Are Off-balance Sheet Activities Risky? Evidence from G7 Countries
Mamiza Haq
UQ Business School,
The University of Queensland, QLD 4072, Australia.
Email: m.haq@business.uq.edu.au.
Telephone: 61-7-3346-3090, Facsimile: 61-7-334-68166.
Abstract
This paper analyses the importance of off-balance sheet activities and charter value on bank risks, using
an unbalanced panel dataset of publicly-listed domestic banks across Canada, France, Germany, Italy,
Japan, UK and US over the 1996–2010 period, with particular focus on the 2007/2008 global financial
crisis (GFC). Overall, our results show a positive relationship between off-balance sheet activities and
market-based risk measures (such as total, systematic, idiosyncratic and interest rate risks) in the post
(during)-GFC period. The self-disciplinary role of charter value is observed in post (during)-GFC period,
particularly for total and idiosyncratic risks. Further, charter value may substitute bank capital in reducing
systematic risk. These findings have policy implications for bank safety.
JEL: G21, G32
Key words: Off-balance sheet items, derivatives, charter value, risk, financial crisis.
Acknowledgements: The authors wish to thank Enzo Dia, Kevin Davis, and conference participants at
the 13th INFINITI International Finance Conference in 2015. The authors acknowledge 2014 AFAANZ
Mid-career Research Grant. The usual caveats apply.
1
1. Introduction
At the very heart of the global financial crisis (GFC) in 2007/2008, losses were
associated with off-balance sheet activities created and held by financial institutions that led to
overall risk exposure of banks. These losses resulted in the failure, acquisition or bailout of some
of the largest institutions and a near meltdown of the world’s financial and economic systems.
Financial institutions have incentives to take ‘excessive’ risk at the expense of tax-payers funds
and creditors because of the well-known ‘moral hazard’ problem emanating from limited liability
and mispriced deposit insurance premium (Merton, 1977). This is compounded by the ‘too-bigto-fail’ effect with large banks. A failure of a bank can have severe repercussions to the local
and/or national economy unlike non-financial institutions. Such externalities impose a burden on
regulators to ensure that these failures do not impose major negative externalities on the
economy.
The aim of this paper is to assess the effectiveness of off-balance sheet activities in
reducing risk and the factors affecting off-balance sheet activities strength in the G7 countries
context. Our study contributes to the existing banking literature in several ways. First, we
investigate the effectiveness of off-balance sheet activities in reducing bank risk. We question
whether banks that are more reliant on non-interest generating activities take less risk.
Specifically, we investigate the following empirical questions. First, we test the effectiveness of
off-balance sheet activities pre and post 2007/2008 financial crisis. Second, we examine whether
bank regulation weakens the impact of off-balance sheet activities on bank risk taking. We
assume that bank capital and charter value may have a complementary role to play in disciplining
banks, while risk-based capital requirements may discourage banks to engage in off-balance sheet
activities and hence reduce the risk of the banking system.
Third, we analyse the moderating effect of off-balance sheet activities on bank charter
value and bank’s asset quality in reducing bank risk. We assume that off-balance sheet activities
provide banks with a comparative advantage and greater efficiency which can lead to an increase
2
in charter value (Reference). Further, Avery and Berger (1991) argue that safer banks with high
quality assets have a greater tendency to engage in off-balance sheet activities which in turn help
banks to reduce risk.
The traditional banking business makes long-term loans and funds them by issuing shortterm deposits. However, in recent years in particular prior to the financial crisis 2007/2008,
fundamental economic forces have undercut the traditional role of banks in financial
intermediation leading to a steady decline in the importance of bank loans and deposits. Over the
decades rising losses on loans, increased interest rate volatility, and squeezed interest margins for
on-balance sheet lending, due to non-bank competition, induced many large banks particularly,
in US to seek profitable off-balance sheet activities. By moving activities off their balance sheet
banks hoped to earn more fee income to offset the declining margins on their traditional lending
business. At the same time, they could avoid regulatory costs since reserve requirements, deposit
insurance premiums and capital adequacy requirements were not levied on off-balance sheet
activities 1. This has proved difficult for both investors and regulators to identify the actual level
of risk a bank faces in a given period of time. In the banking literature (e.g.; ) there is mixed
evidence as to whether off-balance sheet activities increase (decrease) risk. Thus, given increased
bank competition, and divergent capital rules, banks across the world have shifted towards nontraditional activities. These activities do not appear on the balance sheet and they involve the
creation of contingent assets and liabilities. Hence, due to the nature of these activities and the
fact that they have become increasingly widespread it is difficult for investors and regulators to
identify the actual level of risk a bank faces in a given period of time.
Off-balance sheet exposures may induce banks to reduce their total and systematic risks
(Brewer, Koppenhaver and Wilson 1986; Lynge and Lee 1987; Boot and Thakor 1991; Hassan,
Karels and Peterson 1994; Angbazo 1997). Similarly, Esty (1998) argues that contingent liabilities
can reduce equity and asset volatility as they have an impact on asset allocation and bank capital
1 Some of the non-interest income may not be part of the off-balance sheet activities. For example, commission and fees can are
also charged on credit cards and other services and trading income is not exclusively generated by off balance sheet activities.
3
requirements. Thus, even at low levels of net worth (charter value), banks with lower levels of
contingent liabilities may hold a smaller proportion of risky assets.
Banks must honor guarantees implicit in contingent liabilities or agreements when
required. 2 These liabilities help banks, particularly in times of increased competition, to expand
their revenue sources without altering their capital structure. Banks with higher levels of offbalance sheet items are found to be more cost and profit efficient and it has been argued that
off-balance sheet exposures promote a more diversified, margin generating asset-base compared
to deposits or equity financing (Angbazo, 1997). However, increased off-balance sheet activities
and escalation in bank failures have raised concern about the possibility of a positive relation
between bank risk and off-balance sheet items. For example, US commercial banks exhibit a
positive correlation between bank interest rate risk and off-balance sheet activities including
letters of credit, options and net securities lent (Angbazo, 1997). This supports the moral hazard
and adverse selection hypothesis that off-balance sheet activities increase bank risk (Wagster,
1996; Fraser, Madura and Weigand, 2002).
We analyse 278 publicly-listed banks across Canada, France, Germany, Italy, Japan, the
UK and the U.S. over 1996–2010, a period of extensive and rapid regulatory changes in the
financial sectors. Our overall results can be summarised as follows: (i) off-balance sheet activities
increase bank total, systematic and idiosyncratic risks but decrease interest rate risk in post-GFC
period; (ii) However, this influence varies depending on other bank-specific characteristics
(including charter value and asset quality) and the 2007/2008 GFC. For example, we observe
that in presence of off-balance sheet activities, charter value decreases total and idiosyncratic
risks over 2007/2010; (iii) loans are associated with higher market-based risks in both pre- and
post (during)-GFC periods; (iv) the importance of bank capital in reducing bank risk is
2 Calmes and Theoret (2010) use the broad definition of off-balance sheet activities which loosely include all non-interest
generating activities (income diversification is predominantly generated by these activities). Indeed, non-interest income has
become an indispensable proportion of banks’ income today. For example, the total value of non-interest income had been larger
than the interest income for US listed banks from 2003 to 2007. However, how beneficial this income diversification is remains
unclear, in fact, there is a large body of literature related to the cost and benefit of bank diversification.
