On a New Fluctuation–Dissipation Theorem for Degenerate Stationary Flows
Masaya Matsuura ()
Additional contact information
Masaya Matsuura: University of Tokyo
Methodology and Computing in Applied Probability, 2003, vol. 5, issue 3, 369-387
Abstract:
Abstract The theory of KM2O-Langevin equations for stochastic processes (or more generally, flows in inner product spaces) have been developed in view of applications to time series analysis (e.g., Okabe and Nakano, 1991; Okabe, 1999, 2000; Okabe and Matsuura, 2000). In Klimek et al. (2002) and Matsuura and Okabe (2001, 2003), we have investigated degenerate flows, which is important in the analysis of time series obtained from deterministic dynamical systems. As a continuation, we shall in this paper derive an efficient algorithm by which the minimum norm coefficients of KM2O-Langevin equations are explicitly obtained in degenerate cases. The obtained results have close relations to the calculations of conditional expectations such as nonlinear predictors of stochastic processes (Matsuura and Okabe, 2001). The method has also potential applications to financial mathematics.
Keywords: degenerate flow; stationarity; minimum norm property; fluctuation-dissipation theorem; generalized inverse (search for similar items in EconPapers)
Date: 2003
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1023/A:1026291304997 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:metcap:v:5:y:2003:i:3:d:10.1023_a:1026291304997
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009
DOI: 10.1023/A:1026291304997
Access Statistics for this article
Methodology and Computing in Applied Probability is currently edited by Joseph Glaz
More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().