The Interplay between Market-Based Finance and the Credit Cycle
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The Interplay between Market-Based Finance
and the Credit Cycle
Sujit Kapadia, European Central Bank
Third ESRB Annual Conference: Panel on “Identifying and assessing
risks in the shadow banking system”
Frankfurt, 28 September 2018
Disclaimer: This presentation represents only the views of the authors. It does not necessarily reflect the views of the
European Central Bank or the Eurosystem.Increasing
Rubric importance of the non-bank financial sector
• Medium-term growth reflects its role in financing the euro area economy
Assets of the non-bank financial sector EA investment funds’ holdings of EA debt securities
Q1 1999 – Q1 2018; EUR trillion, percentage of total assets of Dec 2009, Dec 2014, Dec 2017; percentage of the outstanding
the financial sector stock of debt securities issued
investment funds (excl. money market funds) insurance corporations and pension funds
money market funds insurance corporations
Dec-09
Dec-14
financial vehicle corporations pension funds
Dec-17
remaining OFIs % of non-bank assets in total financial sector
assets (right-hand scale) 30%
Mar. 2018
50 € 43 trillion 60
25%
Dec. 2008
€ 23 trillion 50
40 20%
40
15%
30
Mar. 1999 Mar. 2003
€ 9 trillion € 12 trillion 30
10%
20
20
5%
10
10 0%
MFI debt securities OFI debt securities government debt non-financial
securities corporate debt
0 0
securities
1999 2001 2003 2005 2007 2009 2011 2013 2015 2017
Sources: ECB and ECB calculations.
Dec. 2000 Mar. 2006 Mar. 2008 Dec. 2009
investment funds MMFs IC and PF split FVCs Note: Debt securities issued by the MFI, government and NFC sectors are
measured as nominal amounts outstanding, while the holdings by funds are
Source: ECB (euro area accounts and balance sheet data of individual based on market value. The change in ratios over time thus partly reflects
sectors) and ECB calculations. 2 valuation effects. www.ecb.europa.eu ©Key financial stability vulnerabilities from market-based finance
Rubric
• Interconnectedness
− Direct exposures on the asset and liabilities side of funds and ICPFs (e.g.
EIOPA, 2017; Abad. et al. 2017; FSB, 2017)
− Common exposures across types of institutions (e.g. IMF, 2016; ECB, 2018)
− Ownership links of asset managers with banks and ICs (e.g. ECB, 2016)
• Liquidity and maturity risks (e.g. ECB, 2016; ESRB, 2016; EIOPA, 2017)
− Liquidity mismatch in some parts of the investment funds sector
− Maturity mismatch of assets and liabilities at ICs, guaranteed products
− Amplification of (market) liquidity shocks
• Solvency risk and leverage (e.g. ESRB, 2017; ECB, 2016; EIOPA, 2017)
− Excessive risk taking can undermine the solvency position of ICPFs
− Leverage and leverage-like exposures may add to pro-cyclicality at IFs
− Synthetic exposures can be leverage-like
• Less emphasis on interplays between market-based finance, the
wider credit cycle and the real economy
3Outline
Rubric
• Interplay of market-based finance with the credit cycle:
different dimensions
− supply of wholesale funding to banking sector
− direct financing of the real economy
− terms and conditions in wholesale markets which may set the tone of
the financial cycle
− links to wider debate on the global financial cycle (see also Rey, 2018)
• ECB research on micro behaviours linked to non-banks which
might contribute to procyclicality
• Policy thoughts and open issues
4Wholesale
Rubric funding (1): procyclical intra-financial system activity
Sectoral breakdown of UK debt, proportion of GDP
Q1 1987 – Q1 2011; per cent
Per cent
Household debt 600
Non-financial corporate debt
Government debt 500
Financial corporate debt
400
300
200
100
0
87 91 95 99 03 07 11
Source: ONS.
