Hélène Halconruy; Nicolas Marie
On a projection least squares estimator for jump diffusion processes Article de journal
Dans: Annals Of The Institute Of Statistical Mathematics, vol. 76, p. 209-234, 2024.
@article{halconruy_2423,
title = {On a projection least squares estimator for jump diffusion processes},
author = {Hélène Halconruy and Nicolas Marie},
url = {https://link.springer.com/article/10.1007/s10463-023-00881-7
Lien donnant accès à l'article :
https://rdcu.be/dlTH4},
year = {2024},
date = {2024-04-01},
journal = {Annals Of The Institute Of Statistical Mathematics},
volume = {76},
pages = {209-234},
abstract = {This paper deals with a projection least squares estimator of the drift function of a jump diffusion process X computed from multiple independent copies of X observed on [0, T]. Risk bounds are established on this estimator and on an associated adaptive estimator. Finally, some numerical experiments are provided.},
note = {Publié uniquement en ligne (donc pas d'issue, volume)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hélène Halconruy
The insider trading problem in a jump-binomial model Article de journal
Dans: Decisions in Economics and Finance, vol. 46, p. 379-413, 2023.
@article{halconruy_2424,
title = {The insider trading problem in a jump-binomial model},
author = {Hélène Halconruy},
url = {https://link.springer.com/article/10.1007/s10203-023-00412-2
Lien d'accès au papier
https://rdcu.be/dlTFM},
year = {2023},
date = {2023-12-01},
journal = {Decisions in Economics and Finance},
volume = {46},
pages = {379-413},
abstract = {We study insider trading in a jump-binomial model of the financial market that is based on a marked binomial process and that serves as a suitable alternative to some classical trinomial models. Our investigations focus on the two main questions: measuring the advantage of the insider's additional information and stating a closed form for her hedging strategy. Our approach is based on the results of enlargement of filtration in a discrete-time setting stated by Blanchet-Scalliet and Jeanblanc (in: From probability to finance, Springer, Berlin, 2020) and on a stochastic analysis for marked binomial processes developed in the companion paper (Halconruy in Electron J Probab 27:1-39, 2022). Our work provides in a discrete-time and an incomplete market setting the analogues of some results of Amendinger et al. (Stoch Process Appl 89(1):101-116, 2000; Finance Stoch 7(1):29-46, 2003), Imkeller et al. (1998, 2006) and extends in an insider framework some utility maximization results stated in Delbaen and Schachermayer (The mathematics of arbitrage, Springer, Berlin, 2006) and in Runggaldier et al. (in: Seminar on stochastic analysis, random fields and applications III, Springer, Berlin, 2002).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hélène Halconruy
Malliavin calculus for marked binomial processes and applications Article de journal
Dans: Electronic Journal Of Probability, vol. 27, no. 164, p. 1-39, 2022.
@article{halconruy_2077,
title = {Malliavin calculus for marked binomial processes and applications},
author = {Hélène Halconruy},
url = {https://projecteuclid.org/journals/electronic-journal-of-probability/volume-27/issue-none/Malliavin-calculus-for-marked-binomial-processes-and-applications/10.1214/22-EJP892.full},
year = {2022},
date = {2022-12-01},
journal = {Electronic Journal Of Probability},
volume = {27},
number = {164},
pages = {1-39},
abstract = {We develop stochastic analysis tools for marked binomial processes (MBP) that are the discrete analogues of the marked Poisson processes. They include in particular: (i) the statement of a chaos decomposition for square-integrable functionals of MBP, (ii) the design of a tailor-made Malliavin calculus of variations, (iii) the statement of the analogues of Stroocks, Clarks and Mehlers formulas. We provide our formalism with two applications: (App1) studying the (compound) Poisson approximation of MBP functional by combining it with the Chen-Stein method and (App2) solving an optimal hedging problem in the trinomial model.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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