Multifractality in the Random Parameters Model
The Random Parameters model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore other properties of the model, like the scaling of its PDF as one take larger scales. Special attention is given to the multifractal structure of the model time series, which revealed a scaling structure compatible with the known stylized facts for a reasonable choice of the parameter values.
References listed on IDEAS
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.:
- R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
- Andre C. R. Martins, 2007. "Random, but not so much: A parameterization for the returns and correlation matrix of financial time series," Papers physics/0701025, arXiv.org.
When requesting a correction, please mention this item's handle: RePEc:arx:papers:0710.5497. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators)
If references are entirely missing, you can add them using this form.