Name
Abstract | ||
|---|---|---|
In this article we present independent component analysis (ICA) applied to the concept of value at risk (VaR) modelling. The use of ICA decomposition enables to extract components with particular statistical properties that can be interpreted in economic terms. However, the characteristic of financial time series, in particular the nonstationarity in terms of higher order statistics, makes it difficult to apply ICA to VaR right away. This requires using adequate ICA algorithms or their modification taking into account the statistical characteristics of financial data. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-40728-4_69 | ICANN |
Keywords | Field | DocType |
Value at Risk, Independent Component Analysis, financial time series analysis | Econometrics,Data mining,Computer science,Higher-order statistics,Independent component analysis,Value at risk | Conference |
Volume | ISSN | Citations |
8131 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryszard Szupiluk | 1 | 38 | 8.97 |
| Piotr Wojewnik | 2 | 20 | 6.32 |
| Tomasz Zabkowski | 3 | 32 | 11.28 |