Name
Title | ||
|---|---|---|
Multistage covariance approach to measure the randomness in financial time series analysis |
Abstract | ||
|---|---|---|
The paper presents a new method for randomness assessment in data with temporal structure. In this approach we perform multistage covariance analysis on several parts of the signal to synthesize information about variability and internal dependencies included in its structure. This allows us to identify deterministic cycles or to detect the level of randomness in signals what is an important issue for the design of transactional, prediction and filtration systems. To confirm validity of the proposed method we tested it on simulated and real financial time series. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-22000-5_63 | KES-AMSTA |
Keywords | Field | DocType |
important issue,temporal structure,multistage covariance analysis,new method,real financial time series,filtration system,deterministic cycle,multistage covariance approach,financial time series analysis,randomness assessment,internal dependency | Time series,Data mining,Computer science,Randomness tests,Noise detection,Finance,Analysis of covariance,Volatility (finance),Information representation,Randomness,Covariance | Conference |
Volume | ISSN | Citations |
6682 | 0302-9743 | 1 |
PageRank | References | Authors |
0.47 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryszard Szupiluk | 1 | 38 | 8.97 |
| Piotr Wojewnik | 2 | 20 | 6.32 |
| Tomasz Zabkowski | 3 | 32 | 11.28 |