4
somewhat inconclusive; (v) disciplining role of bank charter value is effective in post (during)GFC period; (vi) charter value may substitute bank capital. The findings of this study may assist
regulators to rigorously monitor banks, ensuring adequate internal controls over asset quality and
risk management.
The remainder of the paper is structured as follows. Section 2 presents data and
methodology. Section 3 describes the empirical analysis while robustness checks are provided in
Section 4. Finally, Section 5 concludes the paper with some policy implications.
2. Data and Methodology
2.1 Data
The dataset consists of G-7 countries (Canada, France, Germany, Italy, Japan, UK and
USA) over 15 years’ time span (1996-2010). Bank level information, including the balance sheet
and income statement is extracted mainly from the Fitch Solutions database. The annual report
of each of the banks is checked to ensure that bank subsidiaries are not also included as separate
entities in our final data set to reduce the impact of double counting. We have used weekly
market information including share prices and interest rate information from DataStream
International. The original sample is filtered by excluding banks with less than three consecutive
yearly observations, and banks for which data on the main variables are not available (such as
market capitalization, tier 1 ratio). Thus, the final sample includes 278 publicly-listed domestic
banks, giving an unbalanced panel of 3,149 bank-year observations. Table 1 provides the sample
composition.
[Insert Table 1 about here]
2.2 Alternate dependent variables
The bank risk variables, broadly referred to as RISKijt in the following sections, include
market-based risk indicators i.e. total, idiosyncratic, systematic and interest rate risks.
Total risk is computed as the variance of the weekly bank stock returns in each year, i.e.,
(1)
σ 2ri = 1/N ∑ tN=1 (R t − R ) 2
5
where σ ri2 = the total risk or variance of bank returns for bank i; Ri = bank i return per week;
R
= the average bank i return and; N = the number of observations.
Following Konishi and Yasuda (2004), we use the following two-factor market model to
compute systematic, interest rate and idiosyncratic risks 3.
(2)
R it = α i + β i, m R Mt + β i, I R It + ε it
where R it = weekly stock return of bank i at date t ; R Mt = weekly return on the market. Based
on the geographical exposure either the MSCI country index or the MSCI world index or the
MSCI Europe index is used; ε it = residual term. The market beta, β m , is used as a proxy for
systematic risk and is estimated using the MSCI market index. The natural log of the residual
variance from the two factor market model is used as an estimate of idiosyncratic risk for each of
the banks. The interest rate beta, βI , is estimated to capture interest rate exposure. We follow the
work of Haq and Heaney (2012) and choose the long term interest rate in our model since longterm interest rates are considered to better explain bank returns 4.
2.3 Variables of interest
Traditional off-balance sheet activities are measured by total off-balance sheet items
against total liabilities. Off-balance sheet activities include managed securitized assets, guarantees,
acceptances and documentary credits, and committed credit lines and other off-balance sheet
activities. Market-related off-balance sheet activities are the sum of equity derivatives, interest
rate derivatives, credit derivatives, foreign exchange derivatives and commodity derivatives scaled
by total assets (Mayordomo, Rodriguez-Moreno and Peña, 2014).
3 Multi-factor models like the Fama and French three factor model are not used for risk estimation in this study as there is little
support in the literature for the use of this model in analysis of bank returns (Viale, Kolari and Fraser, 2009). The risk estimates
are calculated each year for each bank using the weekly return observations available during the year of interest. While there is
some support for expanding the one factor model to include yield curve effects we include the interest rate level in our two factor
model given the importance of interest rate sensitivity in analysis of bank risk. It should be noted that interest rate level will be
correlated with yield curve, though ultimately variable choice is still fairly arbitrary in the asset pricing literature.
4 However, there is debate concerning whether a two factor market model or a one factor market model should be used. Due to
multicollinearity between interest rates and market factors some authors orthogonalize changes in the interest rate factor
(Flannery and James 1984). Giliberto (1985) argues that this approach can bias the t-statistics against one or other of the two
factors. As a result, we follow Kane and Unal (1988) estimate the model without any attempt to remove common variation from
one of the variables.
6
2.4 Bank-level and country-level control variables
Charter value is the ratio of the sum of the market value of equity and the book value of
liabilities to the book value of total assets following Keeley (1990). Bank capital is measured by
Tier 1 ratio as mentioned in the Basel Accords. On one hand, capital ratio can discipline banks
by way of the capital at risk effect, because by operating with their own capital, banks bear part
of the risk for their activities (Tabak, Fazio and Cajueiro, 2012). One the other hand, higher
capital levels may induce banks to increase probability of default (Gennotte and Pyle, 1991;
Shrieves and Dahl, 1992; Berger, Herring and Szegö, 1995; Rime, 2001) since regulatory
constraints on bank leverage lead to substitution from debt into more risky assets. Thus, the
overall effect of bank capital is ambiguous. Further, as an indicator of asset quality (AQ) we
define loans as the ratio of total loans to total assets (Martinez-Peria and Schmukler, 2001),
reflecting to what extent bank’s focus on traditional intermediation activity that is originate loans
compared to hold other assets such as securities (Demirgüç-Kunt and Huizinga, 2012).
The operational efficiency of banks is measured by cost to income ratio. Less efficient
banks reflect higher expenditures. However, it can also be the case that banks that provide better
quality services to their customers can incur higher expenditures to total assets (Martinez –Peria
and Schmukler, 2001). Similar to Martinez –Peria and Schmukler (2001) we are unable to control
for quality of the services provided by banks, thus, the effect of this variable is indeterminate.
Operating leverage is measured by fixed assets to total assets. Mandelker and Rhee (1984) and
Saunders, Strock and Travlos (1990) consider operating leverage in a similar way to financial
leverage with increases in operating leverage resulting in increases in bank risk. Thus, the analysis
considers that operating leverage will be positively related to alternate bank risk measures.
