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Monte Carlo simulation

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…

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…

VAR: history or simulation?

Greg Lambadiaris, Louiza Papadopoulou, George Skiadopoulos and Yiannis Zoulis assess theperformance of historical and Monte Carlo simulation in calculating VAR, using data from theGreek stock and bond market. They find that while historical simulation…

A true test for value-at-risk

The three classic approaches for measuring portfolio value-at-risk do not compare like with like, argues Richard Sage. Here he presents a test portfolio to highlight the differences between calculation methods

How to spot a VaR cheat

Traders can use weaknesses in VaR measurement to make it appear that they are not taking any risks. Brett Humphreys exposes how easily this can be done

Project risk: improving Monte Carlo value-at-risk

Cashflows from projects and other structured deals can be as complicated as we are willing to allow, but the complexities of Monte Carlo project modelling need not complicate value-at-risk calculation. Here, Andrew Klinger imports least-squares valuation…

Margin notes

Brett Humphreys explains how to measure and manage margin risk, an often-overlooked – yet often-significant – risk exposure

Asian basket spreads and other exotic averaging options

Giuseppe Castellacci and Michael Siclari of OpenLink introduce a class of exotic options that simultaneously generalises both Asian and basket options. They develop approximate analytic models for real-time pricing of complex instruments that average…

Waiting for guidance

South Korea's banks have made huge strides in implementing risk management systems over the past few years, but Basel II is not yet a driving force, with banks waiting for the Korean regulator to publish local guidelines.

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