1 |
Eberlein E and Keller U (1995). Hyperbolic distributions in finance, Bernoulli, 1, 281-299.
DOI
|
2 |
Embrechts P, McNeil A, and Straumann D (2002). Correlation and dependence in risk management: properties and pitfalls, Risk Management: Value at Risk and Beyond, 1, 176-223.
DOI
|
3 |
Eriksson A, Ghysels E, and Wang F (2009). The normal inverse Gaussian distribution and the pricing of derivatives, The Journal of Derivatives, 16, 23-37.
DOI
|
4 |
Godin F, Mayoral S, and Morales M (2012). Contingent claim pricing using a normal inverse Gaussian probability distortion operator, Journal of Risk and Insurance, 79, 841-866.
DOI
|
5 |
Goncu A and Yang H (2016). Variance-Gamma and normal-inverse Gaussian models: goodness-of-fit to Chinese high-frequency index returns, The North American Journal of Economics and Finance, 36, 279-292.
DOI
|
6 |
Hull J and White A (1998). Value at risk when daily changes in market variables are not normally distributed, Journal of Derivatives, 5, 9-19.
DOI
|
7 |
Joe H (1997). Multivariate Models and Multivariate Dependence Concepts, CRC Press, Boca Raton.
|
8 |
Jorion P (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed), McGraw-Hill, New York.
|
9 |
Kalemanova A, Schmid B, and Werner R (2007). The normal inverse Gaussian distribution for synthetic CDO pricing, The Journal of Derivatives, 14, 80-94.
DOI
|
10 |
Kim T and Song S (2011). Value-at-risk estimation using NIG and VG distribution, Journal of the Korean Data Analysis Society, 13, 1775-1788.
|
11 |
Kole E, Koedijk K, and Verbeek M (2007). Selecting copulas for risk management, Journal of Banking & Finance, 31, 2405-2423.
DOI
|
12 |
Kraus D and Czado C (2017). D-vine copula based quantile regression, Computational Statistics & Data Analysis, 110, 1-18.
DOI
|
13 |
Kupiec P (1995). Techniques for verifying the accuracy of risk measurement models, The Journal of Derivatives, 3, 73-84.
DOI
|
14 |
Cherubini U, Mulinacci S, Gobbi F, and Romagnoli S (2011). Dynamic Copula Methods in Finance, John Wiley & Sons, New York.
|
15 |
Madan DB, Carr PP, and Chang EC (1998). The variance gamma process and option pricing, Review of Finance, 2, 79-105.
DOI
|
16 |
Doric D and Doric EN (2011). Return distribution and value at risk estimation for BELEX15, Yugoslav Journal of Operations Research, 21, 103-118.
DOI
|
17 |
Low RKY, Alcock J, Faff R, and Brailsford T (2013). Canonical vine copulas in the context of modern portfolio management: Are they worth it?, Journal of Banking & Finance, 37, 3085-3099.
DOI
|
18 |
Mabitsela L, Mare E, and Kufakunesu R (2015). Quantification of VaR: A note on VaR valuation in the South African equity market, Journal of Risk and Financial Management, 8, 103-126.
DOI
|
19 |
Markowitz H (1952). Portfolio selection, The Journal of Finance, 7, 77-91.
DOI
|
20 |
Aas K, Haff IH, and Dimakos XK (2005). Risk estimation using the multivariate normal inverse Gaussian distribution, The Journal of Risk, 8, 39-60.
|
21 |
Aas K, Czado C, Frigessi A, and Bakken H (2009). Pair-copula constructions of multiple dependence, Insurance: Mathematics and Economics, 44, 182-198.
DOI
|
22 |
Barndorff-Nielsen OE (1997). Normal inverse Gaussian distributions and stochastic volatility modelling, Scandinavian Journal of Statistics, 24, 1-13.
DOI
|
23 |
Barndorff-Nielsen OE, Mikosch T, and Resnick SI (2001). L'evy Processes: Theory and Applications, Springer Science & Business Media, New York.
|
24 |
Bolviken E and Benth FE (2000). Quantification of risk in Norwegian stocks via the normal inverse Gaussian distribution, In Proceedings of the AFIR 2000 Colloquium, Tromso, Norway, 87-98.
|
25 |
Charpentier A (2003). Tail distribution and dependence measures, In Proceedings of the 34th ASTIN Conference, Berlin, Germany, 1-25.
|
26 |
Trivedi PK and Zimmer DM (2007). Copula modeling: an introduction for practitioners, Foundations and Trends in Econometrics, 1, 1-111.
DOI
|
27 |
Okhrin O and Ristig A (2014). Hierarchical Archimedean copulae: the HAC package, Journal of Statistical Software, 58, 1-20.
|
28 |
Okhrin O and Tetereva A (2017). The realized hierarchical archimedean copula in risk Modelling, Econometrics, 5, 1-31.
DOI
|
29 |
Schoutens W (2003). Levy Processes in Finance: Pricing Financial Derivatives, John Wiley & Sons, New York.
|
30 |
Sklar A (1959). Fonctions de repartition an dimensions et leurs marges, Publications de l'Institut Statistique de l'Universite de Paris, 8, 229-231.
|
31 |
Venkataraman S (1997). Value at risk for a mixture of normal distributions: the use of quasi-Bayesian estimation techniques, Economic Perspectives-Federal Reserve Bank of Chicago, 21, 2-13.
|
32 |
Weibel M, Breymann W, and Luthi D (2020). ghyp: A package on generalized hyperbolic distributions, Manual for R Package ghyp.
|
33 |
Wilhelmsson A (2009). Value at Risk with time varying variance, skewness and kurtosis-the NIG-ACD model, The Econometrics Journal, 12, 82-104.
DOI
|
34 |
Wu F, Valdez E, and Sherris M (2007). Simulating from exchangeable Archimedean copulas, Communications in Statistics-Simulation and Computation, 36, 1019-1034.
DOI
|