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Quantitative analysis

Robust asset allocation under model risk

Financial investors often develop a multitude of models to explain financial securities' dynamics, none of which they can fully trust. Model risk (also referred to as ambiguity) prevents investors from using the classical framework of expected utility…

Pricing options on film revenue

This article illustrates two models for cumulative revenues from films, a time-changed gamma process and a compound Poisson process, and how these models can be used to price options. Don Chance, Eric Hillebrand and Jimmy Hilliard find that while both…

Managing diversification

Attilio Meucci introduces a diversification index that represents the effective number of bets in a portfolio. With this index, based on entropy and constrained principal component analysis, he performs mean-diversification management adjusted for…

Factor models for credit correlation

Stewart Inglis, Alex Lipton and Artur Sepp present an extension of the static factor model for pricing credit correlation products introduced by Lipton (2006) and detailed in Inglis & Lipton (2007)

Accelerated ensemble Monte Carlo simulation

Traditional vanilla methods of Monte Carlo simulation can be extremely time-consuming if accurate estimation of the loss distribution is required. Kevin Thompson and Alistair McLeod show that the ensemble Monte Carlo method, introduced here,…

Smile dynamics III

In two articles published in 2004 and 2005 in Risk, Lorenzo Bergomi assessed the structural limitations of existing models for equity derivatives and introduced a new model based on the direct modelling of the joint dynamics of the spot and the implied…

Error of VAR by overlapping intervals

When overlapping intervals in time series are used, volatility and price changes' percentiles are underestimated. Consequently, value-at-risk is also underestimated. Heng Sun, Izzy Nelken, Guowen Han and Jiping Guo measure the size of this underestimation

Joining the SABR and Libor models together

Fabio Mercurio and Massimo Morini propose a Libor market model consistent with SABR dynamics and develop approximations that allow for the use of the SABR formula with modified inputs. They verify that the approximations are acceptably precise, imply…

Robust asset allocation under model risk

Financial investors often develop a multitude of models to explain financial securities' dynamics, none of which they can fully trust. Model risk (also referred to as ambiguity) prevents investors from using the classical framework of expected utility…

Being two-faced over counterparty credit risk

A recent trend in quantifying counterparty credit risk for over-the-counter derivatives has involved taking into account the bilateral nature of the risk so that an institution would consider their counterparty risk to be reduced in line with their own…

Rates squared

Vladimir Piterbarg introduces a conveniently parameterised class of multi-factor quadratic Gaussian models, develops calibration formulas, and explains the advantages of this class of models over alternatives currently available for pricing and risk…

Component VAR for a non-normal world

It has become standard to account for non-normality when estimating portfolio value-at-risk, but there are few methods available to calculate the risk contributions of each component in a non-normal portfolio. Brian Peterson and Kris Boudt present a…

Juggling snowballs

Previous work on the valuation of cancellable snowball swaps in the Libor market model suggested the use of nested Monte Carlo simulations was needed to obtain accurate prices. Here, Christopher Beveridge and Mark Joshi introduce new techniques that…

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