A latent factor model for ordinal data to measure multivariate predictive ability of financial market movements

Philippe Huber, Olivier Scaillet and Maria-Pia Victoria-Feser ()
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Philippe Huber: University of Geneva, HEC and FAME

FAME Research Paper Series from International Center for Financial Asset Management and Engineering

Abstract: In this paper we develop a structural equation model with latent variables in an ordinal setting which allows us to test broker-dealer predictive ability of financial market movements. We use a multivariate logit model in a latent factor framework, develop a tractable estimator based on a Laplace approximation, and show its consistency and asymptotic normality. Monte Carlo experiments reveal that both the estimation method and the testing procedure perform well in small samples. An empirical illustration is given for mid-term forecasts simultaneously made by two broker-dealers for several countries.

Keywords: structural equation model; latent variable; generalised linear model; factor analysis; multinomial logit; forecasts; LAMLE; canonical correlation (search for similar items in EconPapers)
JEL-codes: C12 C13 C30 C51 C52 C53 G10 (search for similar items in EconPapers)
Date: 2005-10
New Economics Papers: this item is included in nep-bec, nep-dcm, nep-ecm, nep-fin and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:fam:rpseri:rp159

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