[1] empirically investigates FX markets and shows that demand shocks propagate across currencies and asset markets through three traded FX risk factors.
[2] empirically investigates stock markets and shows that factor‐level quantity information helps explain the cross-section of expected stock returns.
[3] develops a beta-based foundation for aggregating asset-level quantities to portfolios, diagnoses the heuristic weight-averaging used in current empirics, and shows that market-neutral long-short portfolios have zero net supply—so percentage-change elasticities are inapplicable.
[4] and [5] develop the general theory starting from P = E[MX]. The key innovation is an arbitrage-based characterization of the price-quantity relationship in the cross-section of assets.
[4] focuses solely on the demand effect, examining how quantities influence the pricing kernel M. This utility‑free approach generalizes the mean‑variance model as a special case.
[5] incorporates the information effect, examining how the payoff X is updated based on trading quantities. This distribution-free approach generalizes the normal-distribution updating model as a special case.
[6] shows that the factor model of price impact is a natural generalization of the traditional mean-variance model in a dynamic setting where investor trading is predictable.