Portfolio insurance and prospect theory investors: Popularity and optimal design of capital protected financial products

Dichtl, Hubert; Drobetz, Wolfgang

doi:10.1016/j.jbankfin.2010.11.012

Cited by 92 publications

(67 citation statements)

References 58 publications

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“…Grossman and Vila [30] discuss portfolio insurance in complete markets, noting that the solution of an investor's constrained portfolio optimization problem (subject to a minimum wealth constraint V T > K ) can be characterized by the solution of the unconstrained problem plus a put option with exercise price K . More recently, Dichtl and Drobetz [19] provide empirical evidence that portfolio insurance is consistent with prospect theory, introduced by Kahneman and Tversky [41]. Loss-averse investors seem to use a reference point to evaluate portfolio gains and losses.…”

Section: Portfolio Insurancementioning

confidence: 96%

“…Recently, Dockner [20] compares buy-and-hold, OBPI and CPPI concluding that there does not exist a clear ranking of the alternatives. Dichtl and Drobetz [19] consider prospect theory (Kahneman and Tversky [41]) as framework to evaluate portfolio insurance strategies. They use a twofold methodological approach: Monte Carlo simulation and historical simulation with data for the German stock market.…”

Section: Performance Comparisonmentioning

confidence: 99%

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Risk Control in Asset Management: Motives and Concepts

Dangl

Randl

Zechner

2015

Innovations in Quantitative Risk Management

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In traditional portfolio theory, risk management is limited to the choice of the relative weights of the riskless asset and a diversified basket of risky securities, respectively. Yet in industry, risk management represents a central aspect of asset management, with distinct responsibilities and organizational structures. We identify frictions that lead to increased importance of risk management and describe three major challenges to be met by the risk manager. First, we derive a framework to determine a portfolio position's marginal risk contribution and to decide on optimal portfolio weights of active managers. Second, we survey methods to control downside risk and unwanted risks since investors frequently have nonstandard preferences, which make them seek protection against excessive losses. Third, we point out that quantitative portfolio management usually requires the selection and parametrization of stylized models of financial markets. We, therefore, discuss risk management approaches to deal with parameter uncertainty, such as shrinkage procedures or resampling procedures, and techniques of dealing with model uncertainty via methods of Bayesian model averaging.We thank Victor DeMiguel, Matthias Scherer, Neal Stoughton, Raman Uppal, Arne Westerkamp, Rudi Zagst and an anonymous referee for helpful comments.

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Section: Portfolio Insurancementioning

confidence: 96%

Section: Performance Comparisonmentioning

confidence: 99%

Risk Control in Asset Management: Motives and Concepts

Dangl

Randl

Zechner

2015

Innovations in Quantitative Risk Management

View full text Add to dashboard Cite

show abstract

“…An extreme example of market incompleteness in this context which makes portfolio insurance attractive is the impossibility for an investor to allocate funds into the riskfree asset. Grossman and Vila (1989) discuss portfolio insurance in complete markets, noting that the solution of an investor's constrainted portfolio optimization problem (subject to a a minimum wealth constraint V T > K) can be characterized by the solution of the unconstrained problem plus a put option with exercise price K. More recently, Dichtl and Drobetz (2011) provide empirical evidence that portfolio insurance is consistent with prospect theory, introduced by Kahneman and Tversky (1979). Loss-averse investors seem to use a reference point to evaluate portfolio gains and losses.…”

Section: Portfolio Insurancementioning

confidence: 99%

“…Recently, Dockner (2012) compares buy-and-hold, OBPI and CPPI concluding that there does not exist a clear ranking of the alternatives. Dichtl and Drobetz (2011) consider prospect theory (Kahneman and Tversky, 1979) as framework to evaluate portfolio insurance strategies. They use a twofold methodological approach: Monte Carlo simulation and historical simulation with data for the German stock market.…”

Section: Constant Proportion Portfolio Insurance (Cppi)mentioning

confidence: 99%

Risk Control in Asset Management: Motives and Concepts

2014

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“…The same functional forms of CPT as used by Dichtl and Drobetz (2011) are also adopted here. However, it is defined as in the manner of Schmidt et al (2008) where the reference point may be a stochastic value dependent on a realised state.…”

Section: Cumulative Prospect Theorymentioning

confidence: 99%

Constant Proportion Portfolio Insurance Strategies under Cumulative Prospect Theory with Reference Point Adaptation

2012

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Constant Proportion Portfolio Insurance (CPPI) is a significant and highly popular investment strategy within the structured product market. This has led to recent work which attempts to explain the popularity of CPPI by showing that it is compatible with Cumulative Prospect Theory (CPT). We demonstrate that this cannot explain the popularity of ratcheted CPPI products which lock-in gains during strong growth in the portfolio. In this paper we conjecture that CPPI investors not only follow CPT, but crucially that they also adapt their reference point over time. This important distinction explains investors preference for ratcheted products.JEL: G11; G13.

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Portfolio insurance and prospect theory investors: Popularity and optimal design of capital protected financial products

Cited by 92 publications

References 58 publications

Risk Control in Asset Management: Motives and Concepts

Risk Control in Asset Management: Motives and Concepts

Risk Control in Asset Management: Motives and Concepts

Constant Proportion Portfolio Insurance Strategies under Cumulative Prospect Theory with Reference Point Adaptation

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