This paper describes a consistent and arbitrage-free pricing methodology for bespoke CDO tranches. The proposed method is a multi-factor extension to the (Li 2009) model, and it is free of the known flaws in the current standard pricing method of base correlation mapping. This method assigns a...

We find that firm-level variance risk premium, estimated as the difference between option-implied and expected variances, has a prominent explanatory power for credit spreads in the presence of market- and firm-level risk control variables identified in the existing literature. Such a...

We devise simulation/regression numerical schemes for pricing the CVA on CDO tranches, where CVA stands for Credit Valuation Adjustment, or price correction accounting for the defaultability of a counterparty in an OTC derivatives transaction. This is done in the setup of a continuous-time...

We analyze the market price of counterparty risk and develop an arbitrage-free pricing valuation framework, inclusive of collateral mitigation. We show that the adjustment is given by the sum of option payoff terms, depending on the netted exposure, i.e. the difference between the on-default...

Credit default swaps (CDS) are unfunded, or the synthetic form of credit exposure, while bonds are fully funded, thus the cash form. Borrowing this industry jargon, credit valuation adjustment (CVA) would be seen synthetic, because it is defined as the present value of buying a default...

This paper empirically analyzes a particular type of notes observed in securitization transactions: combination notes. Combination notes are formed by combining parts of two or more tranches of securitization transactions, where one part usually consists of a share of the first loss piece. It is...

Modelling portfolio credit risk is one of the crucial challenges faced by financial services industry in the last few years. We propose the valuation model of collateralized debt obligations (CDO) based on copula functions with up to three parameters, with default intensities estimated from...