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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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:
Contact details of provider:
Postal: Bâtiment K2, 4, rue Albert Borschette, L-1246 Luxembourg-Kirchberg
Phone: +352 46 66 44 6335
Fax: +352 46 66 44 6811
Web page: http://wwwen.uni.lu/luxembourg_school_of_finance
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
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
- Drost, Feike C & Nijman, Theo E, 1993.
"Temporal Aggregation of GARCH Processes,"
Econometric Society, vol. 61(4), pages 909-27, July.
- Drost, F.C. & Nijman, T.E., 1993. "Temporal aggregation of GARCH processes," Open Access publications from Tilburg University urn:nbn:nl:ui:12-153273, Tilburg University.
- Drost, F.C. & Nijman, T.E., 1992. "Temporal Aggregation of Garch Processes," Papers 9240, Tilburg - Center for Economic Research.
- Drost, F.C. & Nijman, T.E., 1990. "Temporal Aggregation Of Garch Processes," Papers 9066, Tilburg - Center for Economic Research.
- Drost, F.C. & Nijman, T.E., 1992. "Temporal aggregation of GARCH processes," Discussion Paper 1992-40, Tilburg University, Center for Economic Research.
- Drost, F.C. & Nijman, T.E., 1990. "Temporal aggregation of GARCH processes," Discussion Paper 1990-66, Tilburg University, Center for Economic Research.
- Shiller, Robert J. & Perron, Pierre, 1985.
"Testing the random walk hypothesis : Power versus frequency of observation,"
Elsevier, vol. 18(4), pages 381-386.
- Pierre Perron & Robert J. Shiller, 1984. "Testing the Random Walk Hypothesis: Power Versus Frequency of Observation," Cowles Foundation Discussion Papers 732, Cowles Foundation for Research in Economics, Yale University.
- Robert J. Shiller & Pierre Perron, 1985. "Testing the Random Walk Hypothesis: Power versus Frequency of Observation," NBER Technical Working Papers 0045, National Bureau of Economic Research, Inc.
- Granger, C.W.J. & Siklos, P.L., 1993.
"Systematic Sampling, Temporal Aggregation, Seasonal Adjustment, and Cointegration: Theory and Evidence,"
93001, Wilfrid Laurier University, Department of Economics.
- 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.
- 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.
- Steven Cook, 2001. "Temporal aggregation and time deformation," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 363-365.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Martine Zenner).
If references are entirely missing, you can add them using this form.