(1987). Applied Probability and Queues. Journal of the Operational Research Society: Vol. 38, No. 11, pp. 1095-1096.

https://link.springer.com/content/pdf/10.1057%2Fjors.1987.184.pdf

Applied Probability and Queues

The Theory of Incentives I: The Principal-Agent Model

Continuous exponential martingales and BMO

/pdf/hu-luojia-estimation-of-a-censored-dynamic-panel-data-model-2iacwnj5z3.pdf

Hu, Luojia , Estimation of a censored dynamic panel data model,Econometrica. Journal of the Econometric Society

We consider a general formulation of the principal–agent problem with a lump-sum payment on a finite horizon, providing a systematic method for solving such problems. Our approach is the following. We first find the contract that is optimal among those for which the agent’s value process allows a dynamic programming representation, in which case the agent’s optimal effort is straightforward to find. We then show that the optimization over this restricted family of contracts represents no loss of generality. As a consequence, we have reduced a non-zero-sum stochastic differential game to a stochastic control problem which may be addressed by standard tools of control theory. Our proofs rely on the backward stochastic differential equations approach to non-Markovian stochastic control, and more specifically on the recent extensions to the second order case.

/pdf/dynamic-programming-approach-to-principal-agent-problems-58k6bwe8xd.pdf

Dynamic Programming Approach to Principal-Agent Problems

In this paper, we investigate a moral hazard problem in finite time with lump-sum and continuous payments, involving infinitely many agents with mean-field type interactions, hired by one principal...

A Tale of a Principal and Many, Many Agents

In this paper, we investigate a moral hazard problem in finite time with lump$-$sum and continuous payments, involving infinitely many Agents with mean field type interactions, hired by one Principal. By reinterpreting the mean$-$field game faced by each Agent in terms of a mean field forward backward stochastic differential equation (FBSDE for short), we are able to rewrite the Principal's problem as a control problem of McKean$-$Vlasov SDEs. We review one general approache to tackle it, introduced recently in [1, 43, 44, 45, 46] using dynamic programming and Hamilton$-$Jacobi$-$Bellman (HJB for short) equations, and mention a second one based on the stochastic Pontryagin maximum principle, which follows [10]. We solve completely and explicitly the problem in special cases, going beyond the usual linear$-$quadratic framework. We finally show in our examples that the optimal contract in the $N-$players' model converges to the mean$-$field optimal contract when the number of agents goes to $+\infty$, thus illustrating in our specific setting the general results of [8].

A tale of a Principal and many many Agents

In this paper we study a utility maximization problem with random horizon and reduce it to the analysis of a specific BSDE, which we call BSDE with singular coefficients, when the support of the default time is assumed to be bounded. We prove existence and uniqueness of the solution for the equation under interest. Our results are illustrated by numerical simulations.

https://hal.archives-ouvertes.fr/hal-01126684/document

Utility maximization with random horizon: a BSDE approach

We study the problem of demand response contracts in electricity markets by quantifying the impact of considering a continuum of consumers with mean–field interaction, whose consumption is impacted by a common noise. We formulate the problem as a Principal–Agent problem with moral hazard in which the Principal—she—is an electricity producer who observes continuously the consumption of a continuum of risk‐averse consumers, and designs contracts in order to reduce her production costs. More precisely, the producer incentivizes each consumer to reduce the average and the volatility of his consumption in different usages, without observing the efforts he makes. We prove that the producer can benefit from considering the continuum of consumers by indexing contracts on the consumption of one Agent and aggregate consumption statistics from the distribution of the entire population of consumers. In the case of linear energy valuation, we provide closed‐form expression for this new type of optimal contracts that maximizes the utility of the producer. In most cases, we show that this new type of contracts allows the Principal to choose the risks she wants to bear, and to reduce the problem at hand to an uncorrelated one.

Mean–field moral hazard for optimal energy demand response management

In this paper we provide new conditions for the Malliavin differentiability of solutions of Lipschitz or quadratic BSDEs. Our results rely on the interpretation of the Malliavin derivative as a Gâteaux derivative in the directions of the Cameron-Martin space. Incidentally , we provide a new formulation for the characterization of the Malliavin-Sobolev type spaces $D^{1,p}$ .

/pdf/on-the-malliavin-differentiability-of-bsdes-5268bjd3fp.pdf

Thibaut Mastrolia

Papers

A Tale of a Principal and Many, Many Agents

A tale of a Principal and many many Agents

Utility maximization with random horizon: a BSDE approach

Mean–field moral hazard for optimal energy demand response management

On the Malliavin differentiability of BSDEs