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Financial risk management: models, history, and institution : models, history, and institution
Financial Risk Management started as one thing and has ended as another. I
took up this project with the primary aim of making risk measurement and
management techniques accessible, by working through simple examples,
and explaining some of the real-life detail of financing positions. I had
gotten fairly far along with it when the subprime crisis began and the world
changed.
I had already begun to appreciate the importance of liquidity and leverage
risks, which are even harder to measure quantitatively than market and
credit risks, and therefore all the more important in practice. In the subprime
crisis, liquidity and leverage risks were dominant. Had the subprime crisis
never occurred, they would have had an honorable place in this text. After
the crisis erupted, it became hard to think about anything else. To understand
why liquidity and leverage are so important, one needs to understand
the basic market and credit risk models. But one also needs to understand
the institutional structure of the financial system.
One aim of Financial Risk Management is therefore to bring together the
model-oriented approach of the risk management discipline, as it has evolved
over the past two decades, with economists’ approaches to the same issues.
There is much that quants and economists can learn from one another. One
needs to understand how financial markets work to apply risk management
techniques effectively.
A basic aim of the book is to provide some institutional and historical
context for risk management issues. Wherever possible, I’ve provided readers
with data from a variety of public- and private-sector sources, for the most
part readily accessible by practitioners and students. One of the blessings
of technology is the abundance of easily obtainable economic and financial
data. The particular phenomena illustrated by the data in the figures are
important, but even more so familiarity with data sources and the habit of
checking impressions of how the world works against data.
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