We find a nonlinear dependence between an indicator of the degree of multiscaling of log-price time series of a stock and the average correlation of the stock with respect to the other stocks traded in the same market. This result is a robust stylized fact holding for different financial markets. We investigate this result conditional on the stocks' capitalization and on the kurtosis of stocks' log-returns in order to search for possible confounding effects. We show that a linear dependence with the logarithm of the capitalization and the logarithm of kurtosis does not explain the observed stylized fact, which we interpret as being originated from a deeper relationship
Of much interest in financial econometrics is the recovery of joint distributional behaviour of coll...
We propose a set of dependence measures that are non-linear, local, invariant to a wide range of tra...
Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongo...
We find a nonlinear dependence between an indicator of the degree of multiscaling of log-price time ...
We report evidence of a deep interplay between cross-correlations hierarchical properties and multif...
We investigate the correlation properties of transaction data from the New York Stock Exchange. The ...
In a Seemingly Unrelated Regression Estimation (SURE) framework, we examine the Granger-causal linka...
We show that expected returns on US stocks and all major global stock market indices have a particul...
Understanding financial asset return correlation is a key facet in asset allocation and investor’s p...
The normality of multi-asset returns in event time is shown empirically. A multivariate subordinatio...
International audienceUsing one of the key properties of copulas that they remain invariant under an...
The thesis is composed of three parts. Part I introduces the mathematical and statistical tools that...
We discuss two elements that define the complexity of financial time series: one is the multiscaling...
Modeling and estimation of correlation coefficients is a fundamental step in risk management, especi...
The paper explores the properties of a class of multivariate Lévy processes used for asset returns. ...
Of much interest in financial econometrics is the recovery of joint distributional behaviour of coll...
We propose a set of dependence measures that are non-linear, local, invariant to a wide range of tra...
Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongo...
We find a nonlinear dependence between an indicator of the degree of multiscaling of log-price time ...
We report evidence of a deep interplay between cross-correlations hierarchical properties and multif...
We investigate the correlation properties of transaction data from the New York Stock Exchange. The ...
In a Seemingly Unrelated Regression Estimation (SURE) framework, we examine the Granger-causal linka...
We show that expected returns on US stocks and all major global stock market indices have a particul...
Understanding financial asset return correlation is a key facet in asset allocation and investor’s p...
The normality of multi-asset returns in event time is shown empirically. A multivariate subordinatio...
International audienceUsing one of the key properties of copulas that they remain invariant under an...
The thesis is composed of three parts. Part I introduces the mathematical and statistical tools that...
We discuss two elements that define the complexity of financial time series: one is the multiscaling...
Modeling and estimation of correlation coefficients is a fundamental step in risk management, especi...
The paper explores the properties of a class of multivariate Lévy processes used for asset returns. ...
Of much interest in financial econometrics is the recovery of joint distributional behaviour of coll...
We propose a set of dependence measures that are non-linear, local, invariant to a wide range of tra...
Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongo...