Advances in Mathematical Finance by Michael C. Fu, Robert A. Jarrow, Ju-Yi Yen, Robert J Elliott

By Michael C. Fu, Robert A. Jarrow, Ju-Yi Yen, Robert J Elliott

This self-contained quantity brings jointly a set of chapters by means of one of the most individual researchers and practitioners within the fields of mathematical finance and monetary engineering. proposing cutting-edge advancements in conception and perform, the Festschrift is devoted to Dilip B. Madan at the celebration of his sixtieth birthday.

Specific themes lined include:

* thought and alertness of the Variance-Gamma process

* Lévy technique pushed fixed-income and credit-risk types, together with CDO pricing

* Numerical PDE and Monte Carlo methods

* Asset pricing and derivatives valuation and hedging

* Itô formulation for fractional Brownian motion

* Martingale characterization of asset rate bubbles

* software valuation for credits derivatives and portfolio management

Advances in Mathematical Finance is a worthwhile source for graduate scholars, researchers, and practitioners in mathematical finance and fiscal engineering.

Contributors: H. Albrecher, D. C. Brody, P. Carr, E. Eberlein, R. J. Elliott, M. C. Fu, H. Geman, M. Heidari, A. Hirsa, L. P. Hughston, R. A. Jarrow, X. Jin, W. Kluge, S. A. Ladoucette, A. Macrina, D. B. Madan, F. Milne, M. Musiela, P. Protter, W. Schoutens, E. Seneta, okay. Shimbo, R. Sircar, J. van der Hoek, M.Yor, T. Zariphopoulou

Show description

Read Online or Download Advances in Mathematical Finance PDF

Similar insurance books

Life Insurance Risk Management Essentials

The purpose of the booklet is to supply an outline of danger administration in existence insurance firms. the focal point is twofold: (1) to supply a huge view of the several issues wanted for hazard administration and (2) to supply the mandatory instruments and methods to concretely follow them in perform. a lot emphasis has been placed into the presentation of the ebook in order that it provides the idea in an easy yet sound demeanour.

Versicherungsmathematik

(Zu Versicherungsmathematik eleven. ) In diesem "höheren" Band der Versicherungsmathematik haben wir uns durch geeignete Stoffauswahl vor allem das Ziel gesteckt, die Ver­ sicherungsmathematiker davon zu überzeugen, daß wichtige technische Probleme der Versicherungspraxis nur durch Verwendung der \Vahr­ scheinlichkeitstheorie und Resultate aus der mathematischen Statistik gelöst werden können.

Financial Risk and Derivatives: A Special Issue of the Geneva Papers on Risk and Insurance Theory

Monetary chance and Derivatives offers a superb representation of the hyperlinks that experience constructed in recent times among the speculation of finance on one hand and assurance economics and actuarial technology at the different. Advances in contingent claims research and advancements within the educational and functional literature facing the administration of economic dangers replicate the shut relationships among assurance and concepts in finance.

Additional info for Advances in Mathematical Finance

Example text

Math. , 7:51– 53,1936. 10. B. Madan, P. C. Chang. The variance gamma process and option pricing. European Finance Review, 2:79–105, 1998. The Early Years of the Variance-Gamma Process 19 11. B. Madan and F. Milne. Option pricing with VG martingale components. Mathematical Finance, 1(4): 19–55,1991. 12. B. Madan and E. Seneta. The profitability of barrier strategies for the stock market. 45, 39 pp, University of Sydney, 1981. 13. B. Madan and E. Seneta. Residuals and the compound Poisson process.

A robust alternative to the normal distribution. Canadian Journal of Statistics, 10:89–102, 1982. 34 Michael C. Fu 23. L. McLeish, Monte Carlo Simulation and Finance. Wiley, 2005. 24. P. Protter. Stochastic Integration and Differential Equations, 2nd edition. Springer-Verlag, 2005. 25. C. Ribeiro, and N. Webber. Valuing path-dependent options in the VarianceGamma model by Monte Carlo with a gamma bridge. Journal of Computational Finance, 7:81–100, 2004. 26. K. Sato. L´evy Processes and Infinitely Divisible Distributions.

Of a standard normal distribution. The distribution of X is thus a normal with mixing on the variance, is symmetric about μ, and has the same form irrespective of the size of time increment t. It is long-tailed relative to the normal in the sense that its kurtosis value 3λσ 4 3+ (θ + σ 2 λ)2 exceeds that of the normal (whose kurtosis value is 3). When the NCP distribution is symmetrized about the origin by putting μ = 0, it has a simple real characteristic function of closed form. The NCP process from the structure (3) clearly has jump components (the ξi s are regarded as “shocks” arriving at Poisson rate), and through the Brownian process add-on θ1/2 b(t) in (3), has obviously a Gaussian component.

Download PDF sample

Rated 4.67 of 5 – based on 35 votes