Title :
Importance sampling for indicator Markov chains
Author :
Giesecke, Kay ; Shkolnik, Alexander D.
Author_Institution :
Dept. of Manage. Sci. & Eng., Stanford Univ., Stanford, CA, USA
Abstract :
We consider a continuous-time, inhomogeneous Markov chain M taking values in {0,1}n. Processes of this type arise in finance as models of correlated default timing in a portfolio of firms, in reliability as models of failure timing in a system of interdependent components, and in many other areas. We develop a logarithmically efficient importance sampling scheme for estimating the tail of the distribution of the total transition count of M at a fixed time horizon.
Keywords :
Markov processes; estimation theory; importance sampling; investment; correlated default timing model; finance; firm portfolio; importance sampling scheme; indicator Markov chains; tail distribution estimation; Manganese; Markov processes; Monte Carlo methods; Portfolios; Q measurement; Random variables; Timing;
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2010 Winter
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-9866-6
DOI :
10.1109/WSC.2010.5678969
