks are 23.1% of the total loans, also the average and
the average LTV ratio is 73%.8 European securitizations market is less developed compared to the USA, which means that holding real estate directly has effect on the RWA. Additionally, European banks tend to hold the loan till maturity.
2.4 Hypothesis
Under Basel IV the credit risk weights of covered bonds, specialized landings, banks, retail and corporations are increasing. The real estate credit risk is now more risk sensitive which means that regarding holding real estate the effect is ambiguous. European securitization market is not fully developed, hence holding real estate directly affects the RWA. Basel IV introduced input and output floors, as a result banks that use the IRB approach need to increase their minimum capital requirement particularly large banks (European Parliament, 2016). Debt is preferred over capital for many different reasons by banks. In the literature the effect of increasing the capital requirement is mostly assumed to have a negative effect on bank value. Diamond and Rajan (2001) argue that holding equity is a tradeoff between liquidity creation and financial distress. Demirgüç-Kunt, Laeven and Levine (2004) state that the implementation cost of capital regulation will have a negative effect. Berger and Bouwman (2009) found a positive correlation between liquidity creation and bank value. Which means that holding more capital will decrease bank value, however found out as well that capital and liquidity are correlated. This correlation is positive for large banks and negative for small banks. These findings suggest that bank value depends on size and other factors than only liquidity creation. All of this above leads to the following hypothesis: Basel IV will have a negative effect on bank value.
8Study on Internal Rating Based (IRB) model in Europe by the European Banking Federation, retrieved: http://www.ebf.eu/wp-content/uploads/2017/01/Study-on-Internal-Rating-Based-IRB-models-in-Europe-Website.pdf.
3. Methodology
To study the effect of Basel IV on the value of banks the Event Study methodology provides the tools to conduct this research. The underlying assumption is that the capital market is efficient or at least semi-strong efficient, which means that on average public information is fully aborted in the share prices. The Event study provides the possibility to statistically test if the announcement of Basel IV had an abnormal effect on the share prices of the European banks. Many researchers developed steps to conduct an Event Study, were Fama, Fisher, Jensen and Roll (1969) are seen as the founders. Bowman (1983) built further on their methodology and introduced 5 septs to carry out an Event Study, which later is reduced by De Jong (2007) to three steps. In this research, the methodology of De Jong is used. The steps are as followed:
1. Identify the event of interest and in particular the timing of the event. 2. Specify a ‘benchmark’ model for normal stock return behavior. 3. Calculate and analyze abnormal returns around the event data
Identify the Event of interest and in particular the timing of the Event
Identifying the exact date of the announcement of the Basel III post-crisis reforms announcement is not easy. the Basel Committee is working on the Basel III post crisis reforms since 2014, by proposing a different way of examining the credit risk standardized approach. On December 7th ,2017 an accord between the Basel Committee and the Group of Central Banks Governors and Heads of supervision (GHOS). In the period of 2014 till 2017 multiple announcement came about the process, only on the 7th of December they finalized the reforms and the implementation dates. Therefore, the announcement date for this event study is December 7th, 2017.
Specify a ‘benchmark’ model for normal stock return behavior
The benchmark is used to determine the normal return. The difference between the actual return and the normal return is called the abnormal return. In formula form where 𝐴𝑅"/ stands for abnormal return, 𝑅"/ stands for actual return and 𝑁𝑅"/ stands for normal return:
To calculate the abnormal returns first the estimation and event period need to be defined. De Jong (2007) summarized these periods in graph 1. T1 till T2 is the Estimation Period, also called the Estimation Window. This is a time period typically before t1 and can differ in size. For example, MacKinlay (1997) used an Estimation Window of 120 days, whereas Brown and Warner (1980) used on of 35-months. t=0 is the date of the event, so the public announcement date. t1 till t2 is the Event Period, also called the Event Window. De Jong (2007) suggests that the Event Window at least includes one day before and one day after the date of the announcement. MacKinlay (1997) however uses an Event Window of (0,1).
