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Relevant bibliographies by topics / Generalized hyperbolic distribution

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Academic literature on the topic 'Generalized hyperbolic distribution'

Author: Grafiati

Published: 4 June 2021

Last updated: 27 April 2022

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Journal articles on the topic "Generalized hyperbolic distribution"

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Scott, David J., Diethelm Würtz, Christine Dong, and Thanh Tam Tran. "Moments of the generalized hyperbolic distribution." Computational Statistics 26, no. 3 (2010): 459–76. http://dx.doi.org/10.1007/s00180-010-0219-z.

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Aljarrah, Mohammad. "Generalized hyperbolic secant distribution: Properties, estimation, and applications." Filomat 35, no. 13 (2021): 4305–26. http://dx.doi.org/10.2298/fil2113305a.

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In this study, we define a generalized hyperbolic secant distribution. Poor fit to heavy tailed data sets is repeatedly obtained by existing three-parameter distributions. Only three parameters are considered in the proposed new distribution and it fits a heavy left- and right-tailed data better than various existing distributions. We study some properties of the new distribution, namely, mode, skewness, kurtosis, hazard function, moments, mean deviation, and Shannon entropy. Seven different frequentist methods for estimating the parameters are briefly described. A simulation study is also con

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Chen, Xiu Fang, and Gao Bo Chen. "Pattern Search for Generalized Hyperbolic Distribution and Financial Risk Measure." Applied Mechanics and Materials 155-156 (February 2012): 424–29. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.424.

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A new parameter estimation--- pattern search algorithm based on maximum likelihood estimation is used to estimate the parameters of generalized hyperbolic distribution, normal inverse Gaussian distribution and hyperbolic distribution, which are used to fit the log-return of Shanghai composite index. The goodness of fit is tested based on Anderson & Darling distance and FOF distance who pay more attention to tail distances of some distribution. Monte Carlo simulation are used to determin the critical values of Anderson & Darling distance and FOF distance of different distributions.Value

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Aleiyouka, Mohalilou, Alexandre Berred, and Mohammad Ahsanullah. "Tail dependence coefficient of generalized hyperbolic distribution." Journal of Statistical Theory and Applications 16, no. 3 (2017): 375. http://dx.doi.org/10.2991/jsta.2017.16.3.9.

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Aas, K. "The Generalized Hyperbolic Skew Student's t-Distribution." Journal of Financial Econometrics 4, no. 2 (2006): 275–309. http://dx.doi.org/10.1093/jjfinec/nbj006.

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Schmidt, Rafael, Tomas Hrycej, and Eric Stützle. "Multivariate distribution models with generalized hyperbolic margins." Computational Statistics & Data Analysis 50, no. 8 (2006): 2065–96. http://dx.doi.org/10.1016/j.csda.2005.03.010.

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Gaunt, Robert E. "A Stein characterisation of the generalized hyperbolic distribution." ESAIM: Probability and Statistics 21 (2017): 303–16. http://dx.doi.org/10.1051/ps/2017007.

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Vaughan, David C. "THE GENERALIZED SECANT HYPERBOLIC DISTRIBUTION AND ITS PROPERTIES." Communications in Statistics - Theory and Methods 31, no. 2 (2002): 219–38. http://dx.doi.org/10.1081/sta-120002647.

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Vilca, Filidor, N. Balakrishnan, and Camila Borelli Zeller. "Multivariate Skew-Normal Generalized Hyperbolic distribution and its properties." Journal of Multivariate Analysis 128 (July 2014): 73–85. http://dx.doi.org/10.1016/j.jmva.2014.03.002.

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Kwak, Minsuk, and Traian A. Pirvu. "Cumulative Prospect Theory with Generalized Hyperbolic Skewed $t$ Distribution." SIAM Journal on Financial Mathematics 9, no. 1 (2018): 54–89. http://dx.doi.org/10.1137/16m1093550.

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Dissertations / Theses on the topic "Generalized hyperbolic distribution"

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Midov, Askerbi, and Konstantin Balashov. "Risk Management based on GARCH and Non-parametric stochastic volatility models and some cases of Generalized Hyperbolic distribution." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-2201.

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<p>The paper is devoted to the modern methods of Value-at-Risk calculation using different cases of Generalized Hyperbolic distribution and models for predicting volatility. In our research we use GARCH-M and Non-parametric volatility models and compare Value-at-Risk calculation depending on the distribution that is used. In the case of Non-parametric model corresponding windows are proved by the Cross Validation method. Furthermore in our work we consider adaption of the method to intraday data using ACD and UHF-GARCH models. The project involves also application of the developed methods to r

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Sak, Halis, Wolfgang Hörmann, and Josef Leydold. "Efficient Risk Simulations for Linear Asset Portfolios." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2008. http://epub.wu.ac.at/1200/1/document.pdf.

