A Latent Factor Model for Ordinal Data to Measure Multivariate Predictive Ability of Financial Market Movements
Author(s) -
Philippe Huber,
Olivier Scaillet,
MariaPia VictoriaFeser
Publication year - 2005
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.855086
Subject(s) - multivariate statistics , measure (data warehouse) , econometrics , factor analysis , ordinal data , latent variable , factor (programming language) , statistics , economics , mathematics , computer science , data mining , programming language
In this paper we develop,a structural equation,model,with latent variables in an ordinal setting which,allows us to test broker-dealer predictive abil- ity 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. Key words: structural equation model, latent variable, generalised lin-
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