Pricing formulae for derivatives in insurance using Malliavin calculus
Abstract In this paper, we provide a valuation formula for different classes of actuarial and financial contracts which depend on a general loss process by using Malliavin calculus. Similar to the celebrated Black–Scholes formula, we aim to express the expected cash flow in terms of a building block...
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2018-06-01
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Online Access: | http://link.springer.com/article/10.1186/s41546-018-0028-9 |
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doaj-aa1ed7b7753b4027afaa14fd6a9972602020-11-24T21:29:17ZengSpringerOpenProbability, Uncertainty and Quantitative Risk2367-01262018-06-013111910.1186/s41546-018-0028-9Pricing formulae for derivatives in insurance using Malliavin calculusCaroline Hillairet0Ying Jiao1Anthony Réveillac2ENSAE Universite Paris Saclay, CRESTUniversité Claude Bernard - Lyon 1, Institut de Science Financière et d’AssurancesINSA de Toulouse, IMT UMR CNRS 5219, Université de ToulouseAbstract In this paper, we provide a valuation formula for different classes of actuarial and financial contracts which depend on a general loss process by using Malliavin calculus. Similar to the celebrated Black–Scholes formula, we aim to express the expected cash flow in terms of a building block. The former is related to the loss process which is a cumulated sum indexed by a doubly stochastic Poisson process of claims allowed to be dependent on the intensity and the jump times of the counting process. For example, in the context of stop-loss contracts, the building block is given by the distribution function of the terminal cumulated loss taken at the Value at Risk when computing the expected shortfall risk measure.http://link.springer.com/article/10.1186/s41546-018-0028-9Cox processesPricing formulaeInsurance derivativesMalliavin calculus |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Caroline Hillairet Ying Jiao Anthony Réveillac |
spellingShingle |
Caroline Hillairet Ying Jiao Anthony Réveillac Pricing formulae for derivatives in insurance using Malliavin calculus Probability, Uncertainty and Quantitative Risk Cox processes Pricing formulae Insurance derivatives Malliavin calculus |
author_facet |
Caroline Hillairet Ying Jiao Anthony Réveillac |
author_sort |
Caroline Hillairet |
title |
Pricing formulae for derivatives in insurance using Malliavin calculus |
title_short |
Pricing formulae for derivatives in insurance using Malliavin calculus |
title_full |
Pricing formulae for derivatives in insurance using Malliavin calculus |
title_fullStr |
Pricing formulae for derivatives in insurance using Malliavin calculus |
title_full_unstemmed |
Pricing formulae for derivatives in insurance using Malliavin calculus |
title_sort |
pricing formulae for derivatives in insurance using malliavin calculus |
publisher |
SpringerOpen |
series |
Probability, Uncertainty and Quantitative Risk |
issn |
2367-0126 |
publishDate |
2018-06-01 |
description |
Abstract In this paper, we provide a valuation formula for different classes of actuarial and financial contracts which depend on a general loss process by using Malliavin calculus. Similar to the celebrated Black–Scholes formula, we aim to express the expected cash flow in terms of a building block. The former is related to the loss process which is a cumulated sum indexed by a doubly stochastic Poisson process of claims allowed to be dependent on the intensity and the jump times of the counting process. For example, in the context of stop-loss contracts, the building block is given by the distribution function of the terminal cumulated loss taken at the Value at Risk when computing the expected shortfall risk measure. |
topic |
Cox processes Pricing formulae Insurance derivatives Malliavin calculus |
url |
http://link.springer.com/article/10.1186/s41546-018-0028-9 |
work_keys_str_mv |
AT carolinehillairet pricingformulaeforderivativesininsuranceusingmalliavincalculus AT yingjiao pricingformulaeforderivativesininsuranceusingmalliavincalculus AT anthonyreveillac pricingformulaeforderivativesininsuranceusingmalliavincalculus |
_version_ |
1716708188390162432 |