ORCID Profile
0000-0001-7472-5475
Current Organisations
UNSW Australian School of Business
,
UNSW Australia Business School
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Investment and Risk Management | Banking, Finance and Investment | Insurance Studies
Publisher: MDPI AG
Date: 06-2019
DOI: 10.3390/RISKS7020061
Abstract: Stochastic mortality models have been developed for a range of applications from demographic projections to financial management. Financial risk based models built on methods used for interest rates and apply these to mortality rates. They have the advantage of being applied to financial pricing and the management of longevity risk. Olivier and Jeffery (2004) and Smith (2005) proposed a model based on a forward-rate mortality framework with stochastic factors driven by univariate gamma random variables irrespective of age or duration. We assess and further develop this model. We generalize random shocks from a univariate gamma to a univariate Tweedie distribution and allow for the distributions to vary by age. Furthermore, since dependence between ages is an observed characteristic of mortality rate improvements, we formulate a multivariate framework using copulas. We find that dependence increases with age and introduce a suitable covariance structure, one that is related to the notion of ax minimum. The resulting model provides a more realistic basis for capturing the risk of mortality improvements and serves to enhance longevity risk management for pension and insurance funds.
Publisher: Elsevier BV
Date: 11-2015
Publisher: International Association for Energy Economics (IAEE)
Date: 07-2020
Publisher: Elsevier BV
Date: 09-2014
Publisher: Elsevier BV
Date: 09-2016
Publisher: Wiley
Date: 15-07-2020
DOI: 10.1111/IRFI.12319
Abstract: Significant portfolio variance biases arise when contrasting multiperiod portfolio returns based on the assumption of fixed continuously rebalanced portfolio weights as opposed to buy‐and‐hold weights. Empirical evidence obtained using S& P 500 constituents from 2003 to 2011 demonstrates that, compared with a buy‐and‐hold assumption, applying fixed weights led to decreased estimates of portfolio volatilities during 2003, 2005 and 2010, but caused a significant increase in volatility estimates in the more turbulent 2008 and 2011. This discrepancy distorts assessments of portfolio risk‐adjusted performance when inappropriate weight assumptions are employed. Consequently, these variance biases have effect on statistical inference in factor models and may result in erroneous portfolio size recommendations for adequate ersification.
Publisher: Elsevier BV
Date: 05-2016
Publisher: Walter de Gruyter GmbH
Date: 20-12-2019
Abstract: This paper investigates dependence among insurance claims arising from different lines of business (LoBs). Using bivariate and multivariate portfolios of losses from different LoBs, we analyse the ability of various copulas in conjunction with skewed generalised hyperbolic (GH) marginals to capture the dependence structure between in idual insurance risks forming an aggregate risk of the loss portfolio. The general form skewed GH distribution is shown to provide the best fit to univariate loss data. When modelling dependency between LoBs using one-parameter and mixture copula models, we favour models that are capable of generating upper tail dependence, that is, when several LoBs have a strong tendency to exhibit extreme losses simultaneously. We compare the selected models in their ability to quantify risks of multivariate portfolios. By performing an extensive investigation of the in- and out-of-s le Value-at-Risk (VaR) forecasts by analysing VaR exceptions (i.e. observations of realised portfolio value that are greater than the estimated VaR), we demonstrate that the selected models allow to reliably quantify portfolio risk. Our results provide valuable insights with regards to the nature of dependence and fulfils one of the primary objectives of the general insurance providers aiming at assessing total risk of an aggregate portfolio of losses when LoBs are correlated.
Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier BV
Date: 02-2019
Publisher: Walter de Gruyter GmbH
Date: 2014
Abstract: This paper deals with the estimation of continuous time diffusion processes describing the dynamics of electricity spot prices. Different parametric models have been proposed in the literature, each attempting to capture empirical characteristics and stylized facts of the electricity market like the spiky behavior of the spot prices. Although jump-diffusion and regime-switching models perform reasonably well, there is always a trade-off between model parsimony and adequacy. The results in the literature indicate that none of the models seem to consistently outperform its counterparts. This paper avoids making parametric assumption about the drift and the diffusion coefficient functions of the underlying electricity spot prices, and estimates these functions together with the market price of risk in a nonparametric way. The latter allows us to price futures contracts written on electricity spots. Using electricity spot prices and futures data from the regional electricity markets in Australia, we show that besides offering a convenient way of estimating the continuous-time models for electricity spot prices, our nonparametric estimation procedure performs well in- and out-of-s le when dealing with pricing of future contracts.
Publisher: Informa UK Limited
Date: 02-01-2015
Publisher: Springer Science and Business Media LLC
Date: 09-2011
Publisher: Informa UK Limited
Date: 16-06-2015
Publisher: Walter de Gruyter GmbH
Date: 2014
Abstract: The growth optimal portfolio (GOP) plays an important role in finance, where it serves as the numéraire portfolio, with respect to which contingent claims can be priced under the real world probability measure. This paper models the GOP using a time dependent constant elasticity of variance (TCEV) model. The TCEV model has high tractability for a range of derivative prices and fits well the dynamics of a global ersified world equity index. This is confirmed when pricing and hedging various derivatives using this index.
Publisher: Wiley
Date: 04-03-2015
DOI: 10.1111/ACFI.12074
Publisher: MDPI AG
Date: 03-01-2019
DOI: 10.3390/RISKS7010002
Abstract: This paper assesses the hedge effectiveness of an index-based longevity swap and a longevity cap for a life annuity portfolio. Although longevity swaps are a natural instrument for hedging longevity risk, derivatives with non-linear pay-offs, such as longevity caps, provide more effective downside protection. A tractable stochastic mortality model with age dependent drift and volatility is developed and analytical formulae for prices of longevity derivatives are derived. The model is calibrated using Australian mortality data. The hedging of the life annuity portfolio is comprehensively assessed for a range of assumptions for the longevity risk premium, the term to maturity of the hedging instruments, as well as the size of the underlying annuity portfolio. The results compare the risk management benefits and costs of longevity derivatives with linear and nonlinear payoff structures.
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 06-2012
Publisher: Springer Science and Business Media LLC
Date: 12-03-2010
Publisher: Informa UK Limited
Date: 03-09-2018
Publisher: Informa UK Limited
Date: 06-02-2018
Publisher: Informa UK Limited
Date: 22-08-2017
Publisher: Elsevier BV
Date: 02-2016
Start Date: 2022
End Date: 12-2024
Amount: $378,292.00
Summary: Quantitative Analysis of Systemic Risk in Insurance. This project aims to achieve a contemporary and comprehensive quantitative analysis of systemic risk in insurance. The significance lies in narrowing the gap between the studies of systemic risk in banking and insurance. Expected outcomes include the construction of insurance/reinsurance networks to formalise systemic risk, the analysis of the role of network integration, and the development of pricing frameworks to entail a systemic risk prem .... Quantitative Analysis of Systemic Risk in Insurance. This project aims to achieve a contemporary and comprehensive quantitative analysis of systemic risk in insurance. The significance lies in narrowing the gap between the studies of systemic risk in banking and insurance. Expected outcomes include the construction of insurance/reinsurance networks to formalise systemic risk, the analysis of the role of network integration, and the development of pricing frameworks to entail a systemic risk premium. The project will benefit insurers and regulators by providing a forward-looking approach to monitoring and assessing insurance risk during a systemic crisis. These important original contributions to insurance risk management will help establish Australia’s global leadership in systemic risk. Read more Read less
Funder: Australian Research Council
View Funded Activity