With regard to revenue diversification prior literature (e.g.; Lepetit, Nys, Rous and Tarazi,
2008; Stiroh and Rumble, 2006) suggest that banks' expansion into non-traditional financial
activities is not associated with diversification benefits, but rather with lower risk-adjusted return
and higher insolvency risk. However, Baele, De Jonghe and Vennet (2007) provide evidence that
7
the market judges more diversified banks to have a higher return potential (measured by Tobin’s
Q). 5 Williams (2012) finds evidence in the Australian context that combining interest with noninterest revenues does not generate any portfolio diversification benefit, supporting the argument
that greater complexity can lead to an increase in agency costs that may exceed any
diversification benefits (Schmid and Walter, 2009; Laeven and Levine, 2007). Revenue diversity
is captured by non-interest income, calculated as:
Revenue diversification index i,j,t= 1- (SH2NETi,j,t + SH2NONi,j,t)
(3)
where; SH2NET=share of net operating revenue from net interest sources and SH2NON = share of
net operating revenue from non-interest sources.
Finally, we incorporate bank size (natural logarithmn of total assets) to capture any
effects of size differences among the sample banks. Large banks may be less risky, since they
benefit more from portfolio diversification. However, regulatory environment can affect the
relationship between bank size and bank risk. Deregulatory periods can encourage a positive
relationship between bank size and bank total risk. In periods of greater regulation also, the
imposition of “too-big-to-fail” policies, explicit and implicit safety net can increase the incentive
of large banks to take on more risk (Galloway et al., 1997). Large banks with greater sensitivity to
the general market movements may exhibit a positive relationship with bank systematic risk
(Anderson and Fraser, 2000). Hence, we predict a positive association between systematic risk
and size.
The Economic Freedom Index (EFI) is used to measure regulatory restrictions, with
higher EFI scores reflecting reduced levels of regulation. A negative relationship is predicted
between bank risk and EFI. We follow Demirgüç-Kunt and Huizinga (2004) and incorporate
real GDP growth (RGDP) as the macro-economic control variable. This will capture the impact
of macro-economic shocks that adversely affect bank performance by increasing risk. Hence, we
predict the relationship to be positive with risk.
5 Baele, De Jonghe and Vennet (2007) also argue that a bank that is more oriented towards non-traditional banking activities
(lower loan to total asset ratio) has a higher systematic and total risk.
8
2.5 Descriptive statistics and correlation analysis
Table 2 presents the descriptive statistics for bank characteristics and macro-economic
variables. The alternative measures, of bank risk, that is, total, systematic, idiosyncratic, and
interest rate risks have a mean value of 0.002, 0.635, 0.001, -0.027, respectively.
[Insert Table 2 about here]
In general, traditional off-balance sheet activities range between 0.3% - 22.3% with an
average of 4.90%. Market-related off-balance sheet activities range between 0 - 0.087 with an
average of 0.002, which is consistent with Mayordomo, Rodriguez-Moreno and Peña, 2014.
Keeley’s (1990) measure of charter value has a mean of 1.03. The maximum (1.11) and
minimum (0.97) charter value is observed in the U.S. and Japan, respectively. Banks hold a Tier 1
ratio well above the minimum capital requirement of 4%. For example, the maximum Tier 1
ratio of 14.1% and the minimum of 6.60% are observed for Royal Bank of Scotland Group Plc
in 2009 and 1998 respectively. Regarding size, the smallest bank in the study is Canadian Western
Bank with total assets of USD 66.51 million in 1996, whereas the largest bank, Royal Bank of
Scotland Group Plc has total assets of USD 4267.102 million in 2008. The maximum and
minimum value for bank efficiency (i.e.; cost to income ratio) ranges between 52%-79%, and
observed for U.S. banks. On average, bank total assets consist of 66% of bank loans. The
macroeconomic variable real GDP growth rate reflects both crisis and normal periods. During
the 2008-2010 period, GDP growth rate ranged between -6.23% to -0.021%.
Pearson correlation coefficients are reported in Table 3. The correlation between charter
value and tier 1 ratio and charter value and efficiency is 0.29 and -0.37 respectively and
statistically significant. Other bank-specific variables are also significantly correlated with size
including Tier 1 ratio (-0.36), off-balance sheet activities (0.21), loan to total assets (-0.24) and
operating leverage (-0.21). To ensure that correlations will not lead to multi-collinearity, we check
the variance inflation factors (VIF). All VIF values were less than 10, with the means lying
between 2 and 4, suggesting that multi-collinearity is not a serious problem (Gujrati, 2003).
9
[Insert Table 3 about here]
2.6 Empirical method
To examine the impact of off-balance sheet activities on bank risk, we estimate the
following panel data model applying both individual bank and time fixed effects (Distinguin,
Kouassi and Tarazi, 2013):
α 0 + β1OBS i,j,t + β2 CVi,j,t + β3 Tier 1 i,j,t + β4 Loans i,j,t + β5 Fixed i,j,t + β6 RDI i,j,t + β7CIR i,j,t + β8 Size i,j,t +
Risk i,j,t = 
γ1GDPGR j,t + γ 2 EFI j,t + η i + τ t + ε i,j,t
(4)
In the context of equation (5), we make the following predictions: β1 > 0. We predict that
off-balance sheet activities have a positive impact on bank risk.
Equation (5) explores the association between off-balance sheet activities and risk
conditional on a bank’s market power and asset quality.
α 0 + β1OBS i,j,t + β2 CVi,j,t + β3 Tier 1 i,j,t + β4 Loans i,j,t + β5 Fixed i,j,t + β6 RDI i,j,t + β7CIR i,j,t + β8 Size i,j,t +
Risk i,j,t = 
 γ1GDPGR j,t + γ 2 EFI j,t + δ1CVi,j,t × OBS i,j,t + δ2 Loans i,j,t × OBS i,j,t + η i + τ t + ε i,j,t
(5)
In addition, to examine how the association between bank capital and risk is conditional
on the strength of a bank’s off-balance sheet activities, market power, asset quality, we estimate
the following specification:
α 0 + β1OBS i,j,t + β2 CVi,j,t + β3 Tier 1 i,j,t + β4 Loans i,j,t + β5 Fixed i,j,t + β6 RDI i,j,t + β7CIR i,j,t + β8 Size i,j,t +
Risk i,j,t = 
 γ1GDPGR j,t + γ 2 EFI j,t + δ1CVi,j,t × Tier1i,j,t + δ2OBS i,j,t × Tier1i,j,t + δ3 Loans i,j,t × Tier1i,j,t + η i + τ t + ε i,j,t
(6)
where: i for individual banks (i = 1, 2, , 16); j for country (j = 1, 2), t for time period (t = 1996,
1997, ….., 2010); ηi is the individual fixed effects, t t is the time fixed-effects, and εi,j,t is the
remaining disturbance term.
3. Empirical results
3.1 Main results
We test for the impact of off-balance sheet activities on both market-based risks. To do
so, we divide our sample into two narrow periods including 1996-2006 (pre-GFC) and 20072010 (post (during)-GFC). First, we find that all our models satisfy the requirement of the bank
10
fixed-effects (Hausman test). The results are reported in Panel A (traditional off-balance sheet
activities) and Panel B (derivative or market related off-balance sheet activities) of Table 4.