Graph 1 De Jong (2007)
To mitigate the chance that the 𝑁𝑅"/ will be biased the 𝑁𝑅"/ are calculated with the following formula:
𝑁𝑅"/ = 𝛼E" +𝛽G"*𝑅$/
𝑅$/ is a market index return and follows increases and decreases that effect the whole market. Comparing the market model returns (𝑁𝑅"/) with the actual returns (𝑅"/) of the Event Window,
the market adjusted abnormal returns (𝐴𝑅"/) are calculated as the prediction errors (𝜀"/) of the market model. The actual returns are calculated as followed:
𝑅"/ =𝛼" +𝛽"*𝑅$/ + 𝜀"/
The 𝛼E" and 𝛽G" are determined by OLS-regression with the data from the Estimation Window. This estimated 𝛼E" and 𝛽G" is used to calculate the normal returns within the Event Window.
Calculate abnormal returns around the event date
The abnormal returns are calculated as described in the paragraph above. To analyze these returns few steps are needed. The first one is calculating the Average Abnormal Return (𝐴𝐴𝑅" ). The average is reflecting the effect of the event, because all other information that are not correlated to the event will cancel out on average. The formula of the 𝐴𝐴𝑅" is as followed:
The second steps consist of calculating the cumulative abnormal return 𝐶𝐴𝑅". The 𝐶𝐴𝑅" shows the effect of the event on the returns from t1 till t2. This is done by accumulating the abnormal returns per individual bank for period t1 till t2, so over the cross-section. The formula is as followed:
Lastly, the cumulative average abnormal return (𝐶𝐴𝐴𝑅) is calculated to test the hypothesis.
Assuming that the abnormal returns are uncorrelated, testing is done with a simple t-test. The null hypothesis is: 𝐻M : E(𝐶𝐴𝑅") = 0. For the t-test the following formula is used:
The standard deviation of 𝐶𝐴𝑅" 𝑆,2'O. is calculated by:
𝑪𝑨𝑹𝒊 analysis
To analyze what effected the 𝑪𝑨𝑹𝒊 the following regression is conducted:
𝐶𝐴𝑅"/ = 𝛼 + 𝛽V𝑀𝑜𝑟𝑡𝑔𝑎𝑔𝑒 + 𝛽[𝐺𝑆𝐼𝐵𝑠 + 𝛽` Size + 𝛽a*ROE + 𝛽b𝑀𝐵 +𝛽c 𝑀𝑜𝑟𝑡𝑔𝑎𝑔𝑒 ∗ 𝐺𝑆𝐼𝐵𝑠 +𝜀
Mortgage in the regression is the natural logarithm of the total mortgage on the balance sheet. This variable is included because Basel IV real estate credit risk is changed under Basel IV. GSIBs is a dummy variable, 1 if the bank is a GSIB and 0 if not. Basel IV introduced an increase of the leverage ratio for G-SIBs, which means that GSIBs need to implement the new credit risk framework and increase their leverage ratio. For this reason, an interaction term is included. Size is the natural logarithm of the total assets. This variable is included because the change of the IRB approach will affect large banks the most (European Parliament,2016). The ROE (Return On Equity) and the MB (Market to Book Value) are control variables.
Chapter 4: Data
Data collection and Descriptive statistics
In this research 113 banks of European union are used for conducting the event study and 39 for the CAR analysis. All the data for this research is retrieved from DataStream. Using the daily returns from the 10/10/2016 till 10/10/2017 for the benchmark and 04-12-2017 till 10-12-2017 for the Event Window. For the market return the daily returns of the Stoxx Europe 600 are used. This dataset includes 25 countries for the Event Study and 17 countries for the CAR analysis. The CAR analyzes variables consist of data from the year 2016.
Graph 2 display the movements of the daily returns of the Event Window. In table 4 the Event Window and the corresponding dates are shown. The graph shows that there is a high variance between of the daily returns. The descriptive statistics are found in table 5. Table 6 provides the correlation matrix. There is a high correlation between mortgage and size. This could be explained by the fact that large banks hold in proportion more mortgage than a small bank. Also, a strong correlation exists between size and SIBs, which is logic because banks that are qualified as G-SIBs are either significant in size or/and importance. Likewise, ROE and the MB are high correlated.
