Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Donatien Hainaut"'
Autor:
Charlotte Jamotton, Donatien Hainaut
Publikováno v:
Intelligent Systems with Applications, Vol 24, Iss , Pp 200455- (2024)
This article explores the application of Variational AutoEncoders (VAEs) to insurance data. Previous research has demonstrated the successful implementation of generative models, especially VAEs, across various domains, such as image recognition, tex
Externí odkaz:
https://doaj.org/article/a7dc249cff694ebda650880954d12a41
Publikováno v:
Risks, Vol 12, Iss 9, p 141 (2024)
The K-means algorithm and its variants are well-known clustering techniques. In actuarial applications, these partitioning methods can identify clusters of policies with similar attributes. The resulting partitions provide an actuarial framework for
Externí odkaz:
https://doaj.org/article/da3fb0f8b7e14625aae2a2b296969a49
Autor:
Donatien Hainaut
Publikováno v:
Risks, Vol 10, Iss 1, p 2 (2021)
This article proposes an interest rate model ruled by mean reverting Lévy processes with a sub-exponential memory of their sample path. This feature is achieved by considering an Ornstein–Uhlenbeck process in which the exponential decaying kernel
Externí odkaz:
https://doaj.org/article/9ab1d2c4112a4fd991857f0f3b3472c2
Autor:
Donatien Hainaut
Publikováno v:
Quantitative Finance and Economics, Vol 1, Iss 2, Pp 145-173 (2017)
This paper proposes two jump diffusion models with and without mean reversion,for stocks or commodities, capable to fit highly leptokurtic processes. The jump component is acontinuous mixture of independent point processes with Laplace jumps. As in f
Externí odkaz:
https://doaj.org/article/584fdce1bc1647ff8809222db66923cd
Autor:
Donatien Hainaut
Publikováno v:
Risks, Vol 9, Iss 1, p 3 (2020)
In this article, a model for pandemic risk and two stochastic extensions is proposed. It is designed for actuarial valuation of insurance plans providing healthcare and death benefits. The core of our approach relies on a deterministic model that is
Externí odkaz:
https://doaj.org/article/b630c8f87b3142b9b18e1f6052c2032e
Autor:
Donatien Hainaut
Publikováno v:
Risks, Vol 6, Iss 3, p 77 (2018)
Most of the models leading to an analytical expression for option prices are based on the assumption that underlying asset returns evolve according to a Brownian motion with drift. For some asset classes like commodities, a Brownian model does not fi
Externí odkaz:
https://doaj.org/article/c07b467bafa34cdfbc930de1ad126aaf
Autor:
Donatien Hainaut
Publikováno v:
ASTIN Bulletin. 53:351-376
This article proposes a continuous time mortality model based on calendar years. Mortality rates belong to a mean-reverting random field indexed by time and age. In order to explain the improvement of life expectancies, the reversion level of mortali
Publikováno v:
European Journal of Operational Research. 297:1139-1150
We propose a fractional self-exciting model for the risk of corporate default. We study the properties of a time-changed version of an intensity based model. As a time-change, we use the inverse of an α -stable subordinator. Performing such a time-c
Autor:
Donatien Hainaut
Publikováno v:
Journal of Computational and Applied Mathematics, Vol. 149, p. 114752 (2023)
Asset dynamics with rough volatility recently received a great deal of attention in finance because they are consistent with empirical observations. This article provides a detailed analysis of the impact of roughness on prices of spread and exchange
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6549780b9a074d969dbc99784944ba02
https://hdl.handle.net/2078.1/265606
https://hdl.handle.net/2078.1/265606
Publikováno v:
European Actuarial Journal, (2023)
The Rough Fractional Stochastic Volatility (RFSV) model of Gatheral et al. (Quant Financ 18(6):933-949, 2014) is remarkably consistent with financial time series of past volatility data as well as with the observed implied volatility surface. Two tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ff758e9b5c8b56d31a39295704870b9
https://hdl.handle.net/2078.1/263669
https://hdl.handle.net/2078.1/263669