No competing financial interests have affected the conduct or results of this research.
This paper suggests two new heuristic algorithms for optimization of Value-at-Risk (Va R).
This paper is based on the research project conducted by Nicklas Larsen during his visit to the University of Florida in Spring 2000.
This research project has not been conducted in the framework of any legal agreement between the University of Florida and Algorithmic, Inc.
Investors and financial regulators are increasingly aware of climate-change risks. helped design the research and draft the manuscript.
So far, most of the attention has fallen on whether controls on carbon emissions will strand the assets of fossil-fuel companies. led the project, from research design through modelling to writing the manuscript.
Financial institutions have for many years sought measures which cogently summarise the diverse market risks in portfolios of financial instruments.
This quest led institutions to develop Value-at-Risk (Va R) models for their trading portfolios in the 1990s.
Numerical experiments showed that the algorithms are efficient and can handle a large number of instruments and scenarios.
However, calculations identified a deficiency of Va R risk measure, compared to CVa R.