Given the random nature of future events on financial markets, the field of stochastics (prob- ability theory, statistics and the theory of stochastic processes) obviously plays an important role in quantitative risk management. In addition, techniques from convex analysis and opti- mization and numerical methods are frequently being used. In fact, part of the challenge in quantitative risk management stems from the fact that techniques from several existing quanti- tative disciplines are drawn together. The ideal skill-set of a quantitative risk manager includes concepts and techniques from such fields as mathematical finance and stochastic process theory, statistics, actuarial mathematics, econometrics and financial economics, combined of course with non-mathematical.
