Relevant bibliographies by topics / Multivariate Lévy models

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Academic literature on the topic 'Multivariate Lévy models'

Author: Grafiati
Published: 9 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Multivariate Lévy models"

1

Jacod, Jean, and Mark Podolskij. "On the minimal number of driving Lévy motions in a multivariate price model." Journal of Applied Probability 55, no. 3 (2018): 823–33. http://dx.doi.org/10.1017/jpr.2018.52.

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Abstract In this paper we consider the factor analysis for Lévy-driven multivariate price models with stochastic volatility. Our main aim is to provide conditions on the volatility process under which we can possibly reduce the dimension of the driving Lévy motion. We find that these conditions depend on a particular form of the multivariate Lévy process. In some settings we concentrate on nondegenerate symmetric α-stable Lévy motions.
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Ballotta, Laura, and Efrem Bonfiglioli. "Multivariate asset models using Lévy processes and applications." European Journal of Finance 22, no. 13 (2014): 1320–50. http://dx.doi.org/10.1080/1351847x.2013.870917.

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Panov, Vladimir. "Series Representations for Multivariate Time-Changed Lévy Models." Methodology and Computing in Applied Probability 19, no. 1 (2015): 97–119. http://dx.doi.org/10.1007/s11009-015-9461-8.

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4

Avanzi, Benjamin, Jamie Tao, Bernard Wong, and Xinda Yang. "Capturing non-exchangeable dependence in multivariate loss processes with nested Archimedean Lévy copulas." Annals of Actuarial Science 10, no. 1 (2015): 87–117. http://dx.doi.org/10.1017/s1748499515000135.

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AbstractThe class of spectrally positive Lévy processes is a frequent choice for modelling loss processes in areas such as insurance or operational risk. Dependence between such processes (e.g. between different lines of business) can be modelled with Lévy copulas. This approach is a parsimonious, efficient and flexible method which provides many of the advantages akin to distributional copulas for random variables. Literature on Lévy copulas seems to have primarily focussed on bivariate processes. When multivariate settings are considered, these usually exhibit an exchangeable dependence stru
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Fasen, Vicky. "Limit Theory for High Frequency Sampled MCARMA Models." Advances in Applied Probability 46, no. 3 (2014): 846–77. http://dx.doi.org/10.1239/aap/1409319563.

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We consider a multivariate continuous-time ARMA (MCARMA) process sampled at a high-frequency time grid {hn, 2hn,…, nhn}, where hn ↓ 0 and nhn → ∞ as n → ∞, or at a constant time grid where hn = h. For this model, we present the asymptotic behavior of the properly normalized partial sum to a multivariate stable or a multivariate normal random vector depending on the domain of attraction of the driving Lévy process. Furthermore, we derive the asymptotic behavior of the sample variance. In the case of finite second moments of the driving Lévy process the sample variance is a consistent estimator.
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Moser, Martin, and Robert Stelzer. "Tail behavior of multivariate lévy-driven mixed moving average processes and supOU Stochastic Volatility Models." Advances in Applied Probability 43, no. 4 (2011): 1109–35. http://dx.doi.org/10.1239/aap/1324045701.

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Multivariate Lévy-driven mixed moving average (MMA) processes of the type Xt = ∬f(A, t - s)Λ(dA, ds) cover a wide range of well known and extensively used processes such as Ornstein-Uhlenbeck processes, superpositions of Ornstein-Uhlenbeck (supOU) processes, (fractionally integrated) continuous-time autoregressive moving average processes, and increments of fractional Lévy processes. In this paper we introduce multivariate MMA processes and give conditions for their existence and regular variation of the stationary distributions. Furthermore, we study the tail behavior of multivariate supOU pr
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Moser, Martin, and Robert Stelzer. "Tail behavior of multivariate lévy-driven mixed moving average processes and supOU Stochastic Volatility Models." Advances in Applied Probability 43, no. 04 (2011): 1109–35. http://dx.doi.org/10.1017/s0001867800005322.

