Estimating Stochastic Differential Equations Using Repeated Eigenfunction Estimation and Neural Networks

Ruhi Tuncer ()

No 12-5, GIAM Working Papers from Galatasaray University Economic Research Center

Abstract: We propose identifying the drift and the diffusion functions of an ergodic scalar stochastic differential equation using repeated eigenfunction estimation. The transition density will be estimated in a new way involving Kolmogorov’s backward equation, neural networks and functions of our choice. Martingale estimating functions will be used to obtain asymptotic properties.

Keywords: Stochastic Differential Equation; Kolmogorov’s backward Equation; Infinitesimal Generator; Eigenfunctions; Transition Density; Neural Networks; Martingale Estimating Functions (search for similar items in EconPapers)
Pages: 15 pages
Date: 2012-10-24
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Persistent link: https://EconPapers.repec.org/RePEc:ris:giamwp:2012_005

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