Time-Deformation Modeling of Stock Returns Directed by Duration Processes

Dingan Feng, Peter X.-K. Song and Tony S. Wirjanto

Econometric Reviews, 2015, vol. 34, issue 4, 480-511

Abstract: This paper proposes a new time-deformation model for stock returns sampled in transaction time and directed by a generalized duration process. Stochastic volatility in this model is driven by an observed duration process and a latent autoregressive process. Parameter estimation in the model is carried out by using a method of simulated moments (MSM) due to its analytical tractability and numerical stability for the proposed model. Simulations are conducted to validate the choice of moments used in the formulation of MSM. Both simulation and empirical results indicate that the proposed MSM works well for the model. The main empirical findings from the analysis of IBM transaction return data include: (i) the return distribution conditional on the duration process is not Gaussian, even though the duration process itself can marginally serve as a directing process; (ii) the return process is highly leveraged; (iii) longer trade duration tends to be associated with higher return volatility; and (iv) the proposed model is capable of reproducing a return process whose marginal density function is close to that of the empirical return process.

Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/07474938.2013.808478 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:emetrv:v:34:y:2015:i:4:p:480-511

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/LECR20

DOI: 10.1080/07474938.2013.808478

Access Statistics for this article

Econometric Reviews is currently edited by Dr. Essie Maasoumi

More articles in Econometric Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by ().