Abstract

We analyse the consequences of conservative portfolio compression, i.e., netting cycles in financial networks, on systemic risk. We show that the recovery rate in case of default plays a significant role in determining whether portfolio compression is potentially beneficial. If recovery rates of defaulting nodes are zero then compression weakly reduces systemic risk. We also provide a necessary condition under which compression strongly reduces systemic risk. If recovery rates are positive we show that whether compression is potentially beneficial or harmful for individual institutions does not just depend on the network itself but on quantities outside the network as well. In particular we show that portfolio compression can have negative effects both for institutions that are part of the compression cycle and for those that are not. Furthermore, we show that while a given conservative compression might be beneficial for some shocks it might be detrimental for others. In particular, the distribution of the shock over the network matters and not just its size.

Highlights

  • Portfolio compression is a mechanism in which multiple offsetting contracts are replaced by fewer contracts to reduce the gross exposure of each institution while keeping its net exposure unchanged

  • The European Securities and Markets Authority (ESMA) has published a consultation paper in 2020, see European Securities and Market Authority (2020), on post-trade risk reduction services (PTRR) of which portfolio compression is an important example. They ask: “Would you agree with the description of the benefits derived from PTRR services? Are there any missing? Could PTRR services instead increase any of those risks? Are there any other risks you see involved in using PTRR services?” there remains uncertainty about the risks of PTRR services such as portfolio compression

  • When does portfolio compression reduce systemic risk? We have identified three structural conditions that imply a reduction in systemic risk: no defaults on a compression network cycle in the non-compressed financial system, all nodes on the compression network cycle repay a larger proportion of their total payment obligations in the compressed system than in the non-compressed system and zero recovery rates

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Summary

INTRODUCTION

Portfolio compression is a mechanism in which multiple offsetting contracts are replaced by fewer contracts to reduce the gross exposure of each institution while keeping its net exposure unchanged. The new contracts that replace the old contracts, lead to a new network structure of exposures between the market participants It is not clear, a priori, what the consequences for systemic risk are—this is what we analyze here. The main contribution of this paper is to derive general theoretical results on the consequences of portfolio compression for systemic risk. We derive structural conditions for portfolio compression to be harmful or to reduce systemic risk in a sense that we will formally define in Definition 3.11. It establishes a relationship between systemic risk and the financial resilience of those nodes taking part in compression, the proportion of debt that they can repay and recovery rates in case of default.

Policy framework and related literature
The network of liabilities
Defining portfolio compression
Portfolio compression as an optimization problem
Payment obligations, margins, and liquidity buffer
Clearing the payment obligations
The zero recovery rate valuation function is defined by
Definition of default, reduction of systemic risk, and harmfulness of portfolio compression
CONSEQUENCES OF PORTFOLIO COMPRESSION FOR SYSTEMIC RISK
Who can be affected by portfolio compression?
Fundamental versus contagious defaults
Structural conditions for the consequences of portfolio compression
Defaults on the compression network cycle in the non-compressed network
Repayment proportions
Recovery rates
Compressing multiple cycles
Policy implications
Illustration of the theoretical results
CONCLUSION
Proofs of the results in Section 4
Full Text
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