Abstract
We develop an eigenfunction expansion based value iteration algorithm to solve discrete time infinite horizon optimal stopping problems for a rich class of Markov processes that are important in applications. We provide convergence analysis for the value function and the exercise boundary, and derive easily computable error bounds for value iterations. As an application we develop a fast and accurate algorithm for pricing callable perpetual bonds under the CIR short rate model.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 122-128 |
| Number of pages | 7 |
| Journal | Statistics and Probability Letters |
| Volume | 85 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2014 |
Funding
We thank the anonymous referee and the Editor very much for offering suggestions that helped to improve this paper. The research of the first author was supported by the Chinese University of Hong Kong Direct Grant for Research with project code 4055005. The research of the second author was supported by the National Science Foundation under grant DMS-1109506 .
Keywords
- Callable perpetual bonds
- Eigenfunction expansions
- Optimal stopping
- Symmetric Hunt processes
- Value iterations
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty