Monte Carlo simulation
Valid Assumptions Required: an analysis of VaR for energy markets
In this 10-part series, Brett Humphreys takes a fresh look at the widely used risk measure value-at-risk (VaR), urging risk managers to be more aware of the many assumptions that go into the calculation to produce the VaR number.
Fast correlation Greeks by adjoint algorithmic differentiation
Adjoint methods have recently been proposed as an efficient way to calculate risk through Monte Carlo simulation. Luca Capriotti and Mike Giles extend these ideas and show how adjoint algorithmic differentiation allows for fast calculation of price…
A rotationally invariant technique for rare event simulation
Because of their low probability, including extreme events in Monte Carlo calculations of the value-at-risk of a credit-risky portfolio requires many simulations. Here, Susanne Klöppel, Ranja Reda and Walter Schachermayer demonstrate a geometrically…
Calculation of variable annuity market sensitivities using a pathwise methodology
Under traditional finite difference methods, the calculation of variable annuity sensitivities can involve multiple Monte Carlo simulations, leading to high computational cost. A pathwise approach reduces this dramatically, while providing an unbiased…
Simulations with exact means and covariances
Attilio Meucci presents a simple method to generate scenarios from multivariate elliptical distributions with given sample means and covariances, and shows an application to the risk management of a book of options
Fast Monte Carlo Bermudan Greeks
In recent years, much effort has been devoted to improving the efficiency of the Libor market model. Matthias Leclerc, Qian Liang and Ingo Schneider extend the pioneering work of Giles & Glasserman (2006) and show how fast calculations of Monte Carlo…
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,…
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…
Speed tests
Counterparty Credit Risk
Valid Assumptions Required: Monte Carlo VaR
Brett Humphreys discusses the many decisions associated with the calculation of a Monte Carlo value-at-risk.
Beyond Black-Litterman in practice
In principle, the copula-opinion pooling (COP) approach extends the Black-Litterman methodology to non-normally distributed markets and views. However, the implementations of the COP framework presented so far rely on restrictive quasi-normal assumptions…
Computation methods - Smoking adjoints: fast Monte Carlo Greeks
Monte Carlo calculation of price sensitivities for hedging is often very time- consuming. Michael Giles and Paul Glasserman develop an adjoint method to accelerate the calculation. The method is particularly effective in estimating sensitivities to a…
Smoking adjoints: fast Monte Carlo Greeks
Monte Carlo calculation of price sensitivities for hedging is often very time-consuming. Michael Giles and Paul Glasserman develop an adjoint method to accelerate the calculation. The method is particularly effective in estimating sensitivities to a…
Back to the future
Current developments in exotic interest rate products push the demand for more sophisticatedinterest rate models. Here, Jesper Andreasen presents a new class of stochastic volatility multifactoryield curve models enabling quick calibration and efficient…
A credit loss control variable
Viktor Tchistiakov, Jeroen de Smet and Peter-Paul Hoogbruin explain and demonstrate how the efficiency of Monte Carlo simulation in valuing a portfolio of credit risky exposures is improved by the use of the Vasicek distribution as a control variable. An…
The Monte Carlo mindset
There is a rich seam to be mined in the provision of tools to calculate counterparty credit risk. Clive Davidson looks at what's on offer so far, and what could be coming on to the market.
Simulating spots
Abstract: The use of Monte Carlo simulation is becoming increasingly importantin energy trading and risk management. Here, Les Clewlow and ChrisStrickland present the first in a series of articles looking at the implementation of simulationtechniques and…
Operational and market risks of a regulated power utility
Victor Dvortsov and Ken Dragoon present an analytical method for including market and operational risks when estimating utility portfolio value-at-risk