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

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Author Info

  • Philippe HUBER

    (University of Geneva, HEC and FAME)

  • Olivier SCAILLET

    (University of Geneva, HEC and FAME)

  • Maria-Pia VICTORIA-FESER

    (University of Geneva, HEC and FAME)

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.

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Bibliographic Info

Paper provided by International Center for Financial Asset Management and Engineering in its series FAME Research Paper Series with number rp159.

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Date of creation: Oct 2005
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Handle: RePEc:fam:rpseri:rp159

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Related research

Keywords: structural equation model; latent variable; generalised linear model; factor analysis; multinomial logit; forecasts; LAMLE; canonical correlation;

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