Name
Abstract | ||
|---|---|---|
The paper presents a method for analyzing coupled time series using Markov models in a domain where the state space is immense. To make the parameter estimation tractable, the large state space is represented as the Cartesian product of smaller state spaces, a paradigm known as factorial Markov models. The transition matrix for this model is represented as a mixture of the transition matrices of the underlying dynamical processes. This formulation is know as mixed memory Markov models. Using this framework, the author analyzes the daily exchange rates for five currencies-British pound, Canadian dollar, Deutschmark, Japanese yen, and Swiss franc-as measured against the US dollar |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1109/CIFER.1998.690077 | Computational Intelligence for Financial Engineering |
Keywords | Field | DocType |
Markov processes,foreign exchange trading,matrix algebra,parameter estimation,state-space methods,time series,British pound,Canadian dollar,Cartesian product,Deutschmark,Japanese yen,Swiss franc,US dollar,coupled time series analysis,currencies,daily exchange rates,dynamical processes,factorial Markov models,large state space,mixed memory Markov models,parameter estimation,transition matrix | Econometrics,Applied mathematics,Markov process,Continuous-time Markov chain,Markov property,Markov model,Computer science,Markov chain,Balance equation,Variable-order Markov model,Markov kernel | Conference |
ISSN | ISBN | Citations |
2380-8454 | 0-7803-4930-X | 3 |
PageRank | References | Authors |
0.60 | 0 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Constantine Papageorgiou | 1 | 1897 | 403.34 |