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We consider the problem of calculating tail probabilities of the returns of linear asset portfolios. As flexible and accurate model for the logarithmic returns we use the $t$-copula dependence structure and marginals following the generalized hyperbolic distribution. Exact calculation of the tail-loss probabilities is not possible and even simulation leads to challenging numerical problems. Applying a new numerical inversion method for the generation of the marginals and importance sampling with carefully selected mean shift we develop an efficient simulation algorithm. Numerical results for a

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Derflinger, Gerhard, Wolfgang Hörmann, Josef Leydold, and Halis Sak. "Efficient Numerical Inversion for Financial Simulations." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2009. http://epub.wu.ac.at/830/1/document.pdf.

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Generating samples from generalized hyperbolic distributions and non-central chi-square distributions by inversion has become an important task for the simulation of recent models in finance in the framework of (quasi-) Monte Carlo. However, their distribution functions are quite expensive to evaluate and thus numerical methods like root finding algorithms are extremely slow. In this paper we demonstrate how our new method based on Newton interpolation and Gauss-Lobatto quadrature can be utilized for financial applications. Its fast marginal generation times make it competitive, even for situa

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Sjöstrand, Maria, and Özlem Aktaş. "Cornish-Fisher Expansion and Value-at-Risk method in application to risk management of large portfolios." Thesis, Högskolan i Halmstad, Tillämpad matematik och fysik (MPE-lab), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-16274.

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One of the major problem faced by banks is how to manage the risk exposure in large portfolios. According to Basel II regulation banks has to measure the risk using Value-at-Risk with confidence level 99%. However, this regulation does not specify the way to calculate Valueat- Risk. The easiest way to calculate Value-at-Risk is to assume that portfolio returns are normally distributed. Altough, this is the most common way to calculate Value-at-Risk, there exists also other methods. The previous crisis shows that the regular methods are unfortunately not always enough to prevent bankruptcy. Thi

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Shi, Xiang. "Advanced Applications of Generalized Hyperbolic Distributions in Portfolio Allocation and Measuring Diversification." Thesis, State University of New York at Stony Brook, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10165670.

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<p> This thesis consists of two parts. The first part addresses the parameter estimation and calibration of the Generalized Hyperbolic (GH) distributions. In this part we review the classical expectation maximization (EM) algorithm and factor analysis for the GH distribution. We also propose a simple shrinkage estimator driven from the penalized maximum likelihood. In addition an on-line EM algorithm is implemented to the GH distribution; and its regret for general exponential family can be represented as a mixture of Kullback-Leibler divergence. We compute the Hellinger distance of the joint

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Pérgola, Gabriel Campos. "Seguro contra risco de downside de uma carteira: uma proposta híbrida frequentista-Bayesiana com uso de derivativos." reponame:Repositório Institucional do FGV, 2013. http://hdl.handle.net/10438/10468.

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Submitted by Gabriel Campos Pérgola (gabrielpergola@gmail.com) on 2013-02-04T12:56:43Z No. of bitstreams: 1 DissertationGabrielPergola2013.pdf: 521205 bytes, checksum: 85369078a82b0d5cc02f8248961e9214 (MD5)<br>Rejected by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br), reason: Prezado Gabriel, Não recebemos os arquivo em PDF. Att. Suzi 3799-7876 on 2013-02-05T18:53:00Z (GMT)<br>Submitted by Gabriel Campos Pérgola (gabrielpergola@gmail.com) on 2013-02-05T19:00:17Z No. of bitstreams: 2 DissertationGabrielPergola2013.pdf: 521205 bytes, checksum: 85369078a82b0d5cc02f8248961e9214 (M

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Yilmaz, Yildiz Elif. "Experimental Design With Short-tailed And Long-tailed Symmetric Error Distributions." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605191/index.pdf.

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One-way and two-way classification models in experimental design for both balanced and unbalanced cases are considered when the errors have Generalized Secant Hyperbolic distribution. Efficient and robust estimators for main and interaction effects are obtained by using the modified maximum likelihood estimation (MML) technique. The test statistics analogous to the normal-theory F statistics are defined to test main and interaction effects and a test statistic for testing linear contrasts is defined. It is shown that test statistics based on MML estimators are efficient and robust. The method

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Shie, Shuen-Shiu, and 謝舜旭. "Empirical Analysis of Forward Rate Unbiasedness--An Application of Generalized Hyperbolic Distribution." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/49608715881346709462.

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Lu, Tienling, and 陸天羚. "Improvements of Pricing Taiwan Index Option Under GARCH Model Valuation －An Application of Generalized Hyperbolic Distribution." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/64818819505947612029.

