Retirement Income Strategies in Expected Utility and Loss Aversion Frameworks

2012 ◽  
Author(s):  
Gaobo Pang ◽  
Mark J. Warshawsky
Keyword(s):  
Expected Utility ◽  
Loss Aversion ◽  
Retirement Income

scholarly journals Coping with Loss Aversion in the Newsvendor Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianwu Sun ◽  
Xinsheng Xu
Keyword(s):  
Expected Utility ◽  
Loss Aversion ◽  
Confidence Level ◽  
Profit Maximization ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Decision Bias ◽  
Optimal Order Quantity

We introduce loss aversion into the decision framework of the newsvendor model. By introducing the loss aversion coefficientλ, we propose a novel utility function for the loss-averse newsvendor. First, we obtain the optimal order quantity to maximize the expected utility for the loss-averse newsvendor who is risk-neutral. It is found that this optimal order quantity is smaller than the expected profit maximization order quantity in the classical newsvendor model, which may help to explain the decision bias in the classical newsvendor model. Then, to reduce the risk which originates from the fluctuation in the market demand, we achieve the optimal order quantity to maximize CVaR about utility for the loss-averse newsvendor who is risk-averse. We find that this optimal order quantity is smaller than the optimal order quantity to maximize the expected utility above and is decreasing in the confidence levelα. Further, it is proved that the expected utility under this optimal order quantity is decreasing in the confidence levelα, which verifies that low risk implies low return. Finally, a numerical example is given to illustrate the obtained results and some management insights are suggested for the loss-averse newsvendor model.

OPTIMAL PORTFOLIO UNDER STATE-DEPENDENT EXPECTED UTILITY

2018 ◽  
Vol 21 (03) ◽  
pp. 1850013 ◽  
Author(s):  
CAROLE BERNARD ◽  
STEVEN VANDUFFEL ◽  
JIANG YE
Keyword(s):  
Portfolio Choice ◽  
Expected Utility ◽  
Loss Aversion ◽  
Reference Point ◽  
Joint Distribution ◽  
Optimal Portfolio ◽  
Characterization Result ◽  
Terminal Wealth ◽  
Utility Maximizer ◽  
State Dependent

We derive the optimal portfolio for an expected utility maximizer whose utility does not only depend on terminal wealth but also on some random benchmark (state-dependent utility). We then apply this result to obtain the optimal portfolio of a loss-averse investor with a random reference point (extending a result of Berkelaar et al. (2004) Optimal portfolio choice under loss aversion, The Review of Economics and Statistics 86 (4), 973–987). Clearly, the optimal portfolio has some joint distribution with the benchmark and we show that it is the cheapest possible in having this distribution. This characterization result allows us to infer the state-dependent utility function that explains the demand for a given (joint) distribution.

scholarly journals Loss Modification Incentives for Insurers Under Expected Utility and Loss Aversion

De Economist ◽  
2015 ◽  
Vol 164 (1) ◽  
pp. 41-67
Author(s):  
Adriaan R. Soetevent ◽  
Liting Zhou
Keyword(s):  
Expected Utility ◽  
Loss Aversion

scholarly journals Desenvolvimento de uma Medida de Desempenho Comportamental

2012 ◽  
Vol 10 (3) ◽  
pp. 395
Author(s):  
Marcelo Cabus Klotzle ◽  
Leonardo Lima Gomes ◽  
Luiz Eduardo Teixeira Brandão ◽  
Antonio Carlos Figueiredo Pinto
Keyword(s):  
Prospect Theory ◽  
Decision Maker ◽  
Performance Measures ◽  
Behavioral Finance ◽  
Expected Utility ◽  
Loss Aversion ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Performance Measure ◽  
Uncertain Outcomes

Since the fifties, several measures have been developed in order to measure the performance of investments or choices involving uncertain outcomes. Much of these measures are based on Expected Utility Theory, but since the nineties a number of measures have been proposed based on Non-Expected Utility Theory. Among the Theories of Non-Expected Utility highlights Prospect Theory, which is the foundation of Behavioral Finance. Based on this theory this study proposes a new performance measure in which are embedded loss aversion along with the likelihood of distortions in the choice of alternatives. A hypothetical example is presented in which various performance measures, including the new measure are compared. The results showed that the ordering of the assets varied depending on the performance measure adopted. According to what was expected, the new performance measure clearly has captured the distortion of probabilities and loss aversion of the decision maker, ie, those assets with the greatest negative deviations from the target were those who had the worst performance.

