Fetching the paper…
Reading the bibliography…
We price European-style options written on forward contracts in a commodity market, which we model with an infinite-dimensional Heath-Jarrow-Morton (HJM) approach.
Nelson, Charles R. and Andrew F. Siegel. Parsimonious modeling of yield curves. Journal of Business : 473-489 (1987)
1987
Earlier work this paper cites.
Heath, David, Robert Jarrow and Andrew Morton. Bond pricing and the term structure of interest rates: A new methodology for contingent claims valuation. Econometrica: Journal of the Econometric Society , 77-105 (1992)
1992
Earlier work this paper cites.
Hutchinson, James M., Andrew W. Lo, and Tomaso Poggio. A nonparametric approach to pricing and hedging derivative securities via learning networks. The Journal of Finance 49.3 (1994): 851-889
1994
Earlier work this paper cites.
Clewlow, Les and Chris Strickland. Energy Derivatives: Pricing and Risk Management. Lacima Publications, London (2000)
2000
Earlier work this paper cites.
Filipović, Damir. Consistency Problems for Heath-Jarrow-Morton Interest Rate Models. Lecture notes in Mathematics, vol. 1760. Springer, Berlin (2001)
2001
Earlier work this paper cites.
Koekebakker, Steen and Fridthjof Ollmar. Forward curve dynamics in the Nordic electricity market. Managerial Finance , 31(6): 73-94 (2005)
2005
Earlier work this paper cites.
Engel, Klaus-Jochen and Rainer Nagel. A Short Course on Operator Semigroups. Springer (2006)
2006
Earlier work this paper cites.
Peszat, Szymon and Jerzy Zabczyk. Stochastic Partial Differential Equations with Lévy Noise: An evolution equation approach. (Vol. 113). Cambridge University Press (2007)
2007
Earlier work this paper cites.
Benth, Fred E. and Steen Koekebakker. Stochastic modeling of financial electricity contracts. Energy Economics , 30(3), 1116-1157 (2008)
2008
Earlier work this paper cites.
Benth, Fred E., J u ¯ \mathrm{\bar{u}} rat e ˙ \mathrm{\dot{e}} S ˇ \mathrm{\check{S}} . Benth and Steen Koekebakker. Stochastic Modelling of Electricity and Related Markets. Vol. 11. World Scientific (2008)
2008
Earlier work this paper cites.
Frestad, Dennis. Common and unique factors influencing daily swap returns in the Nordic electricity market, 1997–2005. Energy Economics , 30(3): 1081-1097 (2008)
2008
Earlier work this paper cites.
Filipovic, Damir. Term-Structure Models. A Graduate Course. Springer, 2009
2009
Earlier work this paper cites.
Andresen, Arne, Steen Koekebakker and Sjur Westgaard. Modeling electricity forward prices using the multivariate normal inverse Gaussian distribution. The Journal of Energy Markets , 3(3), 3 (2010)
2010
Earlier work this paper cites.
Kovács, Mihály, Stig Larsson and Fredrik Lindgren. Strong convergence of the finite element method with truncated noise for semilinear parabolic stochastic equations with additive noise. Numerical Algorithms 53(2-3): 309-320 (2010)
2010
Earlier work this paper cites.
Barth, Andrea and Annika Lang. Simulation of stochastic partial differential equations using finite element methods. Stochastics An International Journal of Probability and Stochastic Processes , 84(2-3): 217-231 (2012)
2012
Cited alongside, same era.
Barth, Andrea and Annika Lang. Multilevel Monte Carlo method with applications to stochastic partial differential equations. International Journal of Computer Mathematics , 89(18): 2479-2498 (2012)
2012
Cited alongside, same era.
Carmona, René and Sergey Nadtochiy. Tangent Lévy market models. Finance and Stochastics , 16(1): 63-104 (2012)
2012
Cited alongside, same era.
Tappe, Stefan. Some refinements of existence results for SPDEs driven by Wiener processes and Poisson random measures. International Journal of Stochastic Analysis (2012)
2012
Cited alongside, same era.
Hernandez, Andres. Model calibration with neural networks. Available at SSRN 2812140 (2016)
2016
Later among the works it cites.
2018
Later among the works it cites.
Benth, Fred E. and Florentina Paraschiv. A space-time random field model for electricity forward prices. Journal of Banking & Finance , 95, 203-216 (2018)
2018
Later among the works it cites.
De Spiegeleer, Jan, Dilip B. Madan, Sofie Reyners and Wim Schoutens. Machine learning for quantitative finance: fast derivative pricing, hedging and fitting. Quantitative Finance , 18(10), 1635-1643 (2018)
2018
Later among the works it cites.
Ferguson, Ryan and Andrew Green. Deeply learning derivatives. arXiv preprint arXiv:1809.02233 (2018)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Barth, Andrea, Annika Lang and Christoph Schwab. Multilevel Monte Carlo method for parabolic stochastic partial differential equations. BIT Numerical Mathematics , 53(1): 3-27 (2013)
2013
Cited alongside, same era.
Rynne, Bryan and Martin A. Youngson. Linear Functional Analysis. Springer Science & Business Media (2013)
2013
Cited alongside, same era.
Barth, Andrea and Fred E. Benth. The forward dynamics in energy markets – infinite-dimensional modelling and simulation. Stochastics An International Journal of Probability and Stochastic Processes , 86(6), 932-966 (2014)
2014
Cited alongside, same era.
Benth, Fred E. and Paul Krühner. Representation of infinite-dimensional forward price models in commodity markets. Communications in Mathematics and Statistics , 2(1), 47-106 (2014)
2014
Cited alongside, same era.
Da Prato, Giuseppe and Jerzy Zabczyk. Stochastic Equations in Infinite Dimensions. Cambridge University Press (2014)
2014
Cited alongside, same era.
2014
Cited alongside, same era.
Benth, Fred E.. Kriging smooth energy futures curves. Energy Risk (2015)
2015
Cited alongside, same era.
Benth, Fred E. and Paul Krühner. Derivatives pricing in energy markets: an infinite-dimensional approach. SIAM Journal on Financial Mathematics , 6(1), 825-869 (2015)
2015
Cited alongside, same era.
2018
Later among the works it cites.
Kondratyev, Alexei. Learning curve dynamics with artificial neural networks. Available at SSRN 3041232 (2018)
2018
Later among the works it cites.
2019
Later among the works it cites.
Bühler, Hans, Lukas Gonon, Josef Teichmann and Ben Wood. Deep hedging. Quantitative Finance , 19(8), 1271-1291 (2019)
2019
Later among the works it cites.
Higham, Catherine F. and Desmond J. Higham. Deep learning: An introduction for applied mathematicians. SIAM Review 61(4): 860-891 (2019)
2019
Later among the works it cites.
Chataigner, Marc, Stéphane Crépey and Matthew Dixon. Deep Local Volatility. Risks , 8(3): 82 (2020)
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
Horvath, Blanka, Aitor Muguruza, and Mehdi Tomas. Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models. Quantitative Finance (2020): 1-17
2020
Closest in time.