The purpose of this paper is to present a rank based approach to cross-sectional linear factor modelling. The emphasis is on approximating factor exposures in a consistent manner in order to facilitate the merging of subjective information (from professional investors) with objective information (from accounting data and/or state of the art quantitative models) in a statistically rigorous way without needing to impose the unrealistic simplifying assumptions typical of more standard time series models. We deal with the problems of identifying country and sector returns by an innovative hierarchical factor structure. This is all discussed from the perspective that investment models are not immutable but rather need to be designed with characteristics that are fit for their purpose; for example, returning aggregate county and sector forecasts that are consistent by construction.
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