Long memory and multifractality: a joint test

John Goddard, Enrico Onali

Research output: Working paper

Abstract

The properties of statistical tests for hypotheses concerning the parameters of the multifractal model of asset returns (MMAR) are investigated, using Monte Carlo techniques. We show that, in the presence of multifractality, conventional tests of long memory tend to over-reject the null hypothesis of no long memory. Our test addresses this issue by jointly estimating long memory and multifractality. The estimation and test procedures are applied to exchange rate data for 12 currencies. In 11 cases, the exchange rate returns are accurately described by compounding a NIID series with a multifractal time-deformation process. There is no evidence of long memory.
Original languageEnglish
Publication statusUnpublished - Jan 2016

Fingerprint

Long memory
Currency
Exchange rate returns
Asset returns
Statistical tests
Exchange rates

Keywords

  • multifractality
  • long memory
  • volatility clustering
  • exchange rate returns

Cite this

Goddard, J., & Onali, E. (2016). Long memory and multifractality: a joint test.
Goddard, John ; Onali, Enrico. / Long memory and multifractality : a joint test. 2016.
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Goddard, J & Onali, E 2016 'Long memory and multifractality: a joint test'.

Long memory and multifractality : a joint test. / Goddard, John; Onali, Enrico.

2016.

Research output: Working paper

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Goddard J, Onali E. Long memory and multifractality: a joint test. 2016 Jan.