[Insert Table 4 about here]
Our findings document that off-balance sheet activities increase bank systematic and
idiosyncratic risks in post (during)-GFC period which in turn, increases bank total risk in the
same period (see columns 2, 4 & 6). Hence, the market recognises the importance and riskiness of
off-balance sheet activities during 2007/2010 period. Similar evidence is also observed for
interest rate risk (see columns 7) however, in pre-GFC period. This positive and statistically
significant association between off-balance sheet activities and bank risk suggest that off-balance
sheet activities, while generating fee income for banks, also creates additional bank risk. This
could be a concern for bank regulators as the risk of off-balance sheet activities, if not managed
properly, could squeeze liquidity and create sudden losses. However, both Basel Accord I and II
proposals have also considered off-balance sheet activities to be risky and these are included in
risk-weighted bank capital ratio calculations. This action seems warranted given the results
reported in this study.
We also perceive that in post (during)-GFC period, the coefficient on off-balance sheet
activities is negative and statistically significant at the 5% level or better, particularly, for interest
rate risks, (see column 8). These findings suggest that off-balance sheet activities help banks to
reduce interest rate risk and thus, manage banks' maturity mismatch issue particularly, in the post
(during)-GFC period. Further, we find support those off-balance sheet activities also decrease
bank systematic risk in pre-GFC period (see column 3), indicating that market may have failed to
identify the riskiness of the contingent liabilities.
With regard to control variables, we observe that the disciplinary role of charter value is
effective in post (during)-GFC period. For example, the coefficient on charter value for total and
idiosyncratic risks (see columns 2 & 6) is negative and statistically significant at the 1% level. In
contrast, we find that higher charter value tends to increase systematic and interest rate risks,
11
particularly, in pre-GFC period, suggesting that a surge in market value of equity and total
liabilities has a positive impact on market-based risk measures (see columns 3, & 7). Thus, the
disciplinary role of charter value was absent prior to 2007/2010 period.
High bank capital is associated with lower total and idiosyncratic risks in both pre- and
post (during)-GFC period (see columns 1, 2, 5 & 6). However, we do observe that bank capital
tend to increase interest rate risk in the pre-GFC period (see column 7). Our findings show higher
loans to assets ratios (asset quality) are associated with lower bank total, idiosyncratic risks during
2007/2010 period (see columns 2 & 6). Further, operating leverage exhibits a positive (statistically
significant at 5% level or better) effect on total, systematic, idiosyncratic risks during 2007/2010
and interest rate risk over 1996-2006 (see column 7).
The coefficient on bank size is negatively associated with total, systematic and
idiosyncratic risks over the full sample period, suggesting that bank risk-taking may not be
consistent with the “too-big –to-fail-policy”, where large banks have greater incentive to take on
risky businesses as they enjoy a comprehensive safety net.
With regard to macro-economic variables, real GDP growth rate is positive and
statistically significant at the 5% level or better for total and idiosyncratic risks, capturing the
impact of adverse macro-economic shocks that affect banks by increasing their risk exposure
over 2007/2010 period. Similar evidence is observed for systematic risk over the full sample
period. However, GDP growth rate decreased idiosyncratic risk in pre-GFC period. Further,
economic freedom index (EFI) is negatively associated with all bank risk measures and is
statistically significant at the 1% level (see columns 1, 3, 5 & 6). This result implies that greater
levels of economic freedom, particularly, in terms of lower levels of regulation and government
intervention, generate lower total, systematic and idiosyncratic risks. Hence, the result is
consistent with our predictions.
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3.2 Results for intermediating effects
3.2.1 Intermediating effects of off-balance sheet activities
It has been argued that off-balance sheet activities increase volatility in bank’s revenue
and therefore, increases bank risk (Mayordomo, Rodriguez-Moreno and Pena, 2014; Nijskens
and Wagner, 2011; Calmès and Théoret, 2010). Further, contingent liabilities can help banks to
earn rents temporarily if they have superior production technology that may not be available to
other institutions, the so-called first-mover effect (Furlong and Kwan, 2006). Banks may have
scope economies with other bank activities giving them a cost-advantage over non-bank
institutions because banks have a comparative advantage in off-balance sheet activities like loan
commitments (Haq and Heaney, 2012). Indeed, the combination of scope economies and
potential efficiency enhancement can contribute to improve banks' charter value (Furlong and
Kwan, 2006). Thus, even in presence of high off-balance sheet activities, bank charter value can
decrease bank risk.
Furthermore, it is evident that off-balance sheet activities increase the insolvency
exposure of a bank that engages in such activities. However, an opposing view holds that loan
commitments contracts may make a bank less risky than had it not engaged in them. The
theoretical work by Boot and Thakor (1991) suggest that banks must convince borrowers that it
will be around to provide the credit required in the near future. Thus, bank managers may have
to maintain lower risk asset portfolio today than would otherwise be the case. By adopting lowerrisk portfolios, managers increase the probability that bank will be able to meet all long-term on
and off balance sheet obligations. Empirical studies such as Avery and Berger (1991) confirm
that bank’s making more loan commitments have lower on balance sheet portfolio risk
characteristics than those with relatively low levels of commitments, that is safer banks have a
greater tendency to make loan commitments.
13
Based on the above discussion we incorporate two interaction terms including charter ×
off-balance activities and asset quality × off-balance activities. Thus, we estimate eq. (5) and the results are
reported in Table 5.
[Insert Table 5 about here]
The coefficient on charter × off-balance sheet activities is negative and statistically significant
with bank total and idiosyncratic risk in post (during)-GFC period (see columns 2 & 6). These
findings suggest the self-disciplinary role of charter value is evident for market-based measures
of risk. Furthermore, with regard to total and idiosyncratic risks, the coefficient on asset quality ×
off-balance sheet activities is positive and statistically significant at the 5% level or better (see columns
1, 2, 5 & 6). This finding is observed for both pre and post (during)-GFC periods, indicating that
in presence of off-balance sheet activities loans tend to increase bank risk. We find similar
evidence for systematic risk although for post (during) - GFC period only (see column 4).
3.2.2 Intermediating effects of bank capital
It is well-known that government guarantees or safety nets (such as deposit insurance,
too-big-to-fail guarantees, and lender of last resort) can lead to a moral hazard problem. If the
value of guarantees to the bank is less than they are charged for them, the safety net provides
banks with a net subsidy (Allen and Rai, 1996), which is incorporated within the bank’s charter
value. Thus, the moral hazard effect explains that, if bank charter value stems from government
subsidies, this may discourage banks from holding capital. As these subsidies become more
generous, bank capital is substituted by a government safety net and a negative association
emerges between charter value and bank capital.
