The influence of an official interest rate
change on the stock returns of banks
University of Groningen
Faculty of Economics and Business
MScBA Finance
8
thJuly 2009
Gert-Jan Veerman Student number: 1406507
TABLE OF CONTENTS 1. Introduction 3 2. Data 9 3. Methodology 14 4. Results 19 5. Conclusion 25 6. References 28 Appendix A 30 Appendix B 31 ABSTRACT
In this paper the effect of an official interest rate change on the stock return of banks is studied. An event study is used to study every interest rate change, 85 in total between 2001 and 2008. The stock returns of 491 listed banks, divided over the Euro zone, the UK and the USA, is used. According to findings, the Euro zone gives the most significant results. An official interest rate cut gives negative abnormal returns and vice versa. There are also significant differences between types of banks, again mainly in the Euro zone.
Keywords: interest rate change, stock returns, banks, exposure, market risk
1. INTRODUCTION
Market interest rates are important factors for banks. Profit margins largely depend on market
interest rates since the margin is, for an important part, the difference between the received
and paid interest. Several studies have confirmed the importance of market interest rate risk
on the value of a bank (Yin et al., 2007, Akella and Greenbaum, 1992). Market interest rates
are partly determined by the official interest rate set by central banks. It is therefore possible
that interest rate changes made by central banks have an important influence on the value of a
bank. However, this is questionable.
The answer to this question is of interest to investors and traders. They can use this
information as a base for their decisions when trading. It can also be interesting for central
banks as this study can give them an insight in the reactions on their monetary policy
decisions. Lastly, this study can be beneficial for listed banks since they have a clearer picture
of how their value and thus stock price is influenced by an official interest rate change.
The research objective of this study is to find out whether or not changes in official interest
rates, set by central banks, have a an effect on the value of banks and therefore the stock price.
This study questions if there are abnormal returns present on and around the announcement
day of a change in official interest rates.
Stock markets, in general, react on changes in the official interest rate made by central banks.
This is mainly because of two reasons. The first reason is that changes in official interest rates
affect the discount factor of cash flows and therefore the stock price. The second reason is that
The extent of these reactions has also been studied. Bernanke and Kuttner (2005) find that, on
average, for every unanticipated cut of 25 basis points in the Federal funds rate target, the
broad stock indexes react with a value increase of 1%. However, this does not mean that the
market does not respond when the official interest rate cut is anticipated. Markets do respond
due to changes in expectations of future monetary policy. These expectations are based upon
changing economic conditions, which provide new information to the market.
All stocks are influenced to some extent by the changes in official interest rates. Banks
however can, arguably, be more influenced than other types of companies. Since the margins
of banks depend, for the majority, on the market interest rate, it is crucial to know how the
market interest rate reacts on the official interest rate set by the central bank. The reaction of
market interest rates change, according to De Bondt (2005), with the maturities of the market
interest rates. Short maturities have the tendency to adjust quicker than longer maturities.
There is also a difference in the adjustment of lending rates and deposit rates. Deposit rates
have the tendency to adjust quicker than lending rates. There are several factors which have
an influence on the time difference in the adjustment of different rates. The most important
factors are marginal pricing costs, bank exposure to interest rate risk, competition and
regulation in different segments of the deposit and credit market, the administrative cost of
effectively changing interest rates and lastly the degree of passive behaviour on the part of
deposit holders and borrowers.
Wright et al. (1996) give three reasons why banks might react stronger on average to an
interest rate change. The first and arguably most important reason is that there is a mismatch
general, a bank borrows for the short term to fund the long term. For example, a bank collects
savings, which have a short term maturity, to lend out mortgages, which have a long term
maturity.
The second reason is that there is not a one-on-one translation from the changes in official
interest rates made by central banks to an adjustment in the interest rate asked and paid by the
bank. This means that differences can occur in the adjustment of the interest rates earned and
paid. This obviously influences present and future cash flows and therefore the value and the
stock price of the bank.
