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Times series Factorial models with incertitute measures on ARMA processes and its application to final data


  • Terraza Virginie

    () (Luxembourg School of Finance, University of Luxembourg)

  • Toque Carole

    () (Luxembourg School of Finance, University of Luxembourg)


In 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. "Keywords: fund’s rating; performance; factor analysis; incertitude measures" "Classification-JEL: C10; G20"

Suggested Citation

  • Terraza Virginie & Toque Carole, 2008. "Times series Factorial models with incertitute measures on ARMA processes and its application to final data," LSF Research Working Paper Series 08-07, Luxembourg School of Finance, University of Luxembourg.
  • Handle: RePEc:crf:wpaper:08-07

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    References listed on IDEAS

    1. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-927, July.
    2. Shiller, Robert J. & Perron, Pierre, 1985. "Testing the random walk hypothesis : Power versus frequency of observation," Economics Letters, Elsevier, vol. 18(4), pages 381-386.
    3. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    4. Steven Cook, 2001. "Temporal aggregation and time deformation," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 363-365.
    5. Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    6. Granger, C. W. J. & Siklos, Pierre L., 1995. "Systematic sampling, temporal aggregation, seasonal adjustment, and cointegration theory and evidence," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 357-369.
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    More about this item

    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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