The implied volatility surface (IVS) is a fundamental building block in computational finance. We provide a survey of methodologies for constructing such surfaces. We also discuss various topics which can influence the successful construction of IVS in practice: arbitrage-free conditions in both...

Two of the most important areas in computational finance: Greeks and, respectively, calibration, are based on efficient and accurate computation of a large number of sensitivities. This paper gives an overview of adjoint and automatic differentiation (AD), also known as algorithmic...

A credit-linked note (CLN) on a tranche of the CDX index (partially) protects the holder against default losses in that tranche. The holder receives a specified redemption amount at note maturity. The note is priced using market spread quotes for a matching CDS on this tranche

Local volatility models are widely used to manage many exotic options in a way consistent with available market prices of vanilla options. Once calibrated, a local volatility grid can be used in numerical methods such as PDE or Monte Carlo to price and hedge exotic options consistently with...

In this article we suggest a new method for solutions of stochastic integrals where the dynamics of the variables in integrand are given by some stochastic differential equation. We also propose numerical simulation of stochastic differential equations which is based on iterated integrals method...

We present a simple method for “inverting” a volatility smile: that is, generating a CDF and inverse CDF given a discrete set of implied volatilities. The method is based on constructing a piece-wise linear CDF that is guaranteed to exactly reprice any non-arbitrageable input volatilities....

Unlike tranches of synthetic CDOs, that depend only on the defaults of the underlying securities, tranches of cashflow CDOs also depend on the interest cash flows from the coupons of the securities. Whilst fast, accurate, (semi-)analytic methods exist for pricing synthetic CDO tranches (Hull and...

Artificial Neural Networks (ANNs) have recently been proposed as accurate and fast approximators in various derivatives pricing applications. ANNs typically excel in fitting functions they approximate at the input parameters they are trained on, and often are quite good in interpolating between...

Recently there has been some interest in the credit risk literature in models which involve stopping times related to excursions. The classical Black-Scholes-Merton-Cox approach postulates that default may occur, either at or before maturity, when the firm's value process falls below a critical...

In this contribution, we study structural models of defaultable bond pricing in which default occurs at the first time a relevant process either reaches the default boundary or has spent continuously (or cumulatively) a fixed time period below that threshold. Unlike first-passage time...