The market rent effect, however, reflects a positive association between bank capital and
charter value. To avoid any additional costs from providing a subsidy, governments impose
restrictions on entry to banking. Entry restrictions allow banks to earn monopoly rents that may
be dependent on the terms of the safety nets. Imperfectly competitive financial markets can also
allow banks to earn monopoly rents and thus, higher charter value. Bank failure can force the
14
shareholders to surrender the bank’s charter value or expected profits from continued
operations. Therefore, banks’ expected future profitability leads to higher charter values which,
in turn, reflect greater capital buffer which may be significant for shareholders to retain control
and reduce the probability of default.
[Insert Table 6 about here]
Based on the above discussion, we estimate eq. (6) and the results are reported in Table
6. The coefficient on charter × Tier 1 ratio is positive and statistically significant at the 5% level
for systematic risk only (see columns 3 & 4) during pre- and post (during) - GFC period. This
finding supports the moral hazard effect suggesting that in presence of bank capital, charter
value fails to discipline banks, thus, charter value can substitute rather than complement bank
capital in reducing bank’s risk taking exposures.
In addition, off-balance sheet activities are fee generating activities and can improve
bank’s profitability much faster than on-balance sheet fee producing activities. For instance,
earning generated from off-balance sheet activities are included in income while total asset
balances are not affected, thus, profitability ratios appear higher compared to income derived
from on-balance sheet activities. In addition, off-balance sheet activities remain off-the bank’s
balance sheet, hence, capital to asset ratio (with the exception of risk-adjusted capital ratio) is not
adversely affected regardless of the volume of business conducted (Federal Deposit Insurance
Corporation (FDIC), 2012). However, the volume and the risk of the off-balance sheet activities
need to be considered by the regulators and examiners in the evaluation of capital adequacy.
Regulatory concern arises with these activities since they subject a bank to certain risks. Many of
the risks involved in these off-balance sheet activities are unquantifiable on an off-site
monitoring basis (FDIC, 2012).
Moreover, the risk-based capital requirements can be viewed as discouraging off-balance
sheet activities growth thus, reducing total risk of the banking system. Thus, banks engage in offbalance sheet activities to reduce regulatory taxes, such as capital requirements. In contrast,
15
Benveniste and Berger (1987), Koppenhaver (1989) argue that capital constraints do not play a
role in bank’s decision to engage in off-balance sheet activities. Further, Avery and Berger
(1991), Jagtiani (1995) find that better performing and more credit worthy banks issue loan
commitments and swaps (inconsistent with capital avoidance hypotheses) and that capital
requirements have no consistent impact on the speed of transmission across off-balance sheet
activities (Jagtiani, Saunders and Udell, 1995). Thus, we interact off-balance sheet activities with
Tier 1 ratio (contingent × Tier 1) to investigate whether in presence of bank capital; off-balance
sheet activities decrease /increase bank risk. The results are reported in Table 6.
With regard to total, idiosyncratic, and interest rate, the coefficient on contingent × Tier 1 is
statistically insignificant, suggesting that the importance of bank capital on off-balance sheet
activities in reducing risk is inconclusive. However, with regard to systematic risk, the coefficient
on contingent × Tier 1 is positive and statistically significant at the 5% level (see column 4),
suggesting that market continues to recognise the riskiness of off-balance sheet activities, even
when bank has capital buffer in place during 2007/2010 period. Perhaps, bank capital
requirements do not serve the risk curtailment purpose as they do for on-balance sheet claims.
Next, we analyse whether banks properly estimate and truthfully report the riskiness of
their loans and ensure compliance and reduce moral hazard in banking. This is precisely the
subject of the supervisory review mentioned in Basel II (Repullo and Suarez, 2004). Our findings
show that the coefficient on asset quality × Tier 1 is positive and statistically significant (at the 5%
level) with total and idiosyncratic risks in post (during)-GFC period (see columns 2 & 6). Thus, in
presence of bank capital, bank loans increases market-based risks. This result further supports
the argument that Basel II does not take into account the net interest income from performing
loans, which provides a buffer in addition to capital losses against credit losses (Repullo and
Suarez, 2004).
16
5. Robustness checks
We conduct a number of robustness checks. First, we run regressions excluding the USA
bank holding companies. Our findings demonstrate that with regard to systematic risk, the
coefficient on off-balance sheet activities is statistically insignificant in both pre- and post
(during) - GFC period. Second, we test the sensitivity of our results by considering alternate
proxy of bank capital. Following Demirgüç-Kunt and Huizinga (2004), we consider leverage
ratio (equity to total assets) as a book value measure of bank capital. Our mains results remain
qualitatively the same. Third, we re-do this analysis without country-level/macroeconomic
variables. The interpretations of the result remain the same as those discussed earlier in Section
3.
Fourth, we divide the sample into high off-balance sheet activities and low off-balance
sheet activities considering the mean of the off-balance sheet activities as the cut-off point. Our
findings show that if off-balance sheet activities are initially at a relatively low level, then an
increase in off-balance sheet activities can lead to an increase in total, systematic and
idiosyncratic risks. This finding is observed in post (during)-GFC period. Similar evidence is also
evident for systematic and idiosyncratic risks in pre-GFC period. Banks with relatively high level
of off-balance sheet activities and in pre-GFC period we find evidence that these items appear to
increase interest rate risk.
Finally, to derive a better understanding of charter value as a determinant of bank risk,
we divide our sample into two groups: high charter value (above the mean value 1.03) and low
charter value (below the mean value 1.03). The coefficients on off-balance sheet activities are
positive and statistically significant at the 1% level, suggesting that in post (during)-GFC period
and with lower charter value, off balance sheet activities increase bank risk including, total,
systematic and idiosyncratic risks. However, the opposite is true for interest rate risk. We also
observe that in pre-GFC period and with high (low) charter value, off-balance sheet activities
tend to decrease systematic risk. In addition, the disciplinary role of charter value is observed for
17
both high and low charter value banks in post (during)-GFC period across total and idiosyncratic
risks. However, the coefficient on charter value is positive and statistically significant at the 1%
level for total and systematic risks, indicating that disciplinary role of charter value is not in effect
even for high charter value banks in pre-GFC period.
6. Conclusion
The significant growth in off-balance sheet activities leads to difficulty to investigate
bank risk. There has been increased amount of regulation focusing particularly on off-balance
sheet activities. For example, Basel Accords increased the credit conversion factor for these
activities from 50% (Basel I) to 100% (Basel II). Hence, regulators have repeatedly concentrated
on strengthening bank capital, disclosure and supervision for banks in controlling excessive risktaking. Charter value has also gained the interest of the regulators in so far as it can work as a
self-disciplinary tool in reducing the moral hazard problem that arises from implicit and explicit
deposit insurance schemes. Against this backdrop, our paper investigates the impact of offbalance sheet activities and charter value on bank risk with particular focus on the recent
financial crisis 2007/2008. To this end, evidence is sought as to how this relationship is
conditional on the strength of a bank’s capital regulation and asset quality. Using a sample of all
publicly listed domestic banks across G-7 countries over the 1996 to 2010 period, our results
suggest that, on average, off-balance sheet activities increase bank risk (total, systematic,
idiosyncratic and interest rate risks) in the post (during)-GFC period. The self-disciplinary role of
charter value is evidenced in post (during)-GFC period, particularly for total and idiosyncratic
risks. We show that in presence of charter value, off-balance sheet activities decrease total and
idiosyncratic risks in post (during)-GFC period. Most notably, we find that charter value may
substitute bank capital in reducing systematic risk. Finally, our findings support that the
importance of bank capital on off-balance sheet activities in reducing risk is inconclusive.
