Large time and small noise asymptotic results for mean reverting diffusion processes with applications
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.Get Access
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.
- Large time and small noise asymptotic results for mean reverting diffusion processes with applications
Volume 16, Issue 2 , pp 401-419
- Cover Date
- Print ISSN
- Online ISSN
- Additional Links
- Keywords and Phrases:Large deviations, Level-2-large deviations, Exit problems, Mean reverting stochastic differential equations.
- JEL Classification Numbers:C00, G10.
- Industry Sectors
- Author Affiliations
- A1. Stern School of Business, New York University, New York, NY 10012, USA(e-mail: email@example.com), US
- A2. Graduate School of Business, Columbia University, New York, NY 10027, USA (e-mail: firstname.lastname@example.org), US
- A3. School of Engineering, Princeton University, New Jersey, NJ 08554, USA(e-mail: email@example.com), US