Publications
61 results found
Sauri O, Veraart A, 2016, On the class of distributions of subordinated Lévy processes, Stochastic Processes and Their Applications, ISSN: 0304-4149
This article studies the class of distributions obtained by subordinating L´evyprocesses and L´evy bases by independent subordinators and meta-times. To dothis we derive properties of a suitable mapping obtained via L´evy mixing. Weshow that our results can be used to solve the so-called recovery problem forgeneral L´evy bases as well as for moving average processes which are driven bysubordinated L´evy processes.
Granelli A, Veraart A, 2016, Modelling the variance risk premium of equity indices: the role ofdependence and contagion, SIAM Journal on Financial Mathematics, Vol: 7, Pages: 382-417, ISSN: 1945-497X
The variance risk premium (VRP) refers to the premium demanded for holding assetswhose variance is exposed to stochastic shocks.This paper identifies a new modelling framework for equity indices and presents for thefirst time explicit analytical formulas for their VRP in a multivariate stochastic volatilitysetting, which includes multivariate non-Gaussian Ornstein-Uhlenbeck processes and Wishartprocesses. Moreover, we propose to incorporate contagion within the equity index via amultivariate Hawkes process and find that the resulting dynamics of the VRP represent aconvincing alternative to the models studied in the literature up to date. We show that ournew model can explain the key stylised facts of both equity indices and individual assets andtheir corresponding VRP, while some popular (multivariate) stochastic volatility models mayfail.
Veraart A, Zdanowicz H, 2015, Modelling and predicting photovoltaic power generation in the EEX market, SSRN
Sauri O, Veraart A, 2015, On the class of distributions of subordinated Levy processes
Nguyen M, Veraart A, 2015, Tempo-spatial Ornstein-Uhlenbeck processes: theory, simulation and statistical inference
Veraart AED, 2015, Modelling the impact of wind power production on electricity prices by regime-switching Levy semistationary processes, Stochastics of Environmental and Financial Economics, Editors: Benth, Di Nunno, Publisher: Springer, Pages: 321-340
This paper studies the impact of wind power production on electricity prices in the European energy market.We propose a new modelling framework based on so-called regime-switching Levy semistationary processes to account for forward-looking information consisting of predicted wind power generation. We show that our new regime-switching model, where the regime switch depends on the so-called wind penetration index, can describe recent electricity price data very well.
Barndorff-Nielsen OE, Benth FE, Veraart AED, 2015, Cross-commodity modelling by multivariate ambit fields, Commodities, Energy and Environmental Finance, Editors: Aid, Ludkovski, Sircar, Publisher: Springer, Pages: 109-148
Barndorff--Nielsen OE, Benth FE, Veraart AED, 2014, Modelling Electricity Futures by Ambit Fields, Advances of Applied Probability, Vol: 46, Pages: 719-745
Noven RC, Veraart AED, Gandy A, 2014, A Levy-driven rainfall model with applications to futures pricing
Barndorff-Nielsen OE, Benth FE, Veraart AED, 2014, Recent advances in ambit stochastics with a view towards tempo-spatial stochastic volatility/intermittency, Banach Center Publications, Vol: 104, Pages: 25-60
Barndorff-Nielsen OE, Lunde A, Shephard N, et al., 2014, Integer-valued trawl processes: A class of stationary infinitely divisible processes, Scandinavian Journal of Statistics, Vol: 41, Pages: 693-724
Granelli A, Veraart AED, 2014, Modelling the Variance Risk Premium of Equity Indices: The Role of Dependence and Contagion
Benth FE, Eyjolfsson H, Veraart AED, 2014, Approximating Levy semistationary processes via Fourier methods in the context of power markets, SIAM Journal on Financial Mathematics, Pages: 71-98
Veraart AED, Veraart LAM, 2013, Risk premiums in energy markets, Journal of Energy Markets, Pages: 91-132
Veraart AED, 2013, Stationary and multi-self-similar random fields with stochastic volatility, Stochastics, Vol: 87, Pages: 848-870, ISSN: 0090-9491
This paper introduces stationary and multi-self-similar random fields which account for stochastic volatility and have type G marginal law. The stationary random fields are constructed using volatility modulated mixed moving average (MA) fields and their probabilistic properties are discussed. Also, two methods for parameterizing the weightfunctions in the MA representation are presented: one method is based on Fourier techniques and aims at reproducing a given correlation structure, the other method is based on ideas from stochastic partial differential equations. Moreover, using a generalized Lamperti transform we construct volatility modulated multi-self-similar random fields which have type G distribution.
Barndorff-Nielsen OE, Benth FE, Pedersen J, et al., 2013, On stochastic integration for volatility modulated Levy-driven Volterra processes, Stochastic Processes and Their Applications, Vol: n/a, ISSN: 0304-4149
Barndorff-Nielsen OE, Benth FE, Veraart AED, 2013, Modelling energy spot prices by volatility modulated Levy-driven Volterra processes, Bernoulli, Vol: 19, Pages: 803-845, ISSN: 1350-7265
Barndorff-Nielsen OE, Veraart AED, 2013, Stochastic Volatility of Volatility and Variance Risk Premia, Journal of Financial Econometrics, Vol: 11, Pages: 1-46
Veraart A, 2012, Impact of time–inhomogeneous jumps and leverage type effects on returns and realised variances
This paper studies the effect of time–inhomogeneous jumps and leverage type effects on realisedvariance calculations when the logarithmic asset price is given by a Lévy–driven stochasticvolatility model. In such a model, the realised variance is an inconsistent estimator of the integratedvariance. Nevertheless it can be used within a quasi–maximumlikelihood setup to drawinference on the model parameters. In order to do that, this paper introduces a new methodologyfor deriving all cumulants of the returns and realised variance in explicit form by solving a recursivesystem of inhomogeneous ordinary differential equations.
Veraart AED, Veraart LAM, 2012, Modelling electricity day-ahead prices by multivariate Levy semistationary processes, Quantitative Energy Finance, Editors: Benth, Kholodnyi, Laurence, Publisher: Springer
Veraart AED, Veraart LAM, 2012, Stochastic volatility and stochastic leverage, Annals of Finance, Vol: 8, Pages: 205-233
Veraart AED, 2011, Likelihood estimation of Levy-driven stochastic volatility models through realised variance measures, Econometrics Journal, Vol: 14, Pages: 204-240, ISSN: 1368-4221
Veraart AED, 2011, How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?, A St A: Advances in Statistical Analysis, Vol: 95, Pages: 253-291
Barndorff-Nielsen OE, Benth FE, Veraart AED, 2011, Ambit Processes and Stochastic Partial Differential Equations, Advanced Mathematical Methods for Finance, Editors: Nunno, Oksendal, Publisher: Springer Verlag, Pages: 35-74, ISBN: 9783642184116
Veraart AED, Winkel M, 2010, Time change, Encyclopedia of Quantitative Finance, Editors: Cont, Publisher: Wiley, Pages: 1812-1816, ISBN: 9780470057568
Veraart AED, 2010, Inference for the jump part of quadratic variation of Ito semimartingales, Econometric Theory, Vol: 26, Pages: 331-368
Veraart AED, 2008, Volatility estimation and inference in the presence of jumps
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