EconPapers    
Economics at your fingertips  
 

Bayesian Pricing of European Call Options on the WIG20 Index

Maciej Kostrzewski ()
Additional contact information
Maciej Kostrzewski: AGH University of Science and Technology, Cracow, Poland

Chapter 10 in FindEcon Monograph Series: Advances in Financial Market Analysis, 2007, vol. 3, pp 153-164 from University of Lodz

Abstract: According to modern financial literature we assume that observed time series are discrete realizations of continuous processes, strictly speaking Itó processes. The processes are strong solutions of stochastic differential equations' (SDE) (see Karatzas and Shreve 1988). They are nowadays essential devices for modelling financial time series. They are used in term-structure modelling, pricing derivative securities, constructing hedging strategies and so on. The main aim of the chapter is to present the results of Bayesian option pricing. Models considered in the chapter are mostly known and are often applied in practice. The exception is the Extended Ornstein-Uhlenbeck model which is given by non-autonomous SDE.

Keywords: Bayesian pricing of European call options; WIG20 index (search for similar items in EconPapers)
JEL-codes: C01 E02 F00 G00 (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.repec.uni.lodz.pl/RePEc/files/findec/2007/2007_No_3_Ch_10.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ann:findec:book:y:2007:n:03:ch:10:mon

Access Statistics for this chapter

More chapters in FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making from University of Lodz Contact information at EDIRC.
Bibliographic data for series maintained by Piotr Wdowiński ().

 
Page updated 2025-04-06
Handle: RePEc:ann:findec:book:y:2007:n:03:ch:10:mon