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Multivariate Lévy-driven mixed moving average (MMA) processes of the type X t = ∬f(A, t - s)Λ(dA, ds) cover a wide range of well known and extensively used processes such as Ornstein-Uhlenbeck processes, superpositions of Ornstein-Uhlenbeck (supOU) processes, (fractionally integrated) continuous-time autoregressive moving average processes, and increments of fractional Lévy processes. In this paper we introduce multivariate MMA processes and give conditions for their existence and regular variation of the stationary distributions. Furthermore, we study the tail behavior of multivariate supOU p
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Fasen, Vicky. "Limit Theory for High Frequency Sampled MCARMA Models." Advances in Applied Probability 46, no. 03 (2014): 846–77. http://dx.doi.org/10.1017/s0001867800007400.

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We consider a multivariate continuous-time ARMA (MCARMA) process sampled at a high-frequency time grid {h n , 2h n ,…, nh n }, where h n ↓ 0 and nh n → ∞ as n → ∞, or at a constant time grid where h n = h. For this model, we present the asymptotic behavior of the properly normalized partial sum to a multivariate stable or a multivariate normal random vector depending on the domain of attraction of the driving Lévy process. Furthermore, we derive the asymptotic behavior of the sample variance. In the case of finite second moments of the driving Lévy process the sample variance is a consistent e
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9

JEVTIĆ, PETAR, MARINA MARENA, and PATRIZIA SEMERARO. "MULTIVARIATE MARKED POISSON PROCESSES AND MARKET RELATED MULTIDIMENSIONAL INFORMATION FLOWS." International Journal of Theoretical and Applied Finance 22, no. 02 (2019): 1850058. http://dx.doi.org/10.1142/s0219024918500589.

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The class of marked Poisson processes and its connection with subordinated Lévy processes allow us to propose a new interpretation of multidimensional information flows and their relation to market movements. The new approach provides a unified framework for multivariate asset return models in a Lévy economy. In fact, we are able to recover several processes commonly used to model asset returns as subcases. We consider a first application example using the normal inverse Gaussian specification.
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10

Fink, Holger. "Conditional Characteristic Functions of Molchan-Golosov Fractional Lévy Processes with Application to Credit Risk." Journal of Applied Probability 50, no. 4 (2013): 983–1005. http://dx.doi.org/10.1239/jap/1389370095.

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Molchan-Golosov fractional Lévy processes (MG-FLPs) are introduced by way of a multivariate componentwise Molchan-Golosov transformation based on an n-dimensional driving Lévy process. Using results of fractional calculus and infinitely divisible distributions, we are able to calculate the conditional characteristic function of integrals driven by MG-FLPs. This leads to important predictions concerning multivariate fractional Brownian motion, fractional subordinators, and general fractional stochastic differential equations. Examples are the fractional Lévy Ornstein-Uhlenbeck and Cox-Ingersoll
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Dissertations / Theses on the topic "Multivariate Lévy models"

1

Petkovic, Alexandre. "Three essays on exotic option pricing, multivariate Lévy processes and linear aggregation of panel models." Doctoral thesis, Universite Libre de Bruxelles, 2009. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210357.

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This thesis is composed of three chapters that form two parts. The first part is composed of two chapters and studies problems related to the exotic option market. In the first chapter we are interested in a numerical problem. More precisely we derive closed-form approximations for the price of some exotic options in the Black and Scholes framework. The second chapter discusses the construction of multivariate Lévy processes with and without stochastic volatility. The second part is composed of one chapter. It deals with a completely different issue. There we will study the problem of individu
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LOREGIAN, ANGELA. "Multivariate Lèvy models: estimation and asset allocation." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/49727.

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Multidimensional asset models based on Lévy processes have been introduced to meet the necessity of capturing market shocks using more refined distribution assumptions compared to the standard Gaussian framework. In particular, along with accurately modeling marginal distributions of asset returns, capturing the dependence structure among them is of paramount importance, for example, to correctly price derivatives written on more than one underlying asset. Most of the literature on multivariate Lévy models focuses in fact on pricing multi-asset products, which is also the case of the mod
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3

Stelzer, Robert [Verfasser]. "Multivariate continuous time stochastic volatility models driven by a Lévy process / Robert Josef Stelzer." 2007. http://d-nb.info/986220337/34.

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