Examination of Portfolio Currency Risk Estimation by Means of Lévy Models
Bibliographic Data
| ID | 6109273 |
|---|---|
| Authors | Tomáš Tichý (0000-0002-6503-5330, VSB - Technical University of Ostrava, corresponding author) |
| Year | 2010 |
| Volume | 58 |
| Issue | 4 |
| Pages | 504-521 |
| Publication date | 2010-08-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Politická ekonomie (JOURNAL) |
| Journal identifiers | ISSN: 0032-3233 • E-ISSN: 2336-8225 |
| Publisher | Prague University of Economics and Business (PUBLISHER • CZ) |
| DOI | 10.18267/j.polek.744 |
| OpenAlex | W2313385093 |
| Language | EN |
| Citations received | 1 |
| References cited | 16 |
Financial risk modeling, measuring, and managing are an inherent part of management in financial institutions. It is also an important step within the setting of optimal level of capital eligible to cover risk exposures. A significant portion of capital is usually assigned to cover the risk of unexpected changes in FX rates. FX rates (the returns) commonly exhibit significant skewness and relatively huge kurtosis. In this paper, we apply subordinated LĂŠvy models coupled together by ordinary elliptical copula functions in order to estimate the FX rate risk of normalized portfolio. Selected models are applied in order to estimate the risk ex-post, as well as ex-ante. The models are also compared to the more standard assumption of the joint normal distribution. Although the results for both types of modeling are quite different and LĂŠvy measure is ignored, suggested models deliver us improved risk estimation
Actuarial science · Basel II · Capital requirement · Copula (linguistics) · Econometrics · Economics · Estimation · Ex-ante · Expected shortfall · Financial economics · Kurtosis · Portfolio · Project portfolio management · Risk management · Risk measure · Skewness · Spectral risk measure · Statistics · Value at risk · Credit Risk and Financial Regulations · Finance · Financial Risk and Volatility Modeling · Mathematics · Stochastic processes and financial applications
| Citations per year | 0.11 |
|---|---|
| Citation span | 2017 - 2017 (1) |
| Highly cited | No |