The third reason is the presence of options in many bank assets, liabilities and
off-balance-sheet items. One of these options is, for instance, the right of depositors to withdraw their
money without a penalty. Official interest rate changes can have an influence on this decision
and therefore the financial position of the bank. This changes the bank’s cash flows and
therefore the stock price.
However, from a different persective, changes in the official interest rate are made by the
central bank to influence the macroeconomic climate. They use the interest instrument for
stimulating and slowing down the economy. The main reason for this action is to hold
inflation stable. As the reason for a change in the official interest rate is purely
macroeconomic, it is possible that banks do not show any abnormal returns when the official
interest rate is changed.
The final possible outcome is that banks show negative abnormal returns when the official
increased. Signaling is the reason for this effect. According to Anker and Wasmund (2005) an
official interest rate change gives a signal about the future money market. A cut in the interest
rate gives the signal of a deteriorating money market in the future which influences the banks
and their stock prices. It can also be a signal for an economic situation that is better or worse
than expected. This is confirmed by Bernanke and Kuttner (2005) who state that an official
interest rate change may be driven by a changing economic environment.
The above reasoning leads to the following hypothesis.
Hypothesis 1
H0: Stock returns of banks show no abnormal returns at the announcement of an interest rate change.
H1: Stock returns of banks show abnormal returns at the announcement of an interest rate change.
The majority of studies regarding both official and market interest rates and banks’ stock
returns are focused on commercial banks (Ghazanfari et al., 2007, Wright et al., 1996,
Wetmore 2003, Kwan 1991, Harun et al., 2008, Booth and Officer 1985). However, there are
also different types of banks on the stock market. These other banks might react differently
from commercial banks. Unfortunately, there is little literature present on these possible
differences between different types of banks. It is plausible that there are differences between
types of banks. For example, real estate and mortgage banks have much more market interest
rate risk than investment banks. Since the exposure differs considerably amongst banks, stock
The study of Wright et al. (1996) makes a distinction between different financial institutions.
The comparison made is between commercial banks and thrift institutions. Thrift institutions
are associations that encourage personal savings and home buying. These institutions are
specialized in accepting savings deposits and mortgage lending. The market interest rate risk
exposure of these thrift institutions is significantly higher than commercial banks. Having a
large portfolio of mortgages is stated as the reason for this higher exposure.
Another reason for the differences between banks is that central banks force remaining banks
to be dependent upon them. The European Central Bank (ECB), for example, has set the
minimum reserve requirements at 2%. This implies that European banks have to put, on
monthly average, 2% of their short-term balance sheet items (e.g. deposits with maturity up to
two years) on an account at the central bank. Monthly average is explained by the following
situation; a bank has, for example, 0% on their account for the first two weeks. In order to
average 2% in that month the bank then has to transfer 4% of the value of their short-term
balance sheet items on the account for the last two weeks. The account now shows a monthly
average of 2%. The system is constructed in such a way that a number of banks do not have
the money to fulfill the minimum reserve requirement. They can get money from the ECB. At
the weekly main refinancing operation (MRO), banks can bid for the money that the ECB
allots. This is how the ECB makes banks dependent on them. If the ECB lowers its official
interest rate, it means that it lowers its minimum bid rate. It therefore becomes cheaper for
banks to meet their minimum reserve requirement (ECB, 2002).
As can be expected from the above, different types of banks have different exposures to the
minimum reserve requirement. For example, a savings bank has more exposure than an
the ECB. This is because a savings bank has more short-term balance sheet items than an
investment bank and therefore has to deposit more money on their account at the ECB to
fulfill the minimum reserve requirement.
In contrast, an interest rate change is made for the long term. Empirical evidence states that
the effect of a change in interest rate can be seen after 1.5 to 2 years (ECB, 2004). Therefore it
is possible that there are no differences in abnormal returns between types of banks since the
effects of the interest rate change are not visible and not certain for a long period of time.
Hypothesis 2
H0: There are no differences in abnormal returns between different types of banks.