5 www.ecb.europa.eu ©Wholesale
Rubric funding (2): procyclicality in repo market activity
Repos & financial market open paper as a % of retail Evolution of outstanding repo and reverse repo amounts
deposits in the US in Europe
1995 – 2011; per cent June 2001 – Dec. 2016; EUR billion
Primary dealer repos and financial open reverse repos and repos
market paper
Net repos and financial open market Per cent 8,000
paper 100
7,000
90
80 6,000
70 5,000
60
4,000
50
3,000
40
30 2,000
20 1,000
10
0
0 06/01 06/03 06/05 06/07 06/09 06/11 06/13 06/15
1995 1997 1999 2001 2003 2005 2007 2009 2011
Source: Federal Reserve Board Flow of Funds and Bank Source: ICMA December 2016 European Repo Market Survey.
calculations.
6 www.ecb.europa.eu ©Direct
Rubric financing (1): the non-bank credit cycle
Source: FSB Global Shadow Banking Monitoring Report 2017
7 www.ecb.europa.eu ©Direct
Rubric financiing (2): insurance companies and real estate
•exposure
Insurance companies can gain real estate exposure directly (e.g. property,
mortgages and real estate securities) and indirectly through real estate funds
• Austria, Belgium, Finland and the Netherlands received a warning on residential real
estate vulnerabilities from the ESRB in 2016
Euro area insurers’ exposure to residential and commercial real estate as percentage of total assets
Q4 2017; per cent
Commercial
Residential
Unassigned
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
NL CY BE AT FI DE EA PT FR
Source: Solvency II data and ECB calculations.
8 www.ecb.europa.eu ©Terms
Rubric and conditions of transactions in financial markets
Secured lending margins and prices of MBS rated AAA at
issuance
Jun 1998 – Aug 2009; per cent
Per cent Index
0 110
10
100
20
90
30
40 80
50
Estimated average margin
(left-hand scale) 70
60
Average margin (left-hand
60
70 scale)
80 50
98 00 02 04 06 08
Source: Ellington Capital Group and JPMorgan. Taken from
Geanakoplos (2010): ‘Solving the present crisis and managing the
leverage cycle’, FRBNY Economic Policy Review.
9 www.ecb.europa.eu ©Outline
Rubric
• ECB research on micro behaviours linked to non-banks which
might contribute to procyclicality
− van der Veer, Levels, Lambert, Molestina Vivar, Weistroffer, Chaudron,
de Sousa van Stralen (2017), “Developing macroprudential policy for
alternative investment funds”, ECB Occasional Paper, No. 202,
November.
− Fache Rousovà and Giuzio (2018): Insurers’ investment strategies:
pro- or counter-cyclical? (mimeo, see also Box 5 in ECB FSR,
November 2017).
10Leverage
Rubric in the IFs and the flow-performance relationship (1)
Global figures suggest low leverage on average, but substantial leverage in a
few funds
Global hedge fund leverage figures by selected metrics Example: Leverage among Dutch alternative investment
September 2016, multiples; global averages funds (AIFs)
Average quarterly values in 2016; net exposure to net asset
value
Financial leverage 1.8 hedge funds
bond funds
Net synthetic
1.2
leverage mixed funds
funds of funds
Gross synthetic
5.8
leverage
equity funds
0.0 2.0 4.0 6.0 8.0 1 2 3 4 5 6 7 8 9 10 20 30 40 50
Source: 2016 IOSCO Hedge Funds Survey Sources: DNB, and DNB and ECB calculations.
Notes: Financial leverage accounts for cash and securities borrowings, while Notes: Data on net exposure and fund’s net asset value from the AIFMD reporting
synthetic leverage takes only derivatives exposures into account. Both financial framework. Substantial leverage is defined under the AIFMD as net exposure
and synthetic leverage should be added for total leverage 11 exceeding three times a fund’s net asset value. www.ecb.europa.eu ©Leverage
Rubric in the IFs and the flow-performance relationship (2)
Leverage increases sensitivity of outflows to poor past performance
x-axis: lagged fund performance in percent
y-axis: net fund flows in percent of lagged total net assets
unleveraged funds
leveraged funds
a) After positive past return, flows in leveraged funds are b) Investors in leveraged funds react more procyclically to
only marginally higher compared with unleveraged funds past negative returns than investors in unleveraged funds
1.4 0.0
1.2 -0.2
1.0 -0.4
0.8 -0.6
0.6 -0.8
0.4 -1.0
0.2 -1.2
0.0 -1.4
0 1 2 3 4 5 6 7 8 9 10 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0
Source: ECB calculation/estimation based on Lipper for Investment Management Database (Thomson Reuters).
