no code implementations • 14 Jan 2023 • Michael B. Giles, Abdul-Lateef Haji-Ali, Jonathan Spence
Associated risk measures, such as the value-at-risk of an underlying valuation adjustment, play an important role in managing these risks.
1 code implementation • 11 Dec 2019 • Michael B. Giles, Abdul-Lateef Haji-Ali
Computing risk measures of a financial portfolio comprising thousands of derivatives is a challenging problem because (a) it involves a nested expectation requiring multiple evaluations of the loss of the financial portfolio for different risk scenarios and (b) evaluating the loss of the portfolio is expensive and the cost increases with its size.
2 code implementations • 18 Aug 2017 • Michael B. Giles, Takashi Goda
In this paper we develop a very efficient approach to the Monte Carlo estimation of the expected value of partial perfect information (EVPPI) that measures the average benefit of knowing the value of a subset of uncertain parameters involved in a decision model.
Numerical Analysis
no code implementations • 4 May 2016 • Michael B. Giles, Mateusz B. Majka, Lukasz Szpruch, Sebastian Vollmer, Konstantinos Zygalakis
We show that this is the first stochastic gradient MCMC method with complexity $\mathcal{O}(\varepsilon^{-2}|\log {\varepsilon}|^{3})$, in contrast to the complexity $\mathcal{O}(\varepsilon^{-3})$ of currently available methods.
