ORCID Profile
0000-0002-0559-2231
Current Organisation
UNSW Sydney
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Banking, Finance and Investment | Insurance Studies | Financial Mathematics | Financial Economics | Investment and Risk Management |
Superannuation and Insurance Services | Demography | Consumption | Finance Services | Preference, Behaviour and Welfare
Publisher: Elsevier BV
Date: 08-2015
Publisher: Elsevier BV
Date: 05-2015
Publisher: Elsevier BV
Date: 2013
Publisher: MDPI AG
Date: 07-2020
DOI: 10.3390/RISKS8030070
Abstract: This paper studies the effect of variance swap in hedging volatility risk under the mean-variance criterion. We consider two mean-variance portfolio selection problems under Heston’s stochastic volatility model. In the first problem, the financial market is complete and contains three primitive assets: a bank account, a stock and a variance swap, where the variance swap can be used to hedge against the volatility risk. In the second problem, only the bank account and the stock can be traded in the market, which is incomplete since the idiosyncratic volatility risk is unhedgeable. Under an exponential integrability assumption, we use a linear-quadratic control approach in conjunction with backward stochastic differential equations to solve the two problems. Efficient portfolio strategies and efficient frontiers are derived in closed-form and represented in terms of the unique solutions to backward stochastic differential equations. Numerical ex les are provided to compare the solutions to the two problems. It is found that adding the variance swap in the portfolio can remarkably reduce the portfolio risk.
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 05-2019
Publisher: Elsevier BV
Date: 09-2021
Publisher: Informa UK Limited
Date: 04-12-2020
Publisher: Elsevier BV
Date: 05-2015
Publisher: Informa UK Limited
Date: 12-06-2014
Publisher: Informa UK Limited
Date: 02-10-2019
Publisher: Elsevier BV
Date: 06-2014
Publisher: Informa UK Limited
Date: 02-06-2016
Publisher: American Institute of Mathematical Sciences (AIMS)
Date: 2017
Publisher: Elsevier BV
Date: 05-2016
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 05-2015
Publisher: Elsevier BV
Date: 2018
Publisher: Oxford University Press (OUP)
Date: 21-09-2016
Publisher: Elsevier BV
Date: 07-2012
Publisher: Springer Science and Business Media LLC
Date: 07-11-2020
Publisher: Elsevier BV
Date: 06-2018
Publisher: Informa UK Limited
Date: 20-11-2017
Publisher: MDPI AG
Date: 27-02-2018
DOI: 10.3390/RISKS6010014
Publisher: Informa UK Limited
Date: 16-10-2019
Publisher: Elsevier BV
Date: 2013
Publisher: Elsevier BV
Date: 03-2021
Publisher: Society for Industrial & Applied Mathematics (SIAM)
Date: 07-04-2022
DOI: 10.1137/20M1320560
Publisher: Elsevier BV
Date: 11-2016
Publisher: Springer Science and Business Media LLC
Date: 11-09-2018
Publisher: Elsevier BV
Date: 07-2022
Publisher: Informa UK Limited
Date: 23-03-2021
Publisher: Elsevier BV
Date: 11-2013
Publisher: Elsevier BV
Date: 09-2019
Publisher: American Institute of Mathematical Sciences (AIMS)
Date: 06-2015
Publisher: Elsevier BV
Date: 02-2014
Publisher: Elsevier BV
Date: 07-2014
Publisher: Oxford University Press (OUP)
Date: 21-12-2015
Publisher: Informa UK Limited
Date: 27-03-2014
Publisher: American Institute of Mathematical Sciences (AIMS)
Date: 2019
DOI: 10.3934/MCRF.2019003
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 03-2013
Publisher: Wiley
Date: 28-03-2013
DOI: 10.1002/FUT.21613
Publisher: Elsevier BV
Date: 11-2020
Publisher: Springer Science and Business Media LLC
Date: 23-07-2015
Publisher: Springer Science and Business Media LLC
Date: 29-04-2016
Publisher: Cambridge University Press (CUP)
Date: 26-03-2018
DOI: 10.1017/ASB.2018.3
Abstract: This paper proposes a new continuous-time framework to analyze optimal reinsurance, in which an insurer and a reinsurer are two players of a stochastic Stackelberg differential game, i.e., a stochastic leader-follower differential game. This allows us to determine optimal reinsurance from joint interests of the insurer and the reinsurer, which is rarely considered in the continuous-time setting. In the Stackelberg game, the reinsurer moves first and the insurer does subsequently to achieve a Stackelberg equilibrium toward optimal reinsurance arrangement. Speaking more precisely, the reinsurer is the leader of the game and decides on an optimal reinsurance premium to charge, while the insurer is the follower of the game and chooses an optimal proportional reinsurance to purchase. Under utility maximization criteria, we study the game problem starting from the general setting with generic utilities and random coefficients to the special case with exponential utilities and constant coefficients. In the special case, we find that the reinsurer applies the variance premium principle to calculate the optimal reinsurance premium and the insurer's optimal ceding/retained proportion of insurance risk depends not only on the risk aversion of itself but also on that of the reinsurer.
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 05-2015
Publisher: Springer Science and Business Media LLC
Date: 17-12-2016
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier BV
Date: 07-2014
Publisher: Elsevier BV
Date: 07-2016
Publisher: Elsevier BV
Date: 07-2013
Publisher: Informa UK Limited
Date: 05-2013
Publisher: American Institute of Mathematical Sciences (AIMS)
Date: 2017
DOI: 10.3934/JIMO.2016002
Publisher: Informa UK Limited
Date: 28-06-2017
Publisher: American Institute of Mathematical Sciences (AIMS)
Date: 2021
DOI: 10.3934/JIMO.2020015
Start Date: 2020
End Date: 2022
Funder: Australian Research Council
View Funded ActivityStart Date: 2016
End Date: 2017
Funder: Natural Sciences and Engineering Research Council
View Funded ActivityStart Date: 06-2021
End Date: 05-2024
Amount: $386,139.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2020
End Date: 02-2024
Amount: $420,039.00
Funder: Australian Research Council
View Funded Activity