In general, the findings of this study have implications for regulators, equity-holders,
bond holders and borrowers, all of whom have concern in understanding the risk and return
18
profile
of
financial
institutions.
Evaluating
bank
risk
is
equally
important
to
regulators/supervisors, borrowers, equity and bond holders. Regulators (including implicit and
explicit safety net providers) and supervisors, who are responsible to maintain financial stability,
have a keen interest in bank risk (in particular total risk) due to the costs associated with
bankruptcy, contagion, asymmetric information, managerial agency problems and possible
disruption in the allocation of credit. Well-diversified equity-holders are particularly concerned
with systematic risk while bond holders tend to be concerned with both systematic risk and
idiosyncratic risk.
Unfortunately, as a result of the GFC, there is a deeply embedded presumption that
governments will use taxpayer dollars to bail out banks, creating a solid incentive for banks to
take undue risks. Should this be allowed to continue, it will leave bank supervisors as the main
restraint on excessive risk taking – not the banks themselves or their investors. Regulators and
policymakers are setting out proposals aimed at counteracting the effects of this moral hazard on
financial systems. The usefulness of the determinants of bank risk suggests that transparency
mandated by regulators have been reflected in the market-based measure. Thus, it supports the
belief that market risk is useful in evaluating large, complex and opaque financial institutions.
19
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20
Table 1 Sample composition
The sample consists of 278 publicly-listed domestic banks including commercial banks and bank holding companies across
Canada, France, Germany, Italy, Japan, United Kingdom (UK) and the United States of America (USA) over 1996-2010, with a
total bank–year observations of 3,149.
Group 7 countries
Number of listed domestic banks
Number of observations
Canada
8
115
France
5
75
Germany
6
85
Italy
10
130
Japan
90
1,053
UK
5
67
USA
154
1,624
278
3,149
21
Table 2 Descriptive statistics
This table shows descriptive statistics for risk measures and bank-specific characteristics. Results are for all publicly-listed
domestic banks across Canada, France, Germany, Italy, Japan, United Kingdom (UK) and the United States of America (USA)
over 1996-2010. We winsorize all variables at the 1% level. + scaled by 100
Mean
Standard deviation
Minimum
Maximum
Dependent variables
Total risk
0.002
0.002
0.049+
0.006
Systematic risk
0.635
0.456
0.018
1.387
Interest rate risk
-0.027
0.145
-0.270
0.202
Idiosyncratic risk
0.001
0.001
0.037+
0.004
0.049
0.002
0.073
0.011
0.003
0
0.223
0.087
Charter value
1.026
0.047
0.970
1.115
Tier 1 ratio
10.151
2.404
6.550
14.100
Revenue diversification
0.321
0.111
0.143
0.479
Efficiency
0.660
0.084
0.521
0.795
Loans to total assets
0.657
0.081
0.516
0.769
Fixed assets to total assets
0.016
0.007
0.007
0.027
Size (natural logarithm of total assets in USD)
9.906
3.789
4.190
22.170
Real GDP growth rate
0.018
0.023
-0.063
0.055
Economic freedom index
74.407
5.604
57.360
81.200
Variable of interest
Off-balance sheet activities- traditional
Off-balance sheet activities- market-related
Bank-level control variables
Country-level control variables
22
Table 3 Correlation analysis
The table shows the pair-wise correlation between off-balance sheet activities (traditional and market related) and other bank-level and macro-level control variables. Superscript
significant at the 5% level.
Charter
value
Bank
capital
Off-balance
sheet
-traditional
Off-balance
sheet -market
Revenue
diversification
Efficiency
Asset
quality
Operating
leverage
Size
**indicates
GDP
growth
rate
Charter value
1
Bank capital
0.29**
1
Off-balance sheet activities-traditional
-0.09**
-0.02
1
Off-balance sheet activities-market related
-0.01
0.03
0.23**
1
Revenue diversification
0.22**
0.18**
0.38**
0.20**
1
Efficiency
-0.37**
-0.17**
0.01
0.02
-0.12**
Asset quality
-0.01
-0.20**
-0.16**
-0.25**
-0.18**
0
1
Operating leverage
0.06**
0.07**
-0.23**
-0.23**
0.01
0.23**
0.18**
1
Size
-0.23**
-0.36**
0.21**
0.24**
-0.04
-0.08
-0.24**
-0.21**
1
GDP growth rate
0.41**
0.19**
-0.11**
-0.03
0.12**
-0.17**
-0.06**
0.10**
-0.21**
1
Economic freedom index
0.30**
0.48**
-0.05**
0.02
0.15**
-0.08**
0.11**
0.09**
-0.40**
0.07**
23
1
statistically
Table 4 Determinants of bank risk- narrow period analysis
The tables represent the results of the bank fixed-effects with year fixed effects estimates of equation (4). The dependent variable
RISK is either total risk or idiosyncratic risk or systematic risk or interest rate risk. Total risk is the standard deviation of the bank’s
weekly stock returns over a year (eq. 1). Idiosyncratic risk is calculated as the variance of εit in eq.(2). Systematic risk is the coefficient
of Rmt, i.e. βm in the two-factor market model as represented by eq.(2). Interest rate risk is the coefficient of RIt, i.e. βI in the twofactor market model as represented by eq.(2). Standard errors are reported in parentheses. Superscripts*, **, *** indicate
statistical significance at 10%, 5%, and 1% levels, respectively.
Panel A: Traditional off-balance sheet activities
Off-balance sheet
Charter value
Tier 1 ratio
Asset quality
Operating
leverage
Revenue div.