H1: There are differences in abnormal returns between different types of banks.
This paper continues in the next section, section 2, with a data description. The third section
explains the methodology used in this study. Section 4 gives the results and section 5 will
draw conclusions from these results, followed by the reference section. This paper also has
2. DATA
We need different types of data in order to test the hypotheses. The first type of data is the
official interest rate changes, which are made by the central banks. We use three central
banks: the European Central Bank (ECB), the Bank of England (BoE) and the Federal
Reserve (FED). When we talk about the official interest rate, we mean the Minimum Bid Rate
of the ECB, The Official Bank of England rate from the BoE and the Federal Funds Rate for
the Fed. The second type of data is the stock returns of the banks used in this study, together
with their type. We use data starting from 2001.
Interest Rate Cuts
The three central banks lowered their interest rates 49 times in total between the 1st of January
2001 and 31st of December 2008. The total amount of official interest rate cut events in this
study is 49. The ECB lowered their interest rates 10 times. In 3 cases they lowered with 25
basis points (bps), in 6 cases with 50 bps and in 1 case with 75 bps. The BoE lowered their
interest rates 16 times. In 12 cases they lowered with 25 bps, in 2 cases with 50 bps and in 1
case with 100 and 150 bps. The FED lowered their interest rates 23 times. In 7 times they
lowered with 25 bps, in 13 times 50 bps and in 3 times with 75 bps.
Table 1
Summary statistic of the interest rate cuts in %
The sample used contains the banks that are qualified as large banks by Bankscope and that
were listed on the 31st of December 2008. The total number of banks used for every interest
rate cut is shown in table 2.
Table 2
Number of stocks used for every interest rate cut. The interest rate cut number corresponds with the date of the interest rate cut which can be found in appendix A.
Interest rate cut Euro zone UK USA 1 107 16 305 2 109 16 306 3 109 16 306 4 111 16 307 5 116 16 307 6 116 16 307 7 116 16 309 8 130 17 309 9 130 17 309 10 131 17 310 11 17 311 12 18 315 13 18 323 14 18 340 15 18 340 16 18 340 17 341 18 341 19 341 20 341 21 342 22 342 23 342 Total 1175 270 7434
As can be seen in table 2, The Euro Zone has 1,175 observations, the UK 270 and the USA
7,434. This brings the total amount of observations used in the case of an interest rate cut to
8,879. The largest amount of different banks used in total is 491, distributed over the Euro
All the banks have one of the following specializations:
- Commercial Banks - Savings Banks - Cooperative Banks
- Real Estate & Mortgage Banks - Medium & Long Term Credit Banks - Investment Banks & Security Houses - Bank Holdings & Holding Companies
These specializations are the distinctions used in the Bankscope database program. The
differences are made by an analyst of Bureau van Dijk, which is the publisher of Bankscope.
The distinctions are based on the experience and opinion of the analyst and not on publicly
available criteria. The distribution of these specializations over the different geographical
areas is summarized in table 3.
Table 3
Number of different specializations during interest rate cuts, divided over the different geographical areas.
Specialization type Euro zone UK USA Total Commercial Banks 72 0 14 86 Savings Banks 2 0 0 2 Cooperative Banks 25 0 0 25 Real Estate & Mortgage Banks 3 0 4 7 Medium & Long Term Credit Banks 3 0 0 3 Investment Banks & Security Houses 6 9 10 25 Bank Holdings & Holding Companies 20 9 314 343 Total 131 18 342 491
Interest Rate Increases
A slightly smaller amount of increases have occurred. The total amount of increases starting
from the 1st of January 2001 is 36. Similar to the interest rate cuts, the ECB has the least
interest rate increases followed by the BoE and FED, which has the most. The ECB lowered
its interest rate 9 times, the BoE 10 times and the FED 17 times. A large difference with the
interest rate cuts is that the increases are always with 25 basis points. The total number of
observations in the different geographical areas. The total number of observations in the Euro
zone is 1,128, in the UK 170 and the USA 5,656. The distribution of the bank stocks over the
three geographical areas can be seen in table 4.
