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Transcript
A Framework to Monitor Systemic Risk
G-20 Conference on Financial Systemic Risk
Sep. 27-28, 2012
Tobias Adrian, Dan Covitz, Nellie Liang
The views expressed herein are solely the author’s, and do not reflect those of the
Federal Reserve Bank of New York, the Federal Reserve Board or its staff. All
information presented here is publicly available.
Outline
 New regulatory structure from the Dodd-Frank Act
 Lessons learned
 Framework for monitoring systemic risk
 Data and implementation challenges
Systemic Risk Framework – Adrian, Covitz, Liang - 2
DFA and Financial Stability
• Stronger emphasis on pre-emptive policies
• Stronger capital and liquidity standards for SIFIs, bank and designated
non-banks
• Infrastructure: FMUs and OTC derivatives reform
• Limits on crisis management, ex post policies
• New resolution regime
• Stronger limits on guarantees, liquidity provision
• Tighter standards could push activities into the shadows
• DFA did not reform wholesale short-term funding markets
• Maturity transformation without deposit insurance or direct access to
lender of last resort will continue
 Systemic risk remains and will build with financial cycles
Systemic Risk Framework – Adrian, Covitz, Liang - 3
Lessons from the Crisis about Systemic Risk
•
•
•
•
•
•
Ensuring the safety and soundness of individual firms does not ensure
financial stability
Need to broaden focus from individual firms to potential effects on the
broader financial system and economy
• Systemic risk externalities via direct and indirect interconnections
amplify distress
Nonfinancial sector leverage also increases systemic risk
Shadow banking without government backstops is subject to run-like
coordination failures
Shadow banking affects core financial institutions
• Implicit and explicit support from core institutions
Systemic risk builds up during periods of low volatility
• Regulators need to be forward looking
• Risk measurement problems and accounting can obscure risk taking
Systemic Risk Framework – Adrian, Covitz, Liang - 4
Process for Monitoring Systemic Risk
• Motivated by research on amplification mechanisms
o Bernanke and Gertler (1989), Kyotaki and Moore (1997), (Geanakoplos (2003), Allen and
Gale (2000), Adrian and Shin (2010), Brunnermeier and Pedersen (2009), He and
Krishnamurthy (2012), Adrian and Boyarchenko (2012)
• Pre-emptive assessment process:
1. Identify possible shocks
2. Assess vulnerabilities (structural or cyclical):
• Amplification channels that could transmit and amplify possible
shocks
• Could disrupt financial intermediation and impair real economic
activity
• Explicit recognition that cannot forecast shocks and triggers
• Focus on vulnerabilities helps to identify micro- and macroprudential
policy responses
Systemic Risk Framework – Adrian, Covitz, Liang - 5
Stylized Framework for Systemic Risk Monitor
• Systemic risk is a marked increase in
price of risk P
• P is increasing in shocks s and
vulnerabilities V
• Goal is to measure V
o Could be determined by intermediary
funding constraints that depend on past
shocks
• Policy trade-off
– Reduction in V raises the price of risk when
shocks are low, but reduces systemic risk
Systemic Risk Framework – Adrian, Covitz, Liang - 6
Conceptual Framework for
Monitoring and Policy Responses
• Monitoring indicates the extent to which shocks might trigger systemic events
o Monitoring informs us about exposures to changes in the price of risk
o Sharp increases in the price of risk can generate systemic risk
• Policy tradeoff between the price of risk and systemic risk
o Higher price of risk today may reduce build-up of systemic risk
• Macroprudential policies
o
Structural – capital surcharge, “through the cycle” haircuts
o
Cyclical –countercylical capital buffer, stress tests, underwriting standards, monetary policy
Systemic Risk Framework – Adrian, Covitz, Liang - 7
Broad Monitoring Framework
1.
SIFIS (bank and nonbank) and FMUs
Firms are systemically important if their distress or failure could disrupt the
functioning of the broader financial system and inflict harm on the real
economy
2.
Shadow Banking
Shadow banking provides maturity and credit transformation without public
sources of backstops and pose systemic risks because of interconnections to
other financial institutions
3.
Nonfinancial Sector
Greater leverage amplifies negative shocks and imposes losses on the
financial sector, increasing the likelihood of an adverse feedback loop
through credit provision
Systemic Risk Framework – Adrian, Covitz, Liang - 8
1. SIFIs and FMUs
• Default risk
– Capital and leverage ratios; off-balance sheet commitments
– Stress test results (CCAR) – best forward-looking measure
– Market-based measures
• CDS, sub-debt bond spreads
• Stock prices, price to book, market equity capitalization, market betas
• Liability risk: runs and funding squeezes, cross border
• Systemic importance
– Size, interconnectedness, complexity, and critical services
– Market-based measures of systemic risk – CoVaR, SES, DIP
• Adrian and Brunnermeier (2008), Huang, Zhou, Zhu (2009), Acharya et al (2010)
Systemic Risk Framework – Adrian, Covitz, Liang - 9
Monitoring SIFIs: Example
Post-stress Tier 1 Common ratio in the Supervisory Stress Scenario (%)
Systemic Risk Framework – Adrian, Covitz, Liang - 10
Monitoring SIFIs: Example
Abnormal Stock Returns of CCAR 2012 Firms
Systemic Risk Framework – Adrian, Covitz, Liang - 11
Monitoring SIFIs: Example
Assets and Liabilities
Systemic Risk Framework – Adrian, Covitz, Liang - 12
Monitoring SIFIs: Example
Market-based Systemic Risk Measures
Systemic Risk Framework – Adrian, Covitz, Liang - 13
Monitoring SIFIs: Example
Interconnectedness of CCPs, Dealers, and non-dealers in CDS
Source: Celso Brunetti and Michael Gordy, "Monitoring Counterparty credit risk and
interconnectedness in CDS trade repository data" mimeo June 2012.