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Hu, Wenbo Kercheval Alec. "Calibration of multivariate generalized hyperbolic distributions using the EM algorithm, with applications in risk management, portfolio optimization and portfolio credit risk." Diss., 2005. http://etd.lib.fsu.edu/theses/available/etd-10312005-131627.

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Thesis (Ph. D.)--Florida State University, 2005.<br>Advisor: Alec Kercheval, Florida State University, College of Arts and Sciences, Dept. of Mathemematics. Title and description from dissertation home page (viewed Jan. 26, 2006). Document formatted into pages; contains xii, 103 pages. Includes bibliographical references.

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Books on the topic "Generalized hyperbolic distribution"

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Fischer, Matthias J. Generalized Hyperbolic Secant Distributions. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45138-6.

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Book chapters on the topic "Generalized hyperbolic distribution"

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Fischer, Matthias J. "The BHS Distribution Family." In Generalized Hyperbolic Secant Distributions. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45138-6_4.

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Fischer, Matthias J. "The SHS and SASHS Distribution Family." In Generalized Hyperbolic Secant Distributions. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45138-6_5.

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Fischer, Matthias J. "The GSH Distribution Family and Skew Versions." In Generalized Hyperbolic Secant Distributions. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45138-6_2.

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Fischer, Matthias J. "The NEF-GHS or Meixner Distribution Family." In Generalized Hyperbolic Secant Distributions. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45138-6_3.

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Fischer, Matthias J. "Hyperbolic Secant Distributions." In Generalized Hyperbolic Secant Distributions. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45138-6_1.

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Fischer, Matthias. "Generalized Hyperbolic Distributions." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_272.

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Fischer, Matthias J. "Application to Finance." In Generalized Hyperbolic Secant Distributions. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45138-6_6.

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Hammerstein, Ernst August v. "Tail Behaviour and Tail Dependence of Generalized Hyperbolic Distributions." In Springer Proceedings in Mathematics & Statistics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45875-5_1.

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Eberlein, Ernst, and Ernst August v. Hammerstein. "Generalized Hyperbolic and Inverse Gaussian Distributions: Limiting Cases and Approximation of Processes." In Seminar on Stochastic Analysis, Random Fields and Applications IV. Birkhäuser Basel, 2004. http://dx.doi.org/10.1007/978-3-0348-7943-9_15.

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"The Generalized Hyperbolic Distribution." In Handbook of Heavy-Tailed Distributions in Asset Management and Risk Management. WORLD SCIENTIFIC, 2019. http://dx.doi.org/10.1142/9789813276208_0004.

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Conference papers on the topic "Generalized hyperbolic distribution"

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Palmer, Jason A., Ken Kreutz-Delgado, and Scott Makeig. "An EM algorithm for maximum likelihood estimation of Barndorff-Nielsen's generalized hyperbolic distribution." In 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016. http://dx.doi.org/10.1109/ssp.2016.7939245.

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Lee, Ikjin, David Yoo, and Yoojeong Noh. "A Novel Second-Order Reliability Method (SORM) Using Non-Central or Generalized Chi-Squared Distributions." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70276.

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This paper proposes a novel second-order reliability method (SORM) using non-central or general chi-squared distribution to improve the accuracy of reliability analysis in existing SORM. Conventional SORM contains three types of errors: (1) error due to approximating a general nonlinear limit state function by a quadratic function at most probable point (MPP) in the standard normal U-space, (2) error due to approximating the quadratic function in U-space by a hyperbolic surface, and (3) error due to calculation of the probability of failure after making the previous two approximations. The pro

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Zhao, Cunlu, and Chun Yang. "Electroosmotic Flow of Power-Law Fluids in a Slit Microchannel." In ASME 2009 7th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2009. http://dx.doi.org/10.1115/icnmm2009-82182.

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Electroosmotic flow of power-law fluids in a slit channel is analyzed. The governing equations including the linearized Poisson–Boltzmann equation, the Cauchy momentum equation and the continuity equation are solved to seek analytical expressions for the shear stress, dynamic viscosity and velocity distributions. Specifically, exact solutions of the velocity distributions are explicitly found for several special values of the flow behavior index. Furthermore, with the implementation of an approximate scheme for the hyperbolic cosine function, approximate solutions of the velocity distributions

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Huang, Yulong, Yonggang Zhang, Yuxin Zhao, Lyudmila Mihaylova, and Jonathon Chambers. "A Novel Robust Rauch-Tung-Striebel Smoother Based on Slash and Generalized Hyperbolic Skew Student's T-Distributions." In 2018 21st International Conference on Information Fusion (FUSION 2018). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455256.

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