Table 4
Number of stocks used for every interest rate increase. The interest rate increase number corresponds with the date of the interest rate increase which can be found in appendix B.
Interest rate increase Euro zone UK USA 1 123 17 327 2 123 17 328 3 124 17 330 4 124 17 330 5 124 17 330 6 126 17 331 7 126 17 331 8 127 17 332 9 131 17 333 10 17 334 11 334 12 334 13 335 14 336 15 337 16 337 17 337 Total 1128 170 5656 Table 5
Number of different specializations during interest rate increases, divided over the different geographical areas.
In table 5 shows that there is a total of 485 banks used for the official interest rate increases.
This differs from the 491 which is used for the official interest rate cuts. The reason for this is
that the official interest rate increases partly occur in different years than the cuts. The amount
of banks listed on the stock market increased over the years and therefore it can happen that
3. METHODOLOGY
The first hypothesis was to test whether or not there were abnormal returns at the
announcement of an official interest rate change. In order to test for abnormal returns, they
have to be defined first. Abnormal returns can be defined as the difference between the
observed or actual returns and the expected returns. The expected returns can be modeled in
different ways. The three most frequently used models are the constant mean return model,
the market model and the Fama and French three factor model. This study uses the market
model.
The constant mean return model was not used as it generates poor outcomes in clustered
events, which is the case in this study. Brown and Warner (1980) state that the constant mean
return model performs very poorly in comparison with models, such as the market model,
which adjust for market performance and systematic risk.
MacKinlay (1997) states that using multi factor models in event studies do not generate better
outcomes than using the market model. This is due to the marginal explanatory power of the
additional factors. Data availability is often also a limiting factor. These are the reasons why
the Fama and French three factor model was not used.
Using the market model to calculate the expected return gives the following equation:
E 𝑅𝑖 = 𝛼𝑖 + 𝛽𝑖𝑅𝑚 (1)
Where E 𝑅𝑖 is the expected return of stock i, 𝛼𝑖 is a constant, 𝛽𝑖 is a coefficient and 𝑅𝑚 is
110 days before the announcement date of the interest rate change. The starting point is
marked with 𝜏0 and ends at 𝜏1, which is known as the estimation window.
The expected return can now be calculated, as well as the abnormal return. In order to
calculate the abnormal return, the expected return is deducted from the observed return.
This is shown in the following equation:
𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − 𝑎𝑖− 𝛽𝑖𝑅𝑚𝑡 (2)
Where 𝐴𝑅𝑖𝑡 is the abnormal return of stock i on time t, 𝑅𝑖𝑡 is the observed return of stock i on
time t, 𝑎𝑖 is the constant from equation (1) and 𝛽𝑖𝑅𝑚𝑡 is the coefficient from equation (1)
times the return of the market on time t. Time t is, in this context, the date the interest rate
change is announced.
Due to speculations or expectations it may be possible that the official interest rate change is
anticipated and the change is already priced in before the announcement date. Using
cumulative abnormal returns can make this visible. This is achieved by starting to check for
abnormal returns for a period starting 10 days before the announcement date until 10 days
after the announcement date. The start of the period is marked with 𝜏1 and the end of the
period is marked with 𝜏2. The abnormal returns between 𝜏1 and 𝜏2, calculated with equation
(2), are summed up to result in the cumulative abnormal return. The equation from the article
of MacKinlay (1997) makes this visible.
𝐶𝐴𝑅𝑖 𝜏1, 𝜏2 = 𝐴𝑅𝑖𝜏
𝜏2
𝜏=𝜏1
Where 𝐶𝐴𝑅𝑖 𝜏1, 𝜏2 is the cumulative abnormal return of stock i from either 10 or 5 days
before the announcement day until either 5 or 10 days after the announcement day and 𝐴𝑅𝑖𝜏 is
the abnormal returns from stock i in the time period between 𝜏1 and 𝜏2.
