Option Pricing in Fractional Brownian Markets by Stefan Rostek

Option Pricing in Fractional Brownian Markets by Stefan Rostek

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Zusammenfassung

Mandelbrot and van Ness (1968) suggested fractional Brownian motion as a parsimonious model for the dynamics of ?nancial price data, which allows for dependence between returns over time. Starting with Rogers(1997) there is an ongoing dispute on the proper usage of fractional Brownian motion in option pricing theory.

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Option Pricing in Fractional Brownian Markets by Stefan Rostek

Mandelbrot and van Ness (1968) suggested fractional Brownian motion as a parsimonious model for the dynamics of ?nancial price data, which allows for dependence between returns over time. Starting with Rogers(1997) there is an ongoing dispute on the proper usage of fractional Brownian motion in option pricing theory. Problems arise because fractional Brownian motion is not a semimartingale and therefore no arbitrage pricing cannot be applied. While this is consensus, the consequences are not as clear. The orthodox interpretation is simply that fractional Brownian motion is an inadequate candidate for a price process. However, as shown by Cheridito (2003) any theoretical arbitrage opportunities disappear by assuming that market p- ticipants cannot react instantaneously. This is the point of departure of Rostek's dissertation. He contributes to this research in several respects: (i) He delivers a thorough introduction to fr- tional integration calculus and uses the binomial approximation of fractional Brownianmotion to give the reader a ?rst idea of this special market setting.
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ISBN 13 9783642003301
ISBN 10 3642003303
Titel Option Pricing in Fractional Brownian Markets
Autor Stefan Rostek
Serie Lecture Notes In Economics And Mathematical Systems
Buchzustand Nicht verfügbar
Bindungsart Paperback
Verlag Springer
Erscheinungsjahr 2009-05-04
Seitenanzahl 137
Hinweis auf dem Einband Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
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