Optimal contracting with moral hazard and behavioral preferences

Chang, Hualei; Cvitanić, Jakša

doi:10.1016/j.jmaa.2015.03.027

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…A closely related paper is Chang, Cvitanić, and Zhou (), who study a principal–agent problem with moral hazard in which the agent's preferences are modeled by CPT. In their paper, asset volatility is controlled by the firm's principal: its shareholders.…”

Section: Introductionmentioning

confidence: 99%

Profit Sharing in Hedge Funds

Kou

2016

Mathematical Finance

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In a new scheme for hedge fund managerial compensation known as the first‐loss scheme, a fund manager uses her investment in the fund to cover any fund losses first; by contrast, in the traditional scheme currently used in most US funds, the manager does not cover investors' losses in the fund. We propose a framework based on cumulative prospect theory to compute and compare the trading strategies, fund risk, and managers' and investors' utilities in these two schemes analytically. The model is calibrated to the historical attrition rates of US hedge funds. We find that with reasonable parameter values, both fund managers' and investors' utilities can be improved and fund risk can be reduced simultaneously by replacing the traditional scheme (with 10% internal capital and 20% performance fee) with a first‐loss scheme (with 10% first‐loss capital and 30% performance fee). When the performance fee in the first‐loss scheme is 40% (a current market practice), however, such substitution renders investors worse off.

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Section: Introductionmentioning

confidence: 99%

Profit Sharing in Hedge Funds

Kou

2016

Mathematical Finance

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“…The settings and models addressed in these papers, as well as the nature of the questions posed, in the few exceptions [de Meza and Webb 2007;Kanbur et al 2008;Nakajima 2011;Chang et al 2014] are very different from our work.…”

Section: Related Workmentioning

confidence: 80%

Behavioral Mechanism Design

Easley

Ghosh

2015

Proceedings of the Sixteenth ACM Conference on Economics and Computation

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Incentive design is more likely to elicit desired outcomes when it is derived based on accurate models of agent behavior. A substantial literature in behavioral economics, however, demonstrates that individuals systematically and consistently deviate from the standard economic model-expected utility theory-for decision-making under uncertainty, which is at the core of the equilibrium analysis necessary to facilitate mechanism design. Can these behavioral biases-as modeled by prospect theory [Kahneman and Tversky 1979]-in agents' decision-making make a difference to the optimal design of incentives in these environments? In this paper, we explore this question in the context of markets for online labor and crowdsourcing where workers make strategic choices about whether to undertake a task, but do not strategize over quality conditional on participation. We ask what kind of incentive scheme-amongst a broad class of contracts, including those observed on major crowdsourcing platforms such as fixed prices or base payments with bonuses (as on MTurk or oDesk), or open-entry contests (as on platforms like Kaggle or Topcoder)-a principal might want to employ, and how the answer to this question depends on whether workers behave according to expected utility or prospect theory preferences.We first show that with expected utility agents, the optimal contract-for any increasing objective of the principalalways takes the form of an output-independent fixed payment to some optimally chosen number of agents. In contrast, when agents behave according to prospect theory preferences, we show that a winner-take-all contest can dominate the fixed-payment contract, for large enough total payments, under a certain condition on the preference functions; we show that this condition is satisfied for the parameters given by the literature on econometric estimation of the prospect theory model [Tversky and Kahneman 1992;Bruhin et al. 2010]. Since these estimates are based on fitting the prospect theory model to extensive experimental data, this result provides a strong affirmative answer to our question for 'real' population preferences: a principal might indeed choose a fundamentally different kind of mechanism-an output-contingent contest versus a 'safe output-independent scheme-and do better as a result, if he accounts for deviations from the standard economic models of decision-making that are typically used in theoretical design.

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“…Only a narrow class of incomplete markets have been treated so far, [51,45,48], using ad hoc techniques. Further problems of optimal control within CPT were treated in [28,16,24,23] but these are connected to our setting only remotely.…”

Section: Introductionmentioning

confidence: 99%

Skorohod's Representation Theorem and Optimal Strategies for Markets with Frictions

Chau¹,

Rásonyi²

2017

SIAM J. Control Optim.

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We prove the existence of optimal strategies for agents with cumulative prospect theory preferences who trade in a continuous-time illiquid market, transcending known results which pertained only to risk-averse utility maximizers. The arguments exploit an extension of Skorohod's representation theorem for tight sequences of probability measures. This method is applicable in a number of similar optimization problems.

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Optimal contracting with moral hazard and behavioral preferences

Cited by 8 publications

References 19 publications

Profit Sharing in Hedge Funds

Profit Sharing in Hedge Funds

Behavioral Mechanism Design

Skorohod's Representation Theorem and Optimal Strategies for Markets with Frictions

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