Workshop: Risk Metrics for Project Finance

A nuanced approach to risk management

IST Member Richard Saldanha will be hosting a Workshop on Risk Metrics for Project Finance at the OR Society’s AI Summit in London July 5th


Quantitative methods used to analyse project finance forecast cash flows are employed in a largely ad-hoc manner. Well publicised deficiencies in commonly used metrics such as internal rate of return and multiple on invested capital suggest looking at other measures as well. In particular, in choosing between projects, different metrics often given alternative orderings of project attractiveness.

We present a more nuanced approach to risk management that considers a range of measures as well as attaching confidence intervals to inferred terminal values for those measures. Such an approach permits multiple risk scenarios to be defined thereby permitting broader views to be expressed. Our approach is outlined in a practical manner using representative data and tools built using the R software environment.

Workshop attendees should gain a practical understanding of how R might help them with their own analysis. In particular, we highlight the translation of a theoretical problem into R code, bespoke R package creation and the effective use of R graphics. We also show how R Markdown in R Studio can be used to combine code and output in an elegant manner.

This workshop is based partly on research carried out by Jack Buesnel in support of his MSc in Economics for Business Intelligence and Systems at the University of Bath in 2021. Jack’s work was jointly supervised by Richard Saldanha and Drago Indjic from Oxquant.

The Risk Metrics Project Finance workshop is happening on Tuesday 5th July 2022, 1.00-2.00pm.

For more information click here.

Richard SaldanhaRichard Saldanha is an expert in quantitative finance. He co-heads Oxquant, a management consulting business involved in AI/ML advisory work in finance and other knowledge industries. Richard has worked in quantitative finance for over 25 years and has held senior roles in both asset management and investment banking at major institutions in the City of London. His experience includes risk management, direct trading and investments. Richard holds a doctorate (DPhil) in Statistics from the University of Oxford. He is a Fellow and Chartered Statistician (CStat) of the Royal Statistical Society, a member of the Institution of Engineering and Technology (MIET) and a member of the Institute of Science and Technology (MIScT).