Multilevel Stochastic Dynamic Process Models and Possible Applications in Global Financial Market Analysis and Surveillance

DOI

10.2991/jcis.2006.156How to use a DOI?

Keywords

stochastic dynamic process models, structural time series models, stochastic differential equations, multilevel trends, financial market analysis

Abstract

This paper advances Multilevel Stochastic Dynamic Process (MSDP) models as a new framework for modeling nonstationary and nonlinear time series and complex systems, and discuss possible applications of MSDP models in global financial market analysis and surveillance. Under the heterogeneous market hypothesis, different types of market participants react to the same information differently, characterized by their time horizons or dealing frequencies. Consequently financial prices exhibit multilevel trends, cycles, and seasonality, which provide the very basis for MSDP models. Both the discrete- and continuous-time MSDP models are constructed: Multilevel Structural Time Series (MSTS) with Unobserved Components (UC) and Multilevel Stochastic Differential Equations (MSDE).

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Heping Pan
PY  - 2006/10
DA  - 2006/10
TI  - Multilevel Stochastic Dynamic Process Models and Possible Applications in Global Financial Market Analysis and Surveillance
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SP  - 673
EP  - 676
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.156
DO  - 10.2991/jcis.2006.156
ID  - Pan2006/10
ER  -