An increasingly popular field of study at universities and an essential skill for investment bank employees, mathematical finance has changed dramatically in recent years, but its roots remain in stochastic calculus. Problems and Solutions in Mathematical Finance: Volume 1 provides a comprehensive explanation of stochastic calculus and probability theory focusing on their relationship with mathematical finance. Quantitative analysts Dr. Eric Chin and Dian Nel and Professor Sverrir Olafsson portray stochastic calculus' role in generating partial differentiation equations for pricing options and constructing probability measures in conjunction with martingale theory. Mathematical and computational finance rely on computational intelligence, numerical methods, and computer simulations to make trading, hedging, and investment decisions, to determine the risk of those decisions, and to define price derivatives.
- Includes chapter-by-chapter introduction of the fundamental tenets, essential definitions, and detailed explanations needed to solve financial problems
- Offers advice from experts in price testing methodologies, model calibration, energy markets, hedging in incomplete markets, and risk management
Problems and Solutions in Mathematical Finance: Volume 1 functions as either an independent information text or a study supplement for students and practitioners eager to recover the basics of mathematical finance.