In order to test whether or not abnormal returns present, a t-test is used to check whether the
abnormal returns significantly differ from zero.
The second hypothesis in this study was to question whether there is a difference in abnormal
returns between types of banks. We use dummies for every type of bank and test with an
Ordinary Least Squared regression whether or not the coefficient of these dummies
significantly differ from zero. The coefficients show the extent of the reaction. A larger
coefficient means a heavier reaction. We also incorporate several control variables into the
regression to check if the results found can be addressed to other factors, such as leverage.
Table 6
Variables used in regression 4
Variable Description
COMDUM Dummy which takes the value of 1 if the bank is a commercial bank and 0 otherwise
SAVDUM Dummy which takes the value of 1 if the bank is a savings bank and 0 otherwise
COODUM Dummy which takes the value of 1 if the bank is a cooperative bank and 0 otherwise
REMDUM Dummy which takes the value of 1 if the bank is a real estate & mortgage bank and 0 otherwise
MLTCDUM Dummy which takes the value of 1 if the bank is a medium & long term credit bank and 0 otherwise
IBSHDUM Dummy which takes the value of 1 if the bank is an investment bank & security house and 0 otherwise
HOLDUM Dummy which takes the value of 1 if the bank is a bank holding or holding company and 0 otherwise
ETA Ratio computed by Equity/Total assets
NLTA Ratio computed by Net loans/Total assets
NLCSTF Ratio computed by Net loans/Customer & Short term funding
NLDB Ratio computed by Net loans/Deposits & Borrowings
CFTA Ratio computed by Capital funds/Total assets
CFNL Ratio computed by Capital funds/Net loans
CFDSTF Ratio computed by Capital funds/Deposits & Short term funding
The variables used in equation (4) are presented in table 6. The regression used is the
following:
𝐴𝑅𝑖 = 𝛽1𝐶𝑂𝑀𝐷𝑈𝑀 + 𝛽2𝑆𝐴𝑉𝐷𝑈𝑀 + 𝛽3𝐶𝑂𝑂𝐷𝑈𝑀 + 𝛽4𝑅𝐸𝑀𝐷𝑈𝑀 + 𝛽5𝑀𝐿𝑇𝐶𝐷𝑈𝑀 +
𝛽6𝐼𝐵𝑆𝐻𝐷𝑈𝑀 + 𝛽7𝐻𝑂𝐿𝐷𝑈𝑀 + 𝛽8𝐸𝑇𝐴 + 𝛽9𝑁𝐿𝑇𝐴 + 𝛽10𝑁𝐿𝐶𝑆𝑇𝐹 + 𝛽11𝑁𝐿𝐷𝐵 +
𝛽12𝐶𝐹𝑇𝐴 + 𝛽13𝐶𝐹𝑁𝐿 + 𝛽14𝐶𝐹𝐷𝑆𝑇𝐹 + 𝛽15𝐶𝐹𝐿 + 𝜀𝑖 (4)
Where 𝐴𝑅𝑖 is the abnormal return as constructed in equation (2) and 𝛽1 untill 𝛽15 are the
variables as described in table 6.
The ETA variable is to check if the capital structure of the bank is a significant factor in
determining the extent of the abnormal returns. CFTA, CFNL, CFDSTF and CFL are other
methods to measure leverage. Previous studies already confirmed the importance of leverage
on the pricing of a stock. Financial institutions are often omitted from a sample since they
have high leverage compared to other companies (Cooper et al., 2003). Since this study is
solely conducted on financial institutions, it might be interesting to see whether leverage is a
relevant factor in the stock return during an official interest rate change. It can be stated that a
higher level of leverage implies a higher level of risk (Brewer et al., 1996). This is in line with
Cantor and Johnson (1992) who state that an improvement in capital structure increases the
stock price since there are lower bankruptcy and agency costs. Cooper et al. (2003) find that,
amongst others, leverage is indeed a reliable variable to price the stock of a bank.
