Risk analysis of financial activity has long been the central role of banks, insurance companies and institutions. Risk management is fundamental when evaluating exposure to a host of factors involving financial operations and regulations hingeing on a number of industries depend on precise tools for determining, with the utmost accuracy, the level of risk in any given financial activity.
The Basel Accords established policy for the banking sector is an example of such assessment. They dictate that firms must employ quantitative tools to such as accurate risk assessment. The most noteworthy of which being the Value at Risk tool.
As a result of this impetus we've seen a growing body of research from accademia on risk assessment concerning financial calculations, starting with the precise axiomatic definition as conveyed in the celebrated work of P. Artzner, F. Delbaen, J.-M. Eber e D. Heath[1], in 1999. Their main objective was to put forth an in-depth analysis of the principle properties of risk assessment. In it, they considered important financial concepts, such as 'diversification'.
More recently, research has centered around a single query: Can we build risk assessment models that take in new information as it comes available to financial institutions? The answer, simply put, is yes.
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