1. OTC Derivatives Reforms: Considerations and Challenges ESRC Conference on Diversity in Macroeconomics Mark Manning, Reserve Bank of Australia

2. Overview Policy motivation An initial contribution −Methodology −Exposures and collateral demands −Financial stability under different clearing structures Policy messages and future work

3. 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

4. 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

5. 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

6. Basic set-up Two agent types: banks (b) and investors (i) Core/Periphery network structure Draw derivative positions from a transaction matrix

7. Static Analysis: Exposure and Collateral

8. BanksInvestorsCCPsSystem Bilateral0.620.31-0.93 Split0.420.310.100.83 Separate CCPs0.150.130.280.56 Single CCP0.120.100.220.44 Total Exposures

11. 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

12. 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

13. 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

15. 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

16. 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