A method of pricing derivatives by simulating the evolution of the underlying variable (or variables) many times over. The average outcome of the simulation is an approximation of the derivative’s value. Monte Carlo is useful in the valuation of complex derivatives for which exact analytical solutions have not been found, but it can be very computationally intensive. Monte Carlo simulation can also be applied to a portfolio of instruments, rather than a single instrument, to estimate the value-at-risk (VaR) of that portfolio.
Commodity trading and risk management is a subject that is necessarily complicated, and is becoming more so. The Energy Risk Glossary seeks to disentangle and clarify the jargon by providing definitions of commonly used energy and commodity market terms.
These include definitions related to a variety of underlying energy products, as well as technical terms about the many instruments and benchmarks used by energy market participants.
Many of the most recent terms to have been added to our glossary stem from the actions of regulators since the 2008 global financial crisis. The onset of rules, such as the US Dodd-Frank Act and European Market Infrastructure Regulation, has markedly increased the cost and complexity associated with commodity trading. Perhaps they have also increased the need for a handy reference guide such as this.
The glossary is extensively cross-referenced, making for easy and thorough searches. We hope you find the latest edition of the Energy Risk Glossary to be a useful resource.
More on Risk Management
ABSTRACT This paper shows that traditional measures of bond systematic risk based on unadjusted past returns have very large downward biases. After we develop an improved method for calculating the market...
ABSTRACT This paper studies the approximation of extreme quantiles of random sums of heavy-tailed random variables, or, more specifically, subexponential random variables. A key application of this approximation...
ABSTRACT Because publicly available measures of deposit runoff risk are scarce, regulators' models to measure interest rate risk in the banking book are based on very coarse assumptions about the allocation...
ABSTRACT This paper analyzes and quantifies the idea of model risk in the environment of internal model building. We define various types of model risk including estimation risk, model risk in distribution...
Sign up for Risk.net email alerts
Research chief is sceptical about end of oil indexation in European gas
Mexico's energy reform may lead to closer ties with adjacent US states
Swap dealers playing a guessing game while complying with CFTC rules
Bill Perkins believes rising demand and reduced risk warehousing will create opportunities for natural gas traders: video
There are no comments submitted yet. Do you have an interesting opinion? Then be the first to post a comment.