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

Collection
  • Cahiers de recherche; 2005.12
Publication date2005
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 forcasts 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
Citation (ISO format)
HUBER, Philippe, SCAILLET, Olivier, VICTORIA-FESER, Maria-Pia. A latent factor model for ordinal data to measure multivariate predictive ability of financial market movements. 2005
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Identifiers
  • PID : unige:5752
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Technical informations

Creation04/15/2010 12:19:46 PM
First validation04/15/2010 12:19:46 PM
Update time03/14/2023 3:26:26 PM
Status update03/14/2023 3:26:26 PM
Last indexation05/02/2024 11:31:45 AM
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