Is the behavior of the stocks in our portfolio close to their behavior during the most recent crisis? How close is the strategy of hedge fund A to the strategy of hedge fund B? In which proportions do we invest in a given universe of stocks so that the resulting portfolio matches as much as possible the strategy of fund C?
All of these questions are essential to finance and they have one feature in common: measuring distances between random quantities. Problems of this kind have been explored for many years in areas other than finance. In A Probability Metrics Approach to Financial Risk Measures, the field of probability metrics and risk measures are related to one another and applied to finance for the first time, revealing groundbreaking new classes of risk measures, finding new relations between existing classes of risk measures, and providing answers to the question of which risk measure is best for a given problem. Applications include optimal portfolio choice, risk theory, and numerical methods in finance.