Notes: The graphs shown are derived from a multivariate regression model analysing the sensitivity of fund flows to past fund returns between leveraged and unleveraged AIFs for
the period from 31 January 2006 to 28 February 2017(see Box 1 for details). In the positive range, the reaction between investors in leveraged and unleveraged funds is relatively
similar. A 10% increase in fund return is associated with an average inflow of 0.4% of total net assets in the following month (graph on the left). In the negative range, investors in
leveraged funds react more procyclically to negative performance than investors in unleveraged funds. For leveraged funds, a 10% decrease in fund performance is associated
with an average outflow of around 0.4%of a fund’s total net assets in the next period. For leveraged funds, a 10% decrease of performance would imply average outflows of
around 1.4%of lagged total net assets (graph on the right).
12 www.ecb.europa.eu ©Insurers’
Rubric investment strategies: pro- or counter-cyclical? (1)
(How) Do insurers react to price changes?
• The underlying drivers of a price change (rather than just the direction) determine
insurers’ investment behaviour
• (Bond) prices can change due to changes in risk-free rate or risk premia, which
have different effects on insurers’ equity
The value of equity decreases with a
The value of equity increases with a
decrease in risk-free rate in presence of
decrease in risk premium
negative duration gap
(Market value of assets increases, while liabilities
(Liabilities increase more than assets) are not affected)
• Risk bearing capacity decreases: sell • Risk bearing capacity increases: buy
assets (countercyclical) assets (procyclical)
Insurer capital view
The overall effect of risk-free rate and risk premia
depends on the relative size of the two factors
13 www.ecb.europa.eu ©Insurers’
Rubric investment strategies: pro- or counter-cyclical? (2)
Insurers’ pro-/counter-cyclicality over time
2009 Q1 – 2016 Q4
4
2
3
1.5
risk premia
2
1
1
.5
0
0
2009q1 2011q1 2013q1 2015q1 2017q1
mydate
Pro-cyclical - buying Pro-cyclical - selling
Risk-free rate Risk premia
Note: The average is weighted by holdings in our sample.
Source: ECB (SHS and CSDB) and authors’ calculations.
14
www.ecb.europa.eu ©Outline
Rubric
• Policy thoughts and open issues
15Policy Rubric thoughts Better data Wholesale funding dependence of banks • NFSR and LCR • Time-varying liquidity ratios for banks (BoE, 2011; ESRB, 2014) Macroprudential instruments for non-banks (ESRB, 2016) • Operationalise macroprudential leverage limits for AIFs (Article 25 AIFMD) • Develop globally comparable leverage measures for investment funds (FSB recommendations to IOSCO) • Operationalise existing liquidity tools for both AIFs and UCITS; consider additional macroprudential liquidity tools • Macroprudential instruments for insurers (EIOPA, 2018) Terms and conditions in wholesale markets • Minimum margins and haircut floors on both centrally cleared and non-centrally cleared derivatives and SFTs (FSB, 2015; Constâncio, 2016) • Time-varying countercyclical margins / haircuts (BoE, 2011; Gai, Haldane and Kapadia, 2011; ECB, 2016) 16 www.ecb.europa.eu ©
Open
Rubric issues
• Deeper understanding of the interplay between market-based finance, the wider
credit cycle and financing of the real economy
• Behavioural aspects and constraints of non-banks financial intermediaries which
may contribute to procyclicality
• Leverage and liquidity risk in the non-bank financial sector potentially amplifying
market stress
• Interplay between banking sector macoprudential policies and market-based
finance
• Macroprudential toolkit to address risks in the non-bank financial sector
17 www.ecb.europa.eu ©You can also read
