A CLASS OF DISTORTION OPERATORS FOR PRICING FINANCIAL AND INSURANCE RISKS
By Shaun S. Wang. 2000
711 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- R´emi Munos
- Rob Kaas
- Michel Denuit
- Qihe Tang
- Andrew J. G. Cairns
- Roger J. A. Laeven
- Marc J. Goovaerts
- Jan Dhaene
In Finance
- Jan Dhaene
- Marc J. Goovaerts
- Michel Denuit
- Rob Kaas
- Qihe Tang
- Steven Vanduffel
- Roger J. A. Laeven
- David P. Blake
In Management Science and Operations Research
- Jan Dhaene
- Marc J. Goovaerts
- Michel Denuit
- Rob Kaas
- Roger J. A. Laeven
- Qihe Tang
- Steven Vanduffel
- David Silver
Citations in the corpus
- Implicit Quantile Networks for Distributional Reinforcement Learning (2018, methodology): “Second, we consider the distortion risk measure proposed by Wang (2000), where Φ and Φ − 1 are taken to be the standard Normal cumulative distribution function and its inverse: For η 0 , this produces risk-averse policies and we include it due to its simple interpretation and ability to switch…”
- Decentralized Likelihood Quantile Networks for Improving Performance in Deep Multi-Agent Reinforcement Learning (2018, background): “Wang (Wang, 2000) is a distortion operator whose range always remains [0 , 1] , but becomes exponentially increasing (probability density shifted towards 1 ) when given positive bias parameter η .”
- Securitization of Catastrophe Mortality Risks (2008, neutral): “Wang (1996, 2000, 2001, 2002) develop a method of pricing risks that unifies financial and in-”
- After VaR: The Theory, Estimation, and Insurance Applications of Quantile-Based Risk Measures (2006, neutral): “…distortion functions have been proposed to remedy these sorts of problems, but the best known of these is the following, the famous Wang Transform (Wang, 2000): g(u) = [ −1 (u) − λ], (10) where (·) is the standard normal distribution function and λ is a market price of risk term that might be…”
- Mortality-dependent financial risk measures (2006, background): “It is also very closely related to the class of distortion risk measures introduced by Shaun Wang that have become widely used in the actuarial risk literature (see, e.g., Wang, 1996, 2000 ).”
- Optimal reinsurance minimizing the distortion risk measure under general reinsurance premium principles (2013, neutral): “Combining with (25), the lemma is proved.”
- Copulas: A Review and Recent Developments (2006, methodology): “Interesting applications of the above theorem in case of TVaR and for a class of distortion risk measures suggested by Wang[119] and discussed by Darkiewicz et al.”
- Modeling Mortality With Jumps: Applications to Mortality Securitization (2009, neutral): “For example, Cox, Lin, and Wang (2006) estimate the market price of risk for the Swiss Re deal is 0.”
- Likelihood Quantile Networks for Coordinating Multi-Agent Reinforcement Learning (2018, neutral): “Our CVnaR is defined as follows: CVnaR maps 𝜏 ∼ 𝑈 ([ 0 , 1 ]) to CVnaR ( 𝜂,𝜏 ) ∼ 𝑈 ([ 𝜂, 1 ]) , and as 𝜂 reduces, CVnaR become less risk-seeking.”
- Natural Hedging of Life and Annuity Mortality Risks (2007, neutral): “Wang (1996, 2000, 2001) has developed a method of pricing risks that unifies financial and insurance pricing theories.”
- Properties of Distortion Risk Measures (2009, methodology): “Special cases are VaRα , CVaRα and the WT measure of Wang (2000).”
- Risk measurement with equivalent utility principles (2006, background): “Chateauneuf, Kast & Lapied (1996), Wang (2000, 2002) and Hamada & Sherris (2003) used the same mechanism for pricing in financial markets; see also Pelsser (2004).”