Mean-Variance

TL;DR for operators A portfolio does not care whether your signal has a beautiful causal origin story. It cares whether the signal points in roughly the right direction, ranks assets usefully, and is scaled well enough not to produce absurd weights. That is the useful, slightly impolite message of Alejandro Rodriguez Dominguez’s paper, Is Causality Necessary for Efficient Portfolios?1 The paper challenges a strong claim in recent causal factor-investing work: that causal factor models are necessary for investment efficiency. Its answer is narrower and more operational. Within static mean-variance and related quadratic optimisation frameworks, causal identification is not the necessary condition. The necessary operating conditions are geometric. ...

TL;DR for operators Shi and Xu’s paper asks a deceptively simple question: what if a market regime change is not just a new label on the same price process, but a price shock in its own right?1 That matters because many portfolio systems treat regimes as parameter containers. In regime 1, volatility is low, drift is healthy, jump intensity is manageable. In regime 2, the numbers change. The model switches shelves, picks a new parameter set, and carries on. Fine, as far as it goes. The market, being less polite than the model, often gaps before anyone has finished updating the spreadsheet. ...

TL;DR for operators A trader usually asks, “What is the signal now?” This paper asks a more expensive question: “What did the signal do on the way here?” That difference matters when alpha does not decay instantly, when order flow moves prices slowly, or when volatility changes the usefulness of the same forecast. ...