Designing a More Equitable Record Contract for Emerging Artists: A Stochastic Optimization Approach

Abstract

The rise of streaming has transformed almost every aspect of the recorded music industry, but the contracts that major labels use to sign new artists have changed remarkably little in the past two decades. Standard “360” deals continue to feature terms that disproportionately favor the label over the artist, designed for an era in which labels had unparalleled access to distribution. This thesis asks whether such contracts remain economically efficient under modern industry conditions, and develops a quantitative system to answer that question. A jump-diffusion stochastic process is used to model emerging artist streaming growth using data on 200 artists and 10,228 tracks collected from the Spotify Web API, the record contract is formulated as an optimization problem with five decision variables (advance, pre- and post-recoupment royalty rates, contract duration, and recoupment cap), and three alternative formulations (label-optimal subject to a participation constraint, the Pareto frontier, and the Nash bargaining solution) were solved via Sample Average Approximation over 10,000 simulated paths. The results show that the standard 360 deal is strictly Pareto-dominated, as under the baseline contract, the label collects roughly 90% of the expected total surplus while the artist is left with only 10%, less than the artist would expect to earn by operating independently without a label. The Nash bargaining solution, on the other hand, allocates approximately 70% of surplus to the artist through a substantially higher royalty rate and a tight cap on recoupable expenses. This thesis is novel, as it applies stochastic optimization and bargaining theory to record label contract design, with the system providing a quantitative basis for evaluating alternatives to the industry status quo, something not observed in the existing literature.