Presents inference and simulation of stochastic process in the
field of model calibration for financial times series modelled by
continuous time processes and numerical option pricing. Introduces
the bases of probability theory and goes on to explain how to model
financial times series with continuous models, how to calibrate
them from discrete data and further covers option pricing with one
or more underlying assets based on these models.
Analysis and implementation of models goes beyond the standard
Black and Scholes framework and includes Markov switching models,
Lévy models and other models with jumps (e.g. the telegraph
process); Topics other than option pricing include: volatility and
covariation estimation, change point analysis, asymptotic expansion
and classification of financial time series from a statistical
viewpoint.
The book features problems with solutions and examples. All the
examples and R code are available as an additional R package,
therefore all the examples can be reproduced.
