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Second, the same balance sheet information can be used to monitor leverage at the sectoral and
sub-sectoral level where leverage is defined as the ratio of total debt to equity and shareholders’
funds.
Third, an indication of the liquidity risk can be obtained by computing the ratio of short-term debt
to total assets or to total debt.
Fourth, to complement the set of indicators, it would be useful to construct an indicator of
maturity mismatch to gain a better understanding of the sector’s or sub-sectors’ exposure to
interest rate movement risk.
Missing from the set of indicators listed above are indicators related to credit and market risk. The
sectoral and sub-sectoral data which are currently available are too aggregated to be able to
construct credit and market risk indicators. While the annual statements and reports published by
public financial institutions provide often information of the credit and/or market risk of a range of
assets on their books, such information is typically available with a considerable lag so as to make
it largely useless in a rapidly evolving financial environment.
Missing is also an indicator of interconnectedness as, at the present time, the publicly available
information can only be analysed at a very aggregate level and provides only a picture, from the
MFIs’ perspective, of the connectedness of MFIs with NBFIs but not, from the NBFIs’ perspective,
of connectedness of NBFIs with themselves or with MFIs.
This is unfortunate as the lack of such data does not allow one to establish whether the rapid
expansion of the balance sheet of a particular NBFI sub-sector or the rapid growth in certain asset
class or financial activity results in increased risk for the sub-sector or the originator of the product
itself, for other financial sub-sectors of the NBFIs, the MFIs and/or real economy. Without good
information on the distribution of risk it is not possible to ascertain whether systemic risk has
increased or not.
Moreover, the broad sectoral monitoring should be accompanied by a monitoring of the evolution
of various asset classes or activities such as:
derivatives (using data from the BIS)
securitised assets (using data from AFEME)
repos (using data from ICMA)
securities lending (using data from Data Explorer)
CCP exposures (using data from the CCPs)
The latter set of data is useful for deriving an overall perspective on how the market is developing
- fast growth in a particular activity/asset class should be viewed as a red flag requiring further,
more detailed examination and potentially, discussions with industry expert.
In terms of individual institutions, we recommend to monitor closely the largest entities in each
sub-sector, provided such entities publish regularly balance sheet information. This
recommendation is based on Drehmann and Tarashev (2011) who note in their discussion of
simple indicators for monitoring systemic importance that “bank size is a reliable proxy of systemic
importance”.
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