Nonparametric estimation of structural models for high-frequency currency market data

Published

Journal Article

Empirical modeling of high-frequency currency market data reveals substantial evidence for nonnormality, stochastic volatility, and other nonlinearities. This paper investigates whether an equilibrium monetary model can account for nonlinearities in weekly data. The model incorporates time-nonseparable preferences and a transaction cost technology. Simulated sample paths are generated using Marcet's parameterized expectations procedure. The paper also develops a new method for estimation of structural economic models. The method forces the model to match (under a GMM criterion) the score function of a nonparametric estimate of the conditional density of observed data. The estimation uses weekly U.S.-German currency market data, 1975-90. © 1995.

Full Text

Duke Authors

Cited Authors

  • Bansal, R; Gallant, AR; Hussey, R; Tauchen, G

Published Date

  • January 1, 1995

Published In

Volume / Issue

  • 66 / 1-2

Start / End Page

  • 251 - 287

International Standard Serial Number (ISSN)

  • 0304-4076

Digital Object Identifier (DOI)

  • 10.1016/0304-4076(94)01618-A

Citation Source

  • Scopus