Efficiency
Size
GDP growth rate
Economic
freedom
Intercept
Year fixed-effects
Number of
observations
F-test
Adjusted-R2
Total
risk
Total
risk
Systematic
risk
Systematic
risk
Idiosyncratic
risk
Idiosyncratic
risk
Interest
rate risk
1996-2006
(1)
-0.001
(0.001)
0.001
(0.002)
-0.006**
(0.002)
-0.001
(0.001)
0.012
20072010
(2)
0.008***
(0.001)
-0.010***
(0.003)
-0.010**
(0.005)
-0.004**
(0.002)
0.046**
19962006
(3)
-1.286***
(0.486)
0.612*
(0.369)
-1.213
(0.855)
0.214
(0.226)
-0.796***
20072010
(4)
1.475***
(0.245)
-0.817
(0.553)
-0.761
(1.094)
-0.582
(0.441)
0.279*
19962006
(5)
0.001
(0.001)
0.001
(0.001)
-0.004**
(0.002)
-0.001
(0.001)
0.012*
20072010
(6)
0.004***
(0.001)
-0.007***
(0.002)
-0.006***
(0.002)
-0.003***
(0.001)
0.031**
19962006
(7)
0.192*
(0.110)
0.273**
(0.137)
0.653**
(0.329)
-0.245***
(0.093)
3.491***
Interest
rate
risk
20072010
(8)
-0.249**
(0.121)
0.359
(0.303)
-0.367
(0.446)
0.387*
(0.209)
-3.309
(0.011)
0.001
(0.001)
0.010
(0.015)
-0.055**
(0.027)
0.002
(0.005)
-0.003***
(0.023)
0.003
(0.010)
0.002**
(0.001)
-0.239**
(0.119)
0.022**
(0.009)
-0.010
(0.318)
0.310*
(0.180)
0.114
(0.181)
-0.584**
(0.282)
0.325***
(0.105)
-0.011*
(0.151)
0.275
(0.181)
0.086
(0.203)
-0.417**
(0.185)
3.721*
(2.226)
0.034*
(0.007)
0.001
(0.004)
0.005
(0.015)
-0.020**
(0.010)
-0.007***
(0.002)
-0.015***
(0.015)
0.010
(0.019)
0.001
(0.001)
-0.072**
(0.031)
0.037***
(0.009)
-0.021***
(1.252)
-0.087
(0.072)
0.016
(0.071)
0.089**
(0.045)
-0.522
(0.421)
0.001
(2.591)
-0.077
(0.112)
-0.040
(0.110)
0.088**
(0.044)
1.224
(1.594)
-0.003
(0.001)
0.012***
(0.002)
Yes
2,228
(0.012)
0.024***
(0.008)
Yes
921
(0.006)
0.541
(0.674)
Yes
2,228
(0.019)
-0.714
(1.646)
Yes
921
(0.005)
0.009***
(0.002)
Yes
2,228
(0.007)
0.025***
(0.005)
Yes
921
(0.002)
2.756
(3.994)
Yes
2,228
(0.012)
-0.437
(5.105)
Yes
921
17.01***
0.16
101***
0.60
33.71***
0.39
6.63***
0.13
21.78***
0.22
75.02***
0.58
7.83***
0.04
16.75***
0.23
24
Panel B: Market related (derivatives) off-balance sheet activities
Derivatives
Charter value
Tier 1 ratio
Asset quality
Operating lev.
Revenue div.
Efficiency
Size
GDP growth
Economic free.
Intercept
Year fixed-effects
Number of
observations
F-test
Adjusted-R2
Total
risk
Total
risk
Systematic
risk
Systematic
risk
Idiosyncratic
risk
Idiosyncratic
risk
19962006
(1)
-0.007***
(0.003)
-0.002
(0.001)
-0.003
(0.002)
-0.000
(0.001)
0.000
(0.000)
0.000
(0.001)
0.000
(0.001)
-0.000*
(0.000)
-0.006***
(0.002)
-0.013***
(0.001)
0.013***
(0.003)
Yes
2,328
20072010
(2)
-0.004***
(0.001)
-0.022***
(0.004)
-0.006
(0.005)
-0.004**
(0.002)
0.001***
(0.000)
-0.004***
(0.001)
0.003***
(0.001)
-0.001*
(0.001)
-0.043***
(0.003)
-0.008
(0.006)
0.030***
(0.008)
Yes
964
19962006
(3)
-0.761
(1.178)
1.795***
(0.341)
-0.429
(0.653)
-0.213
(0.224)
-0.250***
(0.058)
0.782***
(0.193)
0.106
(0.219)
0.437***
(0.048)
5.582***
(0.636)
1.291**
(0.518)
-0.527
(0.878)
Yes
2,328
20072010
(4)
-0.112***
(0.028)
-1.959***
(0.495)
-0.423
(0.971)
-0.955**
(0.422)
0.132*
(0.074)
0.155
(0.185)
0.101
(0.184)
-0.044
(0.141)
-0.150
(0.560)
-0.342
(1.097)
3.937**
(1.542)
Yes
964
19962006
(5)
-0.003*
(0.002)
-0.002*
(0.001)
-0.003
(0.002)
0.000
(0.001)
0.000**
(0.000)
-0.000
(0.000)
0.000
(0.000)
-0.000***
(0.000)
-0.007***
(0.002)
-0.010***
(0.001)
0.010***
(0.002)
Yes
2,328
20072010
(6)
-0.005***
(0.001)
-0.015***
(0.003)
-0.003
(0.003)
-0.004***
(0.001)
0.001***
(0.000)
-0.002**
(0.001)
0.002**
(0.001)
-0.000
(0.000)
-0.024***
(0.002)
0.001
(0.004)
0.021***
(0.005)
Yes
964
1996-2006
(7)
0.580**
(0.241)
0.239*
(0.145)
0.219
(0.252)
-0.283***
(0.084)
0.014
(0.021)
-0.090
(0.067)
-0.025
(0.071)
-0.058***
(0.018)
-1.435***
(0.270)
0.069
(0.168)
-0.437
(0.331)
Yes
2,328
20072010
(8)
-0.006
(0.014)
0.417*
(0.250)
-0.313
(0.427)
0.795***
(0.209)
-0.050
(0.040)
-0.272***
(0.105)
0.052
(0.110)
-0.011
(0.070)
2.663***
(0.263)
-0.389
(0.535)
-0.893
(0.688)
Yes
964
9.22***
0.077
15.33***
0.393
12.22***
0.200
5.69***
0.046
16.89***
0.101
25.36***
0.394
14.12***
0.026
21.12***
0.149
25
Interest
rate risk
Interest
rate risk
Table 5 Moderating effects- narrow period analysis
The tables represent the results of the bank fixed-effects with year fixed effects estimates of equation (5). The dependent variable
RISK is either total risk or idiosyncratic risk or systematic risk or interest rate risk. Total risk is the standard deviation of the bank’s
weekly stock returns over a year (eq. 1). Idiosyncratic risk is calculated as the variance of εit in eq.(2). Systematic risk is the coefficient
of Rmt, i.e. βm in the two-factor market model as represented by eq.(2). Interest rate risk is the coefficient of RIt, i.e. βI in the twofactor market model as represented by eq.(2). Standard errors are reported in parentheses. Superscripts*, **, *** indicate
statistical significance at 10%, 5%, and 1% levels, respectively.