Table 5 Descriptive statistics
Table 6 Correlation Matrix
EVENT -3 -2 -1 0 1 2 3 DATE 04-12-2017 05-12-2017 06-12-2017 07-12-2017 08-12-2017 09-12-2017 10-12-2017
5. Results
5.1 Event Study results
The hypothesis of this research is that Basel IV will have a negative effect on the value of European banks. Hence, this means that we expect that the announcement on December 7th, 2017 will generate negative abnormal returns. Following the methodology of De Jong (2007) the cumulative average abnormal returns (CAAR) are calculated to test the hypothesis. This research uses 12 Event Windows to determine if there are abnormal returns. The results of this study are found in table 7. All the abnormal returns are significant, except Event Window (-1,1) and Event Window (-2,2). The maximum abnormal return is 0.99% and minimum is -1.35%. According with the hypotheses we expect only negative abnormal returns. The majority of the abnormal returns are negative 7 out of 12. However, 5 out of 12 abnormal returns are positive.
The abnormal returns of the Event Windows before the announcement are negatively significant, where the abnormal returns on and after the announcement are positively significant, except for Event Window (2,3). This could suggest that the market expected the announcement of Basel IV or that there exists inside trading. The meetings between the Basel Committee and the Group Central Governors are public information, so this could be the case. The positive significant abnormal on and after the announcement could suggest that the Basel IV turned out better than the market expected.
Basel IV will most likely will increases the capital requirements of banks. Diamond and Rajan (2001) and Demirgüç-Kunt, Laeven and Levine (2004) explain that holding more capital will decrease bank value. Diamond and Rajan (2001) argue that holding capital will limit the liquidity creation and make banks less profitable. They state that holding equity is a tradeoff between liquidity creation and financial distress. Demirgüç-Kunt, Laeven and Levine (2004) suggest that implementation of capital regulation has a negative impact on the value of banks. This could explain the negative abnormal returns. The positive abnormal returns can be explained by the goal of the Basel Committee to strengthen global capital rules to promote a more resilient banking sector. It is possible that the faith in the banking sector increased. Also, the credit risk sensitivity of real estate improved, which means that for banks that hold real estate with low LTV ratio the capital requirement will decrease.
Table 7 The Cumulative Average Abnormal Returns (CAAR)
n=113 significant level two-sided test: 1%*** 5%** 10%***
5.2 Regression Results
In the previous paragraph the Event Study provided 10 out 12 significant results. To examine which parameters contributed to this significant result a multiple regression is conducted. Due to the limited space this study will focus on two cumulative abnormal returns (CAR). These Event Windows are (-3,3) and (0,1). Event Window (-3,3) is chosen because it is the longest Event Window. Event Window (0,1) is chosen because MacKinlay (1997) used the same Window. The following regression is conducted:
𝐶𝐴𝑅"/ = 𝛼 + 𝛽V𝑀𝑜𝑟𝑡𝑔𝑎𝑔𝑒 + 𝛽[𝐺𝑆𝐼𝐵𝑠 + 𝛽` Size + 𝛽a*ROE + 𝛽b𝑀𝐵 +𝛽c 𝑀𝑜𝑟𝑡𝑔𝑎𝑔𝑒 ∗ 𝐺𝑆𝐼𝐵𝑠 +𝜀
In Table 8 and Table 9 the results of the multiple regression are provided. There are four regressions conducted. Regression 1 includes Mortgage, Regression 2 includes Mortgage and
G-(-3,0) (-3,2) (-2,-1) (-1,0) (0,0) (0,1) -0.0135*** -0.0088*** -0.0126*** -0.0047** 0.0033** 0.0099*** (0.0036) (0.0030) (0.0018) (0.0021) (0.0017) (0.0019) (0,3) (1,2) (2,3) (-1,1) (-2,2) (-3,-3) 0.0063*** 0.0081*** -0.0036** 0.0019 -0.0012 -0.0105*** (0.0026) (0.0021) (0.0022) (0.0020) (0.0024) (0.0041)
SIBs, Regression 3, with Mortgage G-BISs, Size, ROE and MB and last Regression 4, with all the variables. In Regression 4 an interaction term is included between Mortgage and G-SIBs.
