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Stochastic Finance

  • Conference proceedings
  • © 2006

Overview

Editors:
  1. A. N. Shiryaev

    1. Steklov Mathematical Institute, Moscow, Russia

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  2. M. R. Grossinho

    1. ISEG, Universidade Técnica de Lisboa, Portugal

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  3. P. E. Oliveira

    1. Universidade de Coimbra, Portugal

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  4. M. L. Esquível

    1. FCT, Universidade Nova de Lisboa, Monte de Caparica, Portugal

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  • Highlights recent developments in stochastic methods and their applications to finance

  • Essential contribution to the literature in financial mathematics and financial engineering

  • Includes supplementary material: sn.pub/extras

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Table of contents (12 papers)

  1. Front Matter

    Pages I-XIV
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  2. Plenary and Invited Lectures

    1. Front Matter

      Pages 1-1
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    2. How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise

      • Yacine Aït-Sahalia, Per A. Mykland, Lan Zhang
      Pages 3-72

    3. Multipower Variation and Stochastic Volatility

      • Ole E. Barndorff-Nielsen, Neil Shephard
      Pages 73-82

    4. Completeness of a General Semimartingale Market under Constrained Trading

      • Tomasz R. Bielecki, Monique Jeanblanc°, Marek Rutkowski
      Pages 83-106

    5. Extremal behavior of stochastic volatility models

      • Vicky Fasen, Claudia Klüppelberg, Alexander Lindner
      Pages 107-155

    6. Capital Asset Pricing for Markets with Intensity Based Jumps

      • Eckhard Platen
      Pages 157-182

    7. Mortgage Valuation and Optimal Refinancing

      • Stanley R. Pliska
      Pages 183-196

    8. Computing efficient hedging strategies in discontinuous market models

      • Wolfgang J. Runggaldier, Sara Di Emidio
      Pages 197-212

    9. A Downside Risk Analysis based on Financial Index Tracking Models

      • Lian Yu, Shuzhong Zhang, Xun Yu Zhou
      Pages 213-236

  3. Contributed Talks

    1. Front Matter

      Pages 237-237
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    2. Modelling electricity prices by the potential jump-diffusion

      • Svetlana Borovkova, Ferry Jaya Permana
      Pages 239-263

    3. Finite dimensional Markovian realizations for forward price term structure models

      • Raquel M. Gaspar
      Pages 265-320

    4. Good Portfolio Strategies under Transaction Costs: A Renewal Theoretic Approach

      • Albrecht Irle, Jörn Sass
      Pages 321-341

    5. Power and Multipower Variation: inference for high frequency data

      • Jeannette H. C. Woerner
      Pages 343-364
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Keywords

About this book

Since the pioneering work of Black, Scholes, and Merton in the field of financial mathematics, research has led to the rapid development of a substantial body of knowledge, with plenty of applications to the common functioning of the world’s financial institutions.

Mathematics, as the language of science, has always played a role in the development of knowledge and technology. Presently, the high-tech character of modern business has increased the need for advanced methods, which rely to a large extent on mathematical techniques. It has become essential for the financial analyst to possess a high degree of proficiency in these mathematical techniques.

Editors and Affiliations

  • Steklov Mathematical Institute, Moscow, Russia

    A. N. Shiryaev

  • ISEG, Universidade Técnica de Lisboa, Portugal

    M. R. Grossinho

  • Universidade de Coimbra, Portugal

    P. E. Oliveira

  • FCT, Universidade Nova de Lisboa, Monte de Caparica, Portugal

    M. L. Esquível

Bibliographic Information

  • Book Title: Stochastic Finance

  • Editors: A. N. Shiryaev, M. R. Grossinho, P. E. Oliveira, M. L. Esquível

  • DOI: https://doi.org/10.1007/0-387-28359-5

  • Publisher: Springer New York, NY

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: Springer-Verlag US 2006

  • Hardcover ISBN: 978-0-387-28262-6Published: 24 October 2005

  • Softcover ISBN: 978-1-4419-3932-6Published: 29 October 2010

  • eBook ISBN: 978-0-387-28359-3Published: 03 June 2006

  • Edition Number: 1

  • Number of Pages: XIV, 364

  • Topics: Probability Theory and Stochastic Processes

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