The NLTA, NLCSTF and NLDB variables indicate whether the bank in question is a net
borrower or a net placer and to which extent. Thus, does the bank borrows more than it places
their own activities. Banks who are net placers have excess money to lend out which makes
them more liquid. Being illiquid has potential costs. When a bank is not liquid enough and
deposit holders want their money, the bank has to sell assets under their value and therefore
making a loss. Being more liquid can prevent this (Diamond and Rajan, 2001). Banks with
higher liquidity have lower chances on bearing liquidity costs and therefore have a lower risk
4. RESULTS
This section discusses the obtained results following the research design from the methodology section. In order to check whether abnormal results were present, a t-test was used. The results are given in table 7.
Table 7
T-test results of interest rate cuts and increases on the announcement day and periods of 5 and 10 days before and after the announcement day. The test that is being conducted is a sample mean test with a mean of 0.
Announcement day -5/+5 -10/+10 Interest rate cut
Eurozone t-statistic -8.3268 *** -0.1484 -0.6349 Std. Dev. 0.0676 0.0444 0.0466 Mean -0.0163 -0.0002 -0.0009 UK t-statistic 0.5085 -1.3939 -1.6346 Std. Dev. 0.0633 0.0891 0.0518 Mean 0.0020 -0.0075 -0.0052 USA t-statistic -0.6432 -0.9182 -1.0571 Std. Dev. 0.1388 0.0825 0.1201 Mean -0.0103 -0.0009 -0.0015 Interest rate increases
For interest rate cuts the announcement day of the Euro zone is highly significant. The two
time periods are not. The UK shows no significant results and the announcement day shows
an inconsistent sign. The two time period with t-statistics of -1.3939 and -1.6346, are almost
significant and do show a consistent sign. The USA does not show any significant or near
significant t-statistics.
The interest rate increases show that the Euro zone, on the announcement day and on the 5
days before and after period, has highly significant statistics. They also show consistent signs.
The UK does not show any significant t-statistics, however, they are very close. The signs do
show an inconsistency. The USA shows highly significant results for the 5 and 10 day period.
The UK and USA do show, in general, reverse signs in comparison with the Euro zone.
The second issue that is addressed in this study is the issue of differences in abnormal returns
between types of banks. Not all types of banks are present in every geographical area.
Dummies are used to study if there are differences present. There are also a number of control
variables used to check whether or not the abnormal results are explained by the capital
structure and the fact if a bank is a net placer or a net borrower and to which extent. Table 8
shows the results for the official interest rate cuts.
The Euro zone shows highly significant results for 5 of the 7 banks. These banks are the
commercial bank, cooperative bank, bank holdings, investment banks and medium and long
term credit banks. The latter two have the highest coefficients with respectively -0.1199 and
-0.1251. The UK and the USA show no significant results for the bank dummies. The USA,
Table 9 shows the results of the official interest rate increases. The same types banks as in the
official interest rate cuts give significant results for the Euro zone. The medium and long term
credit bank is again the most affected. The USA also gives significant results for the
commercial bank and the investment bank. The sign of the coefficient from the USA banks
differs from the sign of the Euro zone banks. The control variables of the USA are significant
again. However, the areas accumulated do not give any significant result for the dummies at
the official interest rate increase and only a few low significant values for the control
variables. The UK does again not show any significant result.
Table 10 gives the results for the whole sample. This means official interest rate cuts and
increases together. For the individual geographical areas, only the Euro zone has only 2
significant results. The tendency of the coefficients is the same with the individual official
interest rate cuts and increases; the investment bank and the bank holding are more influenced
than the commercial bank and the cooperative bank. The UK and the USA do not show any
significant results for the dummies. However, when accumulating the three geographical
areas, 4 of the 7 bank dummies are significant. Also the control variables show significant
5. CONCLUSION
The first hypothesis in this study was to see if there were any abnormal stock returns of banks
present at the change of the official interest rate, set by the central bank. To test this
hypothesis the official interest rates of three central banks were used, the European Central
Bank, the Bank of England and the Federal Reserve. A t-test was used in order to test whether
or not abnormal returns were present.
