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Large time and small noise asymptotic results for mean reverting diffusion processes with applications
| Content Provider | Semantic Scholar |
|---|---|
| Author | Callen, Jeffrey L. Govindaraj, Suresh |
| Copyright Year | 2000 |
| Abstract | Summary. We use the theory of large deviations to investigate the large time behavior and the small noise asymptotics of random economic processes whose evolutions are governed by mean-reverting stochastic differential equations with (i) constant and (ii) state dependent noise terms. We explicitly show that the probability is exponentially small that the time averages of these process will occupy regions distinct from their stable equilibrium position. We also demonstrate that as the noise parameter decreases, there is an exponential convergence to the stable position. Applications of large deviation techniques and public policy implications of our results for regulators are explored. |
| Starting Page | 401 |
| Ending Page | 419 |
| Page Count | 19 |
| File Format | PDF HTM / HTML |
| DOI | 10.1007/PL00004090 |
| Volume Number | 16 |
| Alternate Webpage(s) | http://www-2.rotman.utoronto.ca/facbios/file/Callen-Govindaraj-Xiu2000.pdf |
| Alternate Webpage(s) | https://doi.org/10.1007/PL00004090 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
