An Exploration of How Higher Order Market Effects may Explain and Predict Stock Returns
This note
develops a nonlinear version of the APT and market models with higher order
market moments. I illustrate how these models work for five highly visible
stocks. I show that nonlinearity is a prevalent condition that improves the
understanding of individual stock returns for a given sample. I also find that
nonlinearity may help forecasts in some cases. However, I also show that it is
quite common for all asset pricing models to completely fail to outperform
simple naive forecasts out of sample. The
forecast breakdown has to do with model uncertainty, which I show to be quite
common.
Modalidad: Presencial, Transmisión
en vivo, FBLive IICE.
Detalles: 4 de setiembre
de 2026 a las 12:00 m.d. Miniauditorio, aula 244CE.
Enlace de ZOOM:
https://udecr.zoom.us/j/84617289582?pwd=IoDuyRErGzzObwyFvSKBqmIEcFPHMq.1
ID de
reunión: 846 1728 9582 Código de acceso: 630894