Panel A: Traditional off-balance sheet activities
Charter ×
Contingent
Asset quality ×
Contingent
Intercept
Year fixed effects
Number of
observation
F-test
Adjusted R2
Total
risk
Total
risk
Systematic
risk
Systematic
risk
Idiosyncratic
risk
Idiosyncratic
risk
Interest
rate risk
19962006
(1)
-0.009
20072010
(2)
-0.071***
1996-2006
2007-2010
1996-2006
2007-2010
(3)
-0.562
(4)
-0.233
(5)
0.007
(6)
-0.047**
19962006
(7)
0.110
Interest
rate
risk
20072010
(8)
-0.127
(0.020)
0.033***
(0.027)
0.021**
(0.610)
1.033
(0.218)
5.398**
(0.014)
0.016***
(0.018)
0.019***
(1.520)
-1.841*
(2.340)
-1.890
(0.010)
0.012***
(0.002)
Yes
2,228
(0.009)
0.024***
(0.007)
Yes
921
(3.937)
0.248
(0.637)
Yes
2,228
(2.387)
-0.219
(1.647)
Yes
921
(0.006)
0.010***
(0.001)
Yes
2,228
(0.007)
0.025***
(0.004)
Yes
921
(1.087)
-0.460*
(0.265)
Yes
2,228
(1.190)
-0.473
(0.889)
Yes
921
17.16***
0.17
92.42***
0.62
30.70***
0.39
6.94***
0.14
21.88***
0.22
69.96***
0.60
7.06***
0.04
14.81***
0.23
Panel B: Market related (derivatives) off-balance sheet activities
Charter × derivatives
Asset quality ×
derivatives
Intercept
Year fixed effects
Number of observation
F-test
Adjusted R2
Total
risk
Total
risk
Systematic
risk
Systematic
risk
Idiosyncratic
risk
Idiosyncratic
risk
Interest
rate risk
19962006
(1)
-0.187
(0.118)
0.035
20072010
(2)
0.094***
(0.030)
0.042
19962006
(3)
-11.398***
(2.091)
-26.528
20072010
(4)
12.130***
(2.875)
9.797
19962006
(5)
0.061
(0.042)
0.016
20072010
(6)
0.084***
(0.025)
0.071
19962006
(7)
16.588**
(8.847)
-11.134
Interest
rate
risk
20072010
(8)
5.718
(6.393)
-3.529
(0.122)
0.013***
(0.003)
Yes
2328
(0.178)
0.031***
(0.008)
Yes
964
(53.762)
-1.364*
(0.819)
Yes
2328
(12.586)
4.059***
(1.563)
Yes
964
(0.048)
0.010***
(0.002)
Yes
2328
(0.075)
0.021***
(0.005)
Yes
964
(12.375)
-0.378
(0.339)
Yes
2328
(14.224)
-0.794
(0.691)
Yes
964
0.077
0.395
0.217
0.047
0.100
0.402
0.026
0.149
26
Table 6 Moderating effects- narrow period analysis
The tables represent the results of the bank fixed-effects with year fixed effects estimates of equation (6). The dependent variable
RISK is either total risk or idiosyncratic risk or systematic risk or interest rate risk. Total risk is the standard deviation of the bank’s
weekly stock returns over a year (eq. 1). Idiosyncratic risk is calculated as the variance of εit in eq.(2). Systematic risk is the coefficient
of Rmt, i.e. βm in the two-factor market model as represented by eq.(2). Interest rate risk is the coefficient of RIt, i.e. βI in the twofactor market model as represented by eq.(2). Standard errors are reported in parentheses. Superscripts*, **, *** indicate
statistical significance at 10%, 5%, and 1% levels, respectively.
Panel A: Traditional off-balance sheet activities
Contingent
× Tier1
Charter ×
Tier1
Asset quality
× Tier1
Intercept
Year fixed
effects
Number of
observations
F-test
Adjusted R2
Total
risk
Total
risk
Systematic
risk
Systematic
risk
Idiosyncratic
risk
Idiosyncratic
risk
Interest
rate risk
19962006
(1)
0.016
20072010
(2)
-0.006
1996-2006
2007-2010
1996-2006
2007-2010
(3)
-0.243
(4)
0.626**
(5)
0.019
(6)
-0.023
19962006
(7)
0.408
Interest
rate
risk
20072010
(8)
0.232
(0.039)
0.001
(0.033)
-0.048
(0.313)
0.092**
(0.299)
0.264**
(0.025)
0.011
(0.020)
-0.036
(0.857)
-0.275
(4.122)
-1.049
(0.046)
0.013
(0.135)
0.055**
(0.046)
0.062
(0.115)
0.235
(0.033)
0.002
(0.084)
0.057**
(0.219)
0.810
(0.925)
2.140
(0.022)
0.013**
(0.003)
Yes
(0.025)
0.022
(0.016)
Yes
(0.251)
3.292*
(1.766)
Yes
(0.325)
1.064
(3.081)
Yes
(0.015)
0.011**
(0.004)
Yes
(0.028)
0.023**
(0.010)
Yes
(1.448)
-0.855
(0.665)
Yes
(4.033)
-0.254
(0.306)
Yes
2,228
921
2,228
921
2,228
921
2,228
921
16.24***
0.16
86.31***
0.60
31.96***
0.39
6.00***
0.13
20.05***
0.22
70.92***
0.58
6.77***
0.04
13.75***
0.23
Panel B: Market related (derivatives) off-balance sheet activities
Derivatives×
Tier1
Charter × Tier1
Asset quality ×
Tier1
Intercept
Year fixed effects
Number of
observations
F-test
Adjusted R2
Total
risk
Total
risk
Systematic
risk
Systematic
risk
Idiosyncratic
risk
Idiosyncratic
risk
Interest
rate risk
19962006
(1)
-0.121
20072010
(2)
-0.000
19962006
(3)
-12.404***
20072010
(4)
-2.300
19962006
(5)
0.060
20072010
(6)
-0.013
19962006
(7)
1.726***
Interest
rate
risk
20072010
(8)
0.702
(0.134)
-0.028
(0.042)
0.007
(0.011)
-0.100
(0.127)
0.087*
(1.338)
5.344
(13.400)
11.209*
(1.524)
0.575
(18.153)
9.209
(0.069)
-0.021
(0.030)
-0.009
(0.008)
-0.069
(0.087)
0.070**
(0.467)
-7.180*
(4.203)
0.053
(2.384)
7.756
(9.012)
0.065
(0.019)
0.011*
(0.006)
Yes
2,328
(0.046)
0.027*
(0.015)
Yes
964
(6.400)
0.343
(1.871)
Yes
2,328
(7.567)
4.682**
(2.243)
Yes
964
(0.014)
0.007*
(0.004)
Yes
2,328
(0.028)
0.019**
(0.010)
Yes
964
(2.029)
-1.139*
(0.601)
Yes
2,328
(3.718)
-0.162
(1.116)
Yes
964
0.076
0.395
0.207
0.045
0.101
0.401
0.027
0.147
27