A method for pricing the credit valuation adjustment of unlisted companies
Abstract
Estimating the credit valuation adjustment (CVA) for unlisted companies is a challenging issue because it is not possible to estimate the risk neutral default probability from either the credit default swap (CDS) par spread or equity stock. This paper proposes a calibration method that easily estimates the market risk premium, which is added to the internal rating model of unlisted companies to obtain a risk neutral default probability. The method is applied to price the CVA of a portfolio of swaps for unlisted counterparties using the advanced method approach, and the results are benchmarked using the Bank for International Settlements (BIS) approach for illiquid counterparties. Last, the robustness tests confirm the reliability of the calibration method, both for its use in risk management and accounting.
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Author's Biography
Matteo Formenti holds a MSc in Economics and a PhD in Finance with a theoretical and empirical thesis on asset pricing theory and the role of market risk perception drive inefficient prices. His thesis was awarded as the J. Doukas Best Doctoral Award given by the European Financial Management Association. He previously worked for a major consulting company developing the methodology of back-testing applied to the internal model for counterparty credit risk. He is currently working in the Group Finance department of a major Italian banks with a focus on the behavioural models for managing liquidity and interest rate risk in the banking book. He is Visiting Professor of market risk at MIP (Milan Politecnique) and full professor of Asset Management at LIUC (University of Castellanza) since 2014.
Citation
Formenti, Matteo (2019, March 1). A method for pricing the credit valuation adjustment of unlisted companies. In the Journal of Risk Management in Financial Institutions, Volume 12, Issue 2. https://doi.org/10.69554/JIOU3221.
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