First, the CAR of Event Window (-3,3) is analyzed. The first three regressions do not provide any significant results. Only in Regression 4 significant results are found with a significance level of 5%. There exists a positive relation between G-SIBs and CAR. G-SIBs is a dummy variable, which takes the value 1if the bank is a G-SIBs and 0 if not. This result means that by being a G-SIB the CAR is higher than of not being a G-SIB. The interaction term between Mortgage and G-SIBs is negative significant. Which indicates that being a G-SIB and the Mortgage increases with 1%, the CAR will decrease by 1.55%, ceteris paribus. However, the total interaction effect is the sum of the coefficient of Mortgage, G-SIBs and the interaction term. Which exist of a negative and a positive component. The fact that the 𝑅[ is not even 1% does imply that the performance of this model is poor.
That the interaction effect is negative could be explained by the increase of the liquidity ratio for G-SIBs and the new SA method of calculating the risk exposure of real estate under Basel IV. It is likely, that both changes will affect the G-SIBs. Even though, mortgage could have positive or negative effect (depending on the LTV ratio of the issued loan) the cost of implementation of the new regulation decreases the value of the banks (Demirgüç-Kunt, Laeven and Levine, 2004). The implementation costs for G-SIBs that do not use IRB could explain the negative relation.
In Table 9 the CAR results of Event Window (0,1) is displayed. Mortgage is in both Regression 1 and Regression 2 positively significant for 1%. If mortgage increase with 1% this effect the CAR by 0.35% under Regression 1 and 0.40% under Regression 2. The G-SIBs is significant negative in regression 3. Which means that compared with not being a G-SIB, by being a G-SIB the CAR decreases. Likewise, in regression CAR Event Window (-3,3) the 𝑅[ is low, it improves but is not even low, which imply a poor performance of this model.
The effect of the weights of the credit risk of real estate could lead to an increase or decrease on the RWA. This because per European country the risk of holding real estate difference. The SA of the real estate risk is now more sensitive. The positive relation between mortgage and CAR could imply that the risk sensitive framework of Basel IV for real estate increases the value of European Banks.
6. Conclusion
Due to the major influence banks have on the economics, the banking sector is one of the heaviest regulated sectors. Banking regulation is needed to prevent moral hazard of banks, by decreasing the incentive to take risky investments that are not in line with the interest of deposit holders and to reduce the probability of bankruptcy, which can lead to a financial crisis. Banks preference debt over equity because deposit insurance makes debt cheaper, bail-outs of banks decreases the bankruptcy costs, the asymmetric problem between investors and management and holding capital decrease liquidity reaction. As result of this preference, capital requirements for banks are set. The international body that sets capital requirements is the Basel Committee. In December 2017 Basel IV (official name Basel III reforms) was finalized. Basel IV enhances the Standardized approach (SA) and reduces the use of Internal-Rating Based (IRB) approach. For real estate, this means that the credit risk is more sensitive compared to the flat risk weights of Basel I and II. The uses of the internal is restricted under Basel IV and introduced input floor and the increase of the output floors tries to mitigate the difference under the SA and IRB. Due to the fact, that the mortgage market is of significant size in Europe, the purpose of this paper is to analyze if Basel IV has an effect on the Bank value of the European banks. The method used to find an answer is an Event Study and a multiple regression. The Event Study results found 10 out 12 significant abnormal returns, from which the majority is negative. The results of the regression suggest that Mortgage and Global-Systematic Important Banks (G-SIBs) are parameters for the abnormal returns. Mortgage has a significant positive effect and G-SIBs an ambiguous effect.
The lack of Data excess is a limitation of this study. The increase of observation could provide better insides on all the parameters that effect the cumulative abnormal returns. Furthermore, this research took place in a short period of time after the implementation of Basel IV and therefore the term effects cannot be studied. Further research could analyze the long-term effect of the changes of Basel IV.
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