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
This paper seeks to understand the long memory behaviour of global equity returns using novel method...
The hereto article indicates how multifractals related ideas can contribute to the modelling of the ...
Abstract: Multi-fractal processes have been proposed as a new formalism for modeling the time series...
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in ...
The properties of statistical tests for hypotheses concerning the parameters of the multifractal mod...
The properties of statistical tests for hypotheses concerning the parameters of the multifractal mod...
The behaviors of fat-tailed distribution, linear long memory, and nonlinear long memory are consider...
This paper explores extensions to the random walk model for time series in finance. There is some di...
International audienceThis paper investigates the multifractal model of asset returns (MMAR), a clas...
This paper presents the first empirical investigation of the Multifractal Model of Asset Returns (“MM...
Financial processes may possess long memory and their probability densities may display heavy tails....
The thesis shows the relationship between the persistence in the financial markets returns and their...
Cowles Foundation Discussion Paper, n° 1166/1997This paper presents the first empirical investigatio...
Existing empirical evidence of distributional scaling in financial returns has helped motivate the u...
Cowles Foundation Discussion Paper, n° 1164/1997This paper presents the multifractal model of asset ...
This paper seeks to understand the long memory behaviour of global equity returns using novel method...
The hereto article indicates how multifractals related ideas can contribute to the modelling of the ...
Abstract: Multi-fractal processes have been proposed as a new formalism for modeling the time series...
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in ...
The properties of statistical tests for hypotheses concerning the parameters of the multifractal mod...
The properties of statistical tests for hypotheses concerning the parameters of the multifractal mod...
The behaviors of fat-tailed distribution, linear long memory, and nonlinear long memory are consider...
This paper explores extensions to the random walk model for time series in finance. There is some di...
International audienceThis paper investigates the multifractal model of asset returns (MMAR), a clas...
This paper presents the first empirical investigation of the Multifractal Model of Asset Returns (“MM...
Financial processes may possess long memory and their probability densities may display heavy tails....
The thesis shows the relationship between the persistence in the financial markets returns and their...
Cowles Foundation Discussion Paper, n° 1166/1997This paper presents the first empirical investigatio...
Existing empirical evidence of distributional scaling in financial returns has helped motivate the u...
Cowles Foundation Discussion Paper, n° 1164/1997This paper presents the multifractal model of asset ...
This paper seeks to understand the long memory behaviour of global equity returns using novel method...
The hereto article indicates how multifractals related ideas can contribute to the modelling of the ...
Abstract: Multi-fractal processes have been proposed as a new formalism for modeling the time series...