scholarly journals ON THE OPTIMAL COMBINATION OF ANNUITIES AND TONTINES

2020 ◽  
Vol 50 (1) ◽  
pp. 95-129 ◽  
Author(s):  
An Chen ◽  
Manuel Rach ◽  
Thorsten Sehner
Keyword(s):  
Expected Utility ◽  
Optimal Combination ◽  
Optimal Portfolio ◽  
Longevity Risk ◽  
Retirement Income ◽  
The Novel ◽  
Retirement Plan

AbstractTontines, retirement products constructed in such a way that the longevity risk is shared in a pool of policyholders, have recently gained vast attention from researchers and practitioners. Typically, these products are cheaper than annuities, but do not provide stable payments to policyholders. This raises the question whether, from the policyholders' viewpoint, the advantages of annuities and tontines can be combined to form a retirement plan which is cheaper than an annuity, but provides a less volatile retirement income than a tontine. In this article, we analyze and compare three approaches of combining annuities and tontines in an expected utility framework: the previously introduced “tonuity”, a product very similar to the tonuity which we call “antine” and a portfolio consisting of an annuity and a tontine. We show that the payoffs of a tonuity and an antine can be replicated by a portfolio consisting of an annuity and a tontine. Consequently, policyholders achieve higher expected utility levels when choosing the portfolio over the novel retirement products tonuity and antine. Further, we derive conditions on the premium loadings of annuities and tontines indicating when the optimal portfolio is investing a positive amount in both annuity and tontine, and when the optimal portfolio turns out to be a pure annuity or a pure tontine.

scholarly journals Binary Payment Schemes: Moral Hazard and Loss Aversion

2010 ◽  
Vol 100 (5) ◽  
pp. 2451-2477 ◽  
Author(s):  
Fabian Herweg ◽  
Daniel Müller ◽  
Philipp Weinschenk
Keyword(s):  
Moral Hazard ◽  
Expected Utility ◽  
Loss Aversion ◽  
Reference Point ◽  
Performance Measure ◽  
Principal Agent ◽  
Optimal Contract ◽  
Agent Model ◽  
Payment Schemes ◽  
Principal Agent Model

We modify the principal-agent model with moral hazard by assuming that the agent is expectation-based loss averse according to Kőoszegi and Rabin (2006, 2007). The optimal contract is a binary payment scheme even for a rich performance measure, where standard preferences predict a fully contingent contract. The logic is that, due to the stochastic reference point, increasing the number of different wages reduces the agent's expected utility without providing strong additional incentives. Moreover, for diminutive occurrence probabilities for all signals the agent is rewarded with the fixed bonus if his performance exceeds a certain threshold. (JEL D82, D86, J41, M52, M12)

scholarly journals Analysis of Behavioral Economics in Crowdsensing: A Loss Aversion Cooperation Model

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Deng Li ◽  
Liying Qiu ◽  
Jiaqi Liu ◽  
Congwen Xiao
Keyword(s):  
Behavioral Economics ◽  
Utility Function ◽  
Expected Utility ◽  
Loss Aversion ◽  
Incentive Mechanism ◽  
Experimental Results ◽  
Individual Utility ◽  
Incentive Mechanisms ◽  
Cooperation Model

The existing incentive mechanisms of crowdsourcing construct the expected utility function based on the assumption of rational people in traditional economics. A large number of studies in behavioral economics have demonstrated the defects of the traditional utility function and introduced a new parameter called loss aversion coefficient to calculate individual utility when it suffers a loss. In this paper, combination of behavioral economics and a payment algorithm based on the loss aversion is proposed. Compared with usual incentive mechanisms, the node utility function is redefined by the loss aversion characteristic of the node. Experimental results show that the proposed algorithm can get a higher rate of cooperation with a lower payment price and has good scalability compared with the traditional incentive mechanism.

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