A New Approach to Principal-Agent Problems with Volatility Control
Abstract
Abstract. The recent work by Cvitanić, Possamaï, and Touzi [ Finance Stoch., 22 (2018), pp. 1–37] presents a general approach for continuous-time principal-agent problems through dynamic programming and second-order backward stochastic differential equations (BSDEs). In this paper, we provide an alternative formulation of the principal-agent problem, which can be solved simply by relying on the theory of BSDEs. This reformulation is strongly inspired by an important remark in Cvitanić, Possamaï, and Touzi, namely, that if the principal observes the output process [Formula: see text] in continuous time, then she can compute its quadratic variation pathwise. While in Cvitanić, Possamaï, and Touzi this information is used in the contract, our reformulation consists in assuming that the principal could directly control this process in a “first-best” fashion. The resolution approach for this alternative problem actually follows the line of the so-called Sannikov’s trick in the literature on continuous-time principal-agent problems, as originally introduced by Sannikov [ Rev. Econ. Stud., 75 (2008), pp. 957–984]. We then show that the solution to this incentivize first-best formulation is identical to the solution of the original problem. More precisely, using the contract form introduced in Cvitanić, Possamaï, and Touzi as penalization contracts, we highlight that this first-best scenario can be achieved even if the principal cannot directly control the quadratic variation. Nevertheless, we do not have to rely on the theory of BSDEs of the second order to prove that such contracts are optimal, as their optimality is ensured by showing that the first-best scenario is achieved. We believe that this more straightforward approach to solve principal-agent problems with volatility control will facilitate the dissemination of these problems across many fields and its extension to even more intricate problems.
Fields of Study & Subjects
Aquatic and Environmental Studies
Advanced Research in Systems and Signal Processing
Publication details
- Journal / source
- SIAM Journal on Control and Optimization
- Publisher
- Society for Industrial & Applied Mathematics (SIAM)
- Volume
- 64
- Issue
- 3
- Pages
- 1760–1799
- Publication date
- 5 June 2026
- Language
- EN