Systemic Risk Framework – Adrian, Covitz, Liang - 14
2. Shadow Banking
• Potential for Destabilizing Drops in Asset Prices
o Shadow banking could inflate asset valuations in booms and amplify asset price crashes in busts
o Price and non-price measures of potential bubbles, extremely low volatility
• Leverage Cycle, Maturity Mismatch, and Run Risk
o Leverage in the financial system (including on and off balance sheet exposures)
o Maturity mismatch, non-deposit short-term liabilities
o Activities not backed by government backstops: MMFs, cash pools, securities lending / repo
activities, prime brokerage
o Nonbank financial firms – finance companies, insurers, asset managers
• Risk Transformation and New Products
Systemic Risk Framework – Adrian, Covitz, Liang - 15
Monitoring Shadow Banking: Example
Credit Spreads and Issuance
Systemic Risk Framework – Adrian, Covitz, Liang - 16
Monitoring Shadow Banking: Example
Money Market Funds
Systemic Risk Framework – Adrian, Covitz, Liang - 17
Monitoring Shadow Banking: Example
Shadow Banking Liabilities
Shadow Liabilities
Trillions
25
Trillions
25
Shadow Liabilities
Net Shadow Liabilities
20
20
Bank Liabilities
15
15
10
10
5
5
0
1990
0
1994
1998
2002
2006
Source: Flow of Funds
Systemic Risk Framework – Adrian, Covitz, Liang - 19
2010
Monitoring Shadow Banking: Example
Commercial Paper and Repo Financing
CP and Repo Financing
Billions
3000
Billions
1250
ABCP
(right axis)
Triparty Repo
(left axis)
2500
1000
750
2000
1500
500
Financial CP
(right axis)
Source: FRBNY and Federal Reserve Board
Systemic Risk Framework – Adrian, Covitz, Liang - 18
Jul-11
Jan-11
Jul-10
Jan-10
Jul-09
Jan-09
Jul-08
Jan-08
Jul-07
Jan-07
Jul-06
Jan-06
Jul-05
Jan-05
Jul-04
250
Jan-04
1000
3. Real Economy Monitoring
• Nonfinancial sector risk
o Leverage of nonfinancial sector—households, businesses, governments
• Effect of financial sector on economic activity
o Indicators of macro-economy vulnerability to financial risks
o Balance sheet capacity of financial institutions, collateral quality
Systemic Risk Framework – Adrian, Covitz, Liang - 20
Real Economy Monitoring: Example
Nonfinancial Sector Credit-to-GDP Ratio
Systemic Risk Framework – Adrian, Covitz, Liang - 21
Real Economy Monitoring: Example
Private Nonfinancial Sector Credit-to-GDP Ratio
Systemic Risk Framework – Adrian, Covitz, Liang - 22
Data Challenges


Information needs are immense – detailed data and complex interlinkages
Measurement can change behavior
•
Supervisory stress tests
Detailed data - loans to businesses and households, securities held, revenues, operational risks
Trading book – sensitivities to shocks
Counterparty exposures - build network of interconnections in trading book
Potential to simulate effects of specific firm failures
o
o
o
o
•
Current stress test challenges
SCAP 2009 – revealed weak practices
Subsequent CCARs led to substantial improvements
How to avoid resource allocation to guessing supervisor models and focused on own risk management
o
o
o
•
Nonbank SIFIs and shadow banking
Finance companies, insurers, broker-dealers, asset managers
o
•
•
•
o
In designation process, can ask firms for data
New data for MMFs, and new report forms for hedge funds and private equity funds
But need market-wide data on interconnections
Repo – tri-party, bilateral – and CDS data not yet available
Systemic Risk Framework – Adrian, Covitz, Liang - 23
Measurement and Implementation
Challenges
• Measurement:
o Are market indicators forward looking? (VIX, stock prices, CDS)
o Data needs for interconnections are immense and require cooperation
among regulatory agencies, domestic and foreign, for confidential data
(exposures, repo transactions)
o Firms often don’t have the data required for systemic risk analysis
o Is network analysis well-suited for economic interlinkages?
o Measures may be hard to construct in real time (credit-to-GDP gap)
o Measurement may change behavior (stress tests)
• Implementation:
o Requires much greater cooperation and a change in mindset
among policymakers
o Difficult given governance and policy uncertainty