Option Pricing in Incomplete Markets


Book Description

This volume offers the reader practical methods to compute the option prices in the incomplete asset markets. The [GLP & MEMM] pricing models are clearly introduced, and the properties of these models are discussed in great detail. It is shown that the geometric L(r)vy process (GLP) is a typical example of the incomplete market, and that the MEMM (minimal entropy martingale measure) is an extremely powerful pricing measure. This volume also presents the calibration procedure of the [GLP \& MEMM] model that has been widely used in the application of practical problem




Theory of Incomplete Markets


Book Description

Theory of incompl. markets/M. Magill, M. Quinzii. - V.1.







Equilibrium Pricing in Incomplete Markets


Book Description

Given exogenously the price process of some asets, we constrain the price process of other assets, which are characterised by their final pay-offs. We deal with an incomplete market framework in a discrete time model and assume the existence of the equilibrium. In this setup, we derive restrictions on the state-price deflators and these restrictions do not depend on a particular choice of utility function. A stochastic volatility model is numerically investigated as an example. Our approach leads to an interval of admissible prices much better than the arbitrage pricing interval.




Indifference Pricing


Book Description

This is the first book about the emerging field of utility indifference pricing for valuing derivatives in incomplete markets. René Carmona brings together a who's who of leading experts in the field to provide the definitive introduction for students, scholars, and researchers. Until recently, financial mathematicians and engineers developed pricing and hedging procedures that assumed complete markets. But markets are generally incomplete, and it may be impossible to hedge against all sources of randomness. Indifference Pricing offers cutting-edge procedures developed under more realistic market assumptions. The book begins by introducing the concept of indifference pricing in the simplest possible models of discrete time and finite state spaces where duality theory can be exploited readily. It moves into a more technical discussion of utility indifference pricing for diffusion models, and then addresses problems of optimal design of derivatives by extending the indifference pricing paradigm beyond the realm of utility functions into the realm of dynamic risk measures. Focus then turns to the applications, including portfolio optimization, the pricing of defaultable securities, and weather and commodity derivatives. The book features original mathematical results and an extensive bibliography and indexes. In addition to the editor, the contributors are Pauline Barrieu, Tomasz R. Bielecki, Nicole El Karoui, Robert J. Elliott, Said Hamadène, Vicky Henderson, David Hobson, Aytac Ilhan, Monique Jeanblanc, Mattias Jonsson, Anis Matoussi, Marek Musiela, Ronnie Sircar, John van der Hoek, and Thaleia Zariphopoulou. The first book on utility indifference pricing Explains the fundamentals of indifference pricing, from simple models to the most technical ones Goes beyond utility functions to analyze optimal risk transfer and the theory of dynamic risk measures Covers non-Markovian and partially observed models and applications to portfolio optimization, defaultable securities, static and quadratic hedging, weather derivatives, and commodities Includes extensive bibliography and indexes Provides essential reading for PhD students, researchers, and professionals




Minimax Price Bounds in Incomplete Markets


Book Description

This paper develops an approach to tighten the bounds on asset pricing in an incomplete market that combines no-arbitrage pricing and preference-based pricing, and the approach is applied to call options without dynamic rebalancing. With the no-arbitrage pricing, it is straightforward to obtain the initial bounds, which are too wide to be of practical uses. By accepting that investors exhibit risk aversion from benchmark pricing kernels, it is possible to narrow the bounds considerably. Using the minimax deviation implicit in the parameters, one can restrict further the set of plausible values for call options on a stock.