Value-at-risk (VAR)
VAR versus expected shortfall
John Hull discusses the limitations of VAR and the relative advantages of an alternative measure, expected shortfall
Valid Assumptions Required: advanced volatility measures
In the next article of his VAR series, Brett Humphreys discusses more advanced methods for estimating volatility.
Operational VAR: meaningful means
Making the assumption that the distribution of operational loss severity has finite mean, Klaus Böcker and Jacob Sprittulla suggest a refined version of the analytical operational value-at-risk theorem derived in Böcker & Klüppelberg (2005), which…
Dealing with seller's risk
The risk of trade receivables securitisations comes from both the pool of assets and the seller of the assets. Vivien Brunel develops a model for securitisation exposures that deals with both risks, and analyses in detail the interplay between debtors'…
Valid Assumptions Required: Volatility
Brett Humphreys reviews the assumptions associated with calculating volatility based on historical data.
Valid Assumptions Required: Historical Simulation VaR
Brett Humphreys discusses the assumptions underlying the calculation of a VAR using the historical simulation methodology.
Valid Assumptions Required: examining forward curve assumptions
Brett Humphreys and Eric Raleigh review assumptions about the forward curve and the difference between relative and absolute dates.
Valid Assumptions Required: confidence level and holding period
In the second article of his series, Brett Humphreys examines the assumptions associated with selecting a confidence level and a holding period for a VaR calculation
Valid Assumptions Required: aggregation
In the first article of this series, in which Brett Humphreys questions some of the assumptions and decisions that go into the calculation of value-at-risk, he focuses on portfolio aggregation.
Operational risk - Operational VAR: a closed-form approximation
Klaus Bocker and Claudia Kluppelberg investigate a simple loss-distribution model for operational risk. They show that, when loss data is heavy-tailed (which in practice it is), a simple closed-form approximation for operational value-at-risk (VAR) can…
Time for multi-period capital models
Several financial institutions use single-period models to determine their credit portfolio loss distribution, calculate their loss volatility and assign economic capital.
Operational VAR: a closed-form approximation
Klaus Böcker and Claudia Klüppelberg investigate a simple loss distribution model for operational risk. They show that, when loss data is heavy-tailed (which in practice it is), a simple closed-form approximation for operational VAR can be obtained. They…
An economic capital approach for hedge fund structured products
Hedge fund structured products are increasingly favoured by investors. Banks have been swiftly developing their commercial offers to meet this demand. However, the theoretical framework for the risk management of these products remains little explored,…
Time for multi-period capital models
Several financial institutions use single-period models to determine their credit portfolio lossdistribution, calculate their loss volatility and assign economic capital. Here, Kevin Thompson,Alistair McLeod, Panayiotis Teklos and Shobhit Gupta…
Modelling counterparty credit exposure for credit default swaps
Modelling counterparty credit exposure for credit derivatives is more complicated than for non-credit products, since the reference credit and counterparty can exhibit positive default correlation. Here, Christian Hille, John Ring and Hideki Shimamoto…
A Markovian approach to modelling correlated defaults
Vladyslav Putyatin, David Prieul and Svetlana Maslova unveil a simple dynamic binomial credit model with a Poissonian mixing distribution to satisfy the constraints faced by financial institutions assessing their credit exposure in a consistent manner…