For the banks in the Euro zone abnormal returns were significantly present on the
announcement date of an interest rate cut as well as an interest rate increase. The interest rate
cut had a negative sign and the interest rate increase had a positive sign. Concluding from this
result it can be said that there is an impact from an official interest rate change on the stock
return of banks in the Euro zone. An official interest rate cut is perceived as negative and an
official interest rate increase as positive. This suggests that signaling is reason. An interest
rate cut can be a signal for a slowing down in the money market which is negative for banks
and vice versa. It can also be a signal that the economy is in a worse state or better state than
expected. For example, an interest rate cut can signal that the overall economy is in a worse
state than expected and therefore future cash flows are lower which influences the stock price
of the bank.
The UK and USA did not give any significant results on the announcement day for both the
interest rate increase and the interest rate cut. Despite the USA not having any significant
results on the announcement day, it has a high standard deviation which indicates there was
There were cumulative abnormal returns present for the Euro zone and the USA at the 5 days
before until 5 days after the announcement date when an interest rate increase was announced.
It is hard to give an economic interpretation for these statistically significant results since
these results were not very consistent. For example, they differ in sign. The USA also gave
significant results for a period from 10 days before an interest rate increase announcement
until 10 days after. Again, it is hard to give an economic interpretation for these significant
results. In the UK, there were no abnormal returns found in any situation or time span.
The second objective of this study was to find out whether or not there was a difference
between types of banks. A distinction between 7 different specializations was used, taken
from Bankscope. Literature about the exposure and reactions of different types of banks is
limited which made it hard to theorize more reasons other than different exposures to market
interest rate risk and different reactions on a changing economic climate.
On the announcement day of an official interest rate cut, the Euro zone gave significant
results for 5 of the 7 types of banks. The conclusion is that there are differences between types
of banks in the Euro zone. This suggests that medium and long term credit banks, investment
banks and bank holdings are more affected by a change in the economic climate than other
banks in the Euro zone.
The USA and the UK had no significant results for any of the different types on the
announcement day of an official interest rate cut. The USA did show significant control
variables, and thus can be concluded that these variables do have an influence, at least in this
On the announcement day of an official interest rate increase, 5 of the 7 bank dummies in the
Euro zone gave significant results. The conclusion from this is that there is also a difference
between types of banks at an official interest rate increase. The medium and long term credit
bank had again the largest coefficient, which suggests that this type of bank is the most
affected by the official interest rate increase.
When putting the complete sample together, official interest rate cuts and increases and all
three geographical areas, 4 of the 7 bank dummies are significant. The conclusion is that they
are in general affected by an official interest rate change. The medium and long term credit
bank is the most affected.
Summarized, we conclude that abnormal returns are present but they are mainly present in the
Euro zone and less in the UK and USA. It is also the Euro zone where the main differences
are between types of banks. We suggest that the differences are a result of the extent to which
the banks are affected by future changes in the economic climate.
One of the limitations of this research is the small sample of UK banks and this is due to only
18 banks being listed on the London Stock Exchange. The absence of significant results might
be explained by this fact. The second limitation is the lack of clarity of definitions regarding
the different types of banks. It would be helpful to know what the criteria are to classify one
bank, for instance, as a commercial bank and another as a savings bank. For further research
we would recommend to study the volatility around events such as an official interest rate
change. Furthermore, the effect of an official interest rate change on market interest rates in
different areas of the world could be studied, giving more insight into why reactions between
6. REFERENCES
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APPENDIX A
Dates of interest rate cuts. The number of the interest rate cut corresponds with the number in table 2. For example, Interest cut number 1 is on 11-5-2001 in the Euro zone and 8-2-2001 in the UK etc.
APPENDIX B
Dates of interest rate increase. The number of the interest rate increase corresponds with the number in table 4. For example, Interest cut number 1 is on 6-12-2005 in the Euro zone and 6-11-2003 in the UK etc.
