Times series Factorial models with incertitute measures on ARMA processes and its application to final data
AbstractIn this paper, we propose a non-parametric structural approach in order to define new pertinent criterion in the selection process of time series. This approach combines a technical analysis of oscillators derived from Wilder (1978) and the Shannon (1948) theory of information, with factorial techniques of visualization. In identifying classes of times series, using reference graphic models and pertinent criteria to better select appropriate models, this structural approach must be a first process to forecast models on significant entropies. First, we apply this approach on simulated ARMA processes, to show significant groupings and oppositions explained by entropies, and to return some well known properties of autocorrelations functions. In the second one, we use the methodology to derive groups of funds based on their ratings. We observe that the Luxembourg funds are characterized by reductions of incertitude measured on Europerformance ratings against the French funds which are characterized by reductions of incertitude on Morningstar ratings, according their performance with incertitude reductions measured on daily returns.
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Bibliographic InfoPaper provided by Luxembourg School of Finance, University of Luxembourg in its series LSF Research Working Paper Series with number 08-07.
Date of creation: 2008
Date of revision:
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More information through EDIRC
fund’s rating; performance; factor analysis; incertitude measures;
Find related papers by JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- G20 - Financial Economics - - Financial Institutions and Services - - - General
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