2020
DOI: 10.48550/arxiv.2012.04364
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Insurance valuation: A two-step generalised regression approach

Abstract: Current approaches to fair valuation in insurance often follow a two-step approach, combining quadratic hedging with application of a risk measure on the residual liability, to obtain a cost-of-capital margin. In such approaches, the preferences represented by the regulatory risk measure are not reflected in the hedging process. We address this issue by an alternative two-step hedging procedure, based on generalised regression arguments, which leads to portfolios that are neutral with respect to a risk measure… Show more

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“…Note thatCarbonneau (2020) demonstrates the potential of the deep hedging algorithm for global hedging long-term lookback options embedded in segregated funds guarantees with multiple hedging instruments. It is also worth highlighting thatBarigou et al (2020) developed a pricing scheme consistent with local non-quadratic hedging procedures for insurance liabilities which relies on neural networks.28 In the context of segregated funds, the short position of the embedded option is assumed to be held by an insurance company who has to provide a quote and mitigate its risk exposure. The long position is held by an unsophisticated investor who will not be hedging his risk exposure.…”
mentioning
confidence: 99%
“…Note thatCarbonneau (2020) demonstrates the potential of the deep hedging algorithm for global hedging long-term lookback options embedded in segregated funds guarantees with multiple hedging instruments. It is also worth highlighting thatBarigou et al (2020) developed a pricing scheme consistent with local non-quadratic hedging procedures for insurance liabilities which relies on neural networks.28 In the context of segregated funds, the short position of the embedded option is assumed to be held by an insurance company who has to provide a quote and mitigate its risk exposure. The long position is held by an unsophisticated investor who will not be hedging his risk exposure.…”
mentioning
confidence: 99%