Affiliation:
1. School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW 2522, Australia
Abstract
Abstract
In quantitative finance practice, model calibration is a key challenge. This is especially so when a local regime-switching model needs to be calibrated because designing an efficient and reliable algorithm to obtain local volatility values as a function of underlying price and time is important for the model to be successfully used in practice. Therefore, this paper proposes a new algorithm for calibrating local regime-switching models with observed option prices available for a particular market that is suitable for this type of model. The newly proposed algorithm is tested with calibrations performed on synthetic as well as real market data. Our empirical test results indicate that the algorithm has great potential to be used in financial risk management.
Publisher
Oxford University Press (OUP)
Subject
Applied Mathematics,Management Science and Operations Research,Strategy and Management,General Economics, Econometrics and Finance,Modelling and Simulation,Management Information Systems
Cited by
3 articles.
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