Dynamic Copula Methods in Finance

Cherubini, Umberto; Mulinacci, Sabrina; Gobbi, Fabio

doi:10.1002/9781118467404

Cited by 127 publications

(108 citation statements)

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“…the volatility and time-integrated variance distributions, by using a copula. The copula methodology has been used intensively in the financial world, see, for example, [8] , in risk management and option pricing. In the field of risk management, some relevant works are Li [9] , Embrechts et al [10] , Cherubini and Luciano [11] or Rosenberg and Schuermann [12] .…”

Section: Introductionmentioning

confidence: 99%

On a one time-step Monte Carlo simulation approach of the SABR model: Application to European options

Leitao

Grzelak

Oosterlee

2017

Applied Mathematics and Computation

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a b s t r a c tIn this work, we propose a one time-step Monte Carlo method for the SABR model. We base our approach on an accurate approximation of the cumulative distribution function of the time-integrated variance (conditional on the SABR volatility), using Fourier techniques and a copula. Resulting is a fast simulation algorithm which can be employed to price European options under the SABR dynamics. Our approach can thus be seen as an alternative to Hagan's analytic formula for short maturities that may be employed for model calibration purposes.

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Section: Introductionmentioning

confidence: 99%

On a one time-step Monte Carlo simulation approach of the SABR model: Application to European options

Leitao

Grzelak

Oosterlee

2017

Applied Mathematics and Computation

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“…It is important to notice that the C-convolution has a closed form if and only if the marginal distributions are gaussian and the copula linking them is the gaussian copula (see Cherubini, Gobbi, Mulinacci & Romagnoli, 2012). For computational purposes in this paper we only consider that case.…”

Section: The Convolution Based Unit Root Processmentioning

confidence: 99%

“…For computational purposes in this paper we only consider that case. The reader can find some examples of Cconvolution with Clayton and Frank copulas in the book of Cherubini, Gobbi, Mulinacci & Romagnoli (2012 …”

Section: The Convolution Based Unit Root Processmentioning

confidence: 99%

“…This methodology exploits the properties of copula functions. The application of copula functions to stochastic processes (more in particular to Markov processes) was recently described in the book by Cherubini, Gobbi, Mulinacci and Romagnoli (2012). Our contribution relies on the application of a particular family of copulas, which are generated by the convolution operator, to the design of time series processes.…”

Section: Introductionmentioning

confidence: 99%

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Convolution Based Unit Root Processes: a Simulation Approach

Gobbi¹

2016

IJSP

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“…Such a model would estimate the intraday dependence and produce the forecast of the multivariate distribution of log-returns in the next second and could not be used for one-day-ahead VaR forecasts. For further details on the standard estimation procedures, refer to Nelsen (2007), Trivedi and Zimmer (2007), Jaworski et al (2013), Cherubini et al (2011), Joe (2014 and Durante and Sempi (2015). In contrast to the direct application of the ML approach to tick-by-tick data or high-frequency estimator of Kendall's τ, there is a considerable literature discussing how to estimate the correlation matrix of daily log-returns via a realized correlation matrix or similar methods, see , , Zhang et al (2005), Hayashi and Yoshida (2005), De Pooter et al (2008).…”

Section: The Concept Of the Realized Copulamentioning

confidence: 99%

The Realized Hierarchical Archimedean Copula in Risk Modelling

Okhrin¹,

Tetereva

2017

Econometrics

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This paper introduces the concept of the realized hierarchical Archimedean copula (rHAC). The proposed approach inherits the ability of the copula to capture the dependencies among financial time series, and combines it with additional information contained in high-frequency data. The considered model does not suffer from the curse of dimensionality, and is able to accurately predict high-dimensional distributions. This flexibility is obtained by using a hierarchical structure in the copula. The time variability of the model is provided by daily forecasts of the realized correlation matrix, which is used to estimate the structure and the parameters of the rHAC. Extensive simulation studies show the validity of the estimator based on this realized correlation matrix, and its performance, in comparison to the benchmark models. The application of the estimator to one-day-ahead Value at Risk (VaR) prediction using high-frequency data exhibits good forecasting properties for a multivariate portfolio.

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Dynamic Copula Methods in Finance

Cited by 127 publications

References 0 publications

On a one time-step Monte Carlo simulation approach of the SABR model: Application to European options

On a one time-step Monte Carlo simulation approach of the SABR model: Application to European options

Convolution Based Unit Root Processes: a Simulation Approach

The Realized Hierarchical Archimedean Copula in Risk Modelling

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