otc derivatives reforms: considerations and challenges

OTC Derivatives Reforms: Considerations and Challenges

ESRC Conference on Diversity in MacroeconomicsMark Manning, Reserve Bank of Australia

Overview

• Policy motivation• An initial contribution

− Methodology− Exposures and collateral demands− Financial stability under different clearing

structures• Policy messages and future work

Policy Motivation

• Fundamental changes to core financial markets− G20 financial reform agenda− Strengthen risk management; reduce

interconnectedness• Collateralisation and central clearing

− Trade-off between counterparty risk and liquidity risk

− Encumbrance; funding and liquidity• Assess implications for stability, market functioning

and real economic outcomes

Initial Contribution

• OTC Derivatives: Netting and Networks− Joint work with Alex Heath and Gerard Kelly

• Simulation approach− Static: Exposures and collateral demands− Dynamic: Financial stability

• Flexible, but stylised• Can examine a variety of clearing structures• Stylised ‘world’: network structure; balance

sheets

Links to Literature

• Duffie and Zhu (2011)− Model dealer exposures in alternative clearing

settings; consider fragmentation and un-netting• Macroeconomic Assessment Group on Derivatives

(2013)− Examine costs/benefits of G20 reforms: net long-

run impact on GDP • Duffie (2014)

− Model collateral demand in alternative clearing settings using bilateral CDS exposure data

Basic set-up

• Two agent types: banks (b) and investors (i)• Core/Periphery network structure• Draw derivative positions from a transaction matrix

Static Analysis: Exposure and Collateral

• Bilateral clearing:

• Central clearing, single CCP:

• Central clearing, separate CCPs:

• Mixed clearing:

• Split clearing: and

Banks Investors CCPs System

Bilateral 0.62 0.31 - 0.93

Split 0.42 0.31 0.10 0.83

Separate CCPs 0.15 0.13 0.28 0.56

Single CCP 0.12 0.10 0.22 0.44

Total Exposures

Changing the Size of the CoreExposure relative to notional outstanding

2 4 6 8 10 120

1

2

3

4

5

0

1

2

3

4

5

Number of banks

Single CCP

%

Separate CCPs

Bilateral

Split clearing

%

Changing the Directionality of the PeripheryExposure relative to notional outstanding

0 6 12 18 24 300

1

2

3

4

5

0

1

2

3

4

5

Number of directional investors

Single CCP

%

Separate CCPs

Bilateral

%

Dynamic Analysis: Networks (1)

Previous model extended by giving agents balance sheets• Banks and investors hold a composite ‘illiquid

asset’• Can be sold/transformed into a ‘liquid asset’ to

meet collateral needs• Liabilities comprise debt and equity for banks and

equity only for investors− Both banks and investors can default due to

illiquidity; banks can also default due to insolvency

Dynamic Analysis: Networks (2)

Models the dynamic interaction between derivative exposure and other balance sheet items under alternative clearing arrangements• Focus is on how price shocks are transmitted to

balance sheets and how they may trigger liquidity shortages or defaults

• Examines also the dynamics of collateral transformation

Simulation and Timeline

Monte Carlo simulation with 70 000 iterations. Seven steps:• Populate transaction matrix• Draw illiquid asset price change• Draw derivative price change• Calculate variation margin payment obligations• Sell/transform illiquid assets to obtain liquidity for

variation margin payments; could trigger default • Default could impose losses on others• Update balance sheets

Bank Default and Collateral CoverageExpected number of defaults

Bilateral

50.00 69.15 84.13 93.32 97.72 99.38 99.87 99.985

6

7

8

9

10

5

6

7

8

9

10

Coverage level (%)

Mixed clearing

Single CCP

No No

Policy Messages

• The appropriate scope of central clearing and collateralisation will depend on product and agent characteristics

• There is likely to be an ‘optimal’ level of collateralisation, which will vary with the structure of clearing arrangements

Future Work

• Economic significance of the results− Take the model to ‘real’ data

• Add richness to banks’ and investors’ balance sheets

• Endogenise pricing and agents’ trading choices