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Danske Bank

About: Danske Bank is a based out in . It is known for research contribution in the topics: Volatility (finance) & Volatility smile. The organization has 69 authors who have published 145 publications receiving 3733 citations. The organization is also known as: Danske Bank A/S.


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Kestutis Aidas1, Celestino Angeli2, Keld L. Bak3, Vebjørn Bakken4, Radovan Bast5, Linus Boman6, Ove Christiansen3, Renzo Cimiraglia2, Sonja Coriani7, Pål Dahle8, Erik K. Dalskov, Ulf Ekström4, Thomas Enevoldsen9, Janus J. Eriksen3, Patrick Ettenhuber3, Berta Fernández10, Lara Ferrighi, Heike Fliegl4, Luca Frediani, Kasper Hald11, Asger Halkier, Christof Hättig12, Hanne Heiberg13, Trygve Helgaker4, Alf C. Hennum14, Hinne Hettema15, Eirik Hjertenæs16, Stine Høst3, Ida-Marie Høyvik3, Maria Francesca Iozzi17, Brannislav Jansik18, Hans-Jørgen Aa. Jensen9, Dan Jonsson, Poul Jørgensen3, Johanna Kauczor19, Sheela Kirpekar, Thomas Kjærgaard3, Wim Klopper20, Stefan Knecht21, Rika Kobayashi22, Henrik Koch16, Jacob Kongsted9, Andreas Krapp, Kasper Kristensen3, Andrea Ligabue23, Ola B. Lutnæs24, Juan Ignacio Melo25, Kurt V. Mikkelsen26, Rolf H. Myhre16, Christian Neiss27, Christian B. Nielsen, Patrick Norman19, Jeppe Olsen3, Jógvan Magnus Haugaard Olsen9, Anders Osted, Martin J. Packer9, Filip Pawłowski28, Thomas Bondo Pedersen4, Patricio Federico Provasi29, Simen Reine4, Zilvinas Rinkevicius5, Torgeir A. Ruden, Kenneth Ruud, Vladimir V. Rybkin20, Paweł Sałek, Claire C. M. Samson20, Alfredo Sánchez de Merás30, Trond Saue31, Stephan P. A. Sauer26, Bernd Schimmelpfennig20, Kristian Sneskov11, Arnfinn Hykkerud Steindal, Kristian O. Sylvester-Hvid, Peter R. Taylor32, Andrew M. Teale33, Erik I. Tellgren4, David P. Tew34, Andreas J. Thorvaldsen3, Lea Thøgersen35, Olav Vahtras5, Mark A. Watson36, David J. D. Wilson37, Marcin Ziółkowski38, Hans Ågren5 
TL;DR: Dalton is a powerful general‐purpose program system for the study of molecular electronic structure at the Hartree–Fock, Kohn–Sham, multiconfigurational self‐consistent‐field, Møller–Plesset, configuration‐interaction, and coupled‐cluster levels of theory.
Abstract: Dalton is a powerful general-purpose program system for the study of molecular electronic structure at the Hartree-Fock, Kohn-Sham, multiconfigurational self-consistent-field, MOller-Plesset, confi ...

1,212 citations

Journal ArticleDOI
TL;DR: In this paper, the authors study the forecasting of future realized volatility in the stock, bond, and foreign exchange markets, as well as the continuous sample path and jump components of this, from variables in the information set, including implied volatility backed out from option prices.
Abstract: We study the forecasting of future realized volatility in the stock, bond, and foreign exchange markets, as well as the continuous sample path and jump components of this, from variables in the information set, including implied volatility backed out from option prices. Recent nonparametric statistical techniques of Barndor-Nielsen & Shephard (2004, 2006) are used to separate realized volatility into its continuous and jump components, which enhances forecasting performance, as shown by Andersen, Bollerslev & Diebold (2005). We generalize the heterogeneous autoregressive (HAR) model of Corsi (2004) to include implied volatility as an additional regressor, and to the separate forecasting of the realized components. We also introduce a new vector HAR (VecHAR) model for the resulting simultaneous system, controlling for possible endogeneity issues in the forecasting equations. We show that implied volatility contains incremental information about future volatility relative to both continuous and jump components of past realized volatility. Indeed, in the foreign exchange market, implied volatility completely subsumes the information content of daily, weekly, and monthly realized volatility measures, when forecasting future realized volatility or its continuous component. In addition, implied volatility is an unbiased forecast of future realized volatility in the foreign exchange and stock markets. Perhaps surprisingly, the jump component of realized return volatility is, to some extent, predictable, and options appear to be calibrated to incorporate information about future jumps in all three markets.

276 citations

Journal ArticleDOI
TL;DR: In this paper, a jump-process is used to fit the stock price model to the observed volatility smile/skew, which is shown to be unconditionally stable and, if combined with FFT (Fast Fourier Transform) methods, computationally efficient.
Abstract: The standard approach (e.g. Dupire (1994) and Rubinstein (1994)) to fitting stock processes to observed option prices models the underlying stock price as a one-factor diffusion process with state- and time-dependent volatility. While this approach is attractive in the sense that market completeness is maintained, the resulting model is often highly non-stationary, difficult to fit to steep volatility smiles, and generally is not well supported by empirical evidence. In this paper, we attempt to overcome some of these problems by overlaying the diffusion dynamics with a jump-process, effectively assuming that a large part of the observed volatility smiles can be explained by fear of sudden large market movements ("crash-o-phobia"). The first part of this paper derives a forward PIDE (Partial Integro-Differential Equation) satisfied by European call option prices and demonstrates how the resulting equation can be used to fit the model to the observed volatility smile/skew. In the second part of the paper, we discuss efficient methods of applying the calibrated model to the pricing of contingent claims. In particular, we develop an ADI (Alternating Directions Implicit) finite difference method that is shown to be unconditionally stable and, if combined with FFT (Fast Fourier Transform) methods, computationally efficient. The paper also discusses the usage of Monte Carlo methods, and contains several detailed examples from the S&P500 market. We compare pricing results obtained by the jump-diffusion approach with those of pure diffusion, and find significant differences for a range of popular contracts.

229 citations

Journal ArticleDOI
TL;DR: In this article, the authors consider extending the Libor market model to markets with volatility skews in observable option prices and discuss efficient techniques for calibration to quoted prices of caps and swaptions.
Abstract: This paper considers extensions of the Libor market model (Brace et al (1997), Jamshidian (1997), Miltersen et al (1997)) to markets with volatility skews in observable option prices. We expand the family of forward rate processes to include diffusions with non-linear forward rate dependence and discuss efficient techniques for calibration to quoted prices of caps and swaptions. Special emphasis is put on generalized CEV processes for which exact closed-form expressions for cap prices are derived. We also discuss modifications of the CEV process which exhibit appealing growth and boundary characteristics. The proposed models are investigated numerically through Crank-Nicholson finite difference schemes and Monte Carlo simulations.

223 citations

Journal ArticleDOI
TL;DR: In this article, the forecasting of future realized volatility in the foreign exchange, stock, and bond markets from variables in our information set, including implied volatility backed out from option prices, is studied.

217 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202112
202012
20197
20186
20175
20166