To mitigate systemic risk, some regulators have advocated the greater use of centralized counterparties (CCPs) to clear Over-The-Counter (OTC) derivatives trades. Regulators should be cognizant that large banks active in the OTC derivatives market do not hold collateral against all the positions in their trading book and the paper proves an estimate of this under-collateralization. Whatever collateral is held by banks is allowed to be rehypothecated (or re-used) to others. Since CCPs would require all positions to have collateral against them, off-loading a significant portion of OTC derivatives transactions to central counterparties (CCPs) would require large increases in posted collateral, possibly requiring large banks to raise more capital. These costs suggest that most large banks will be reluctant to offload their positions to CCPs, and the paper proposes an appropriate capital levy on remaining positions to encourage the transition.

Recent regulatory efforts, especially in the U.S. and Europe, are aimed at reducing moral hazard so that the next financial crisis is not bailed out by tax payers. This paper looks at the possibility that central counterparties (CCPs) may be too-big-to-fail entities in the making. The present regulatory and reform efforts may not remove the systemic risk from OTC derivatives but rather shift them from banks to CCPs. Under the present regulatory overhaul, the OTC derivative market could become more fragmented. Furthermore, another taxpayer bailout cannot be ruled out. A reexamination of the two key issues of (i) the interoperability of CCPs, and (ii) the cost of moving to CCPs with access to central bank funding, indicates that the proposed changes may not provide the best solution. The paper suggests that a tax on derivative liabilities could make the OTC derivatives market safer, particularly in the transition to a stable clearing infrastructure. It also suggests reconsideration of a "public utility" model for the OTC market infrastructure.

The financial crisis of 2007–2009 exposed the weaknesses of the global over-the-counter (OTC) derivatives market such as limited transparency regarding risk exposures, poor counterparty risk management practices, and the risk of contagion arising from interconnectedness in this market. In the aftermath of the financial crisis, regulators introduced worldwide legislative and regulatory changes aimed at increasing the transparency and stability of the financial markets. In this book, Dr. Olga Lewandowska explores those novel regulatory solutions and their impact. The main focus is on central counterparty (CCP) clearing that became mandatory for OTC derivatives under the new regulatory paradigm. In four research papers, she analyzes CCP from different risk perspectives and based on four diverse research methods. Her book offers a comprehensive assessment of the risk-reduction potential of the CCPs, their implications for the financial markets, and the practical challenges in the implementation of the recent financial market reforms.

The netting of OTC derivatives trades, known as 'compression', reduces systemic risk in financial markets by minimising counterparty exposures between large financial institutions, in particular the large dealer banks. We present here a framework for compression in the OTC derivatives market for interest rate swaps. We minimise the total net counterparty exposure by partially or fully unwinding existing swap trades and determine the degree of compression obtained as a function of the number of trades, the number of participating parties and the number of risk constraints. We do this using both linear programming (LP) and quadratic programming (QP) approaches. We are able to separately quantify the benefit of bilateral and multilateral netting. We also compare the tendency of both LP and QP approaches to favour full unwinds of existing trades versus partial unwinds. We calculate the performance of both optimisation approaches by calculating their average reduction in counterparty risk by simulating over large numbers of randomly generated trade sets. We show that significant compression can be achieved, and find that LP approaches are preferable as they are generally computationally faster and produce solutions with more full unwinds than QP approaches.