This study analyses volatility persistence of the U.S. stock market, after taking into account the role of breaks and outliers. By employing a wavelet-based algorithm, it identifies several outliers which are comfortably associated with major events such as the ‘Black Monday’ and the Asian crisis. There is also evidence of clustering of breaks and a substantial variation in the properties of the identified segments
In this article, we test for the presence of structural breaks in volatility by two alternative app...
Outliers of moderate magnitude cause large changes in financial time series of prices and returns an...
This article tests for periodic breaks in the unconditional variance of stock return data on two Chi...
This study analyses volatility persistence of the U.S. stock market, after taking into account the r...
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and po...
International audienceFinancial market participants and policy-makers can benefit from a better unde...
Financial time-series may exhibit breakpoints in unconditional variance due, possibly, to institutio...
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and poo...
The paper evaluates the performance of several recently proposed tests for structural breaks in cond...
The volatility of financial instruments is rarely constant, and usually varies over time. This creat...
The paper evaluates the performance of several recently proposed tests for structural breaks in cond...
Outliers can lead to model misspecifications, poor forecasts and invalid inferences. Their identific...
In this article, we contribute to the discussion of volatility persistence in the presence of sudden...
In this article, we test for the presence of structural breaks in volatility by two alternative app...
Outliers of moderate magnitude cause large changes in financial time series of prices and returns an...
This article tests for periodic breaks in the unconditional variance of stock return data on two Chi...
This study analyses volatility persistence of the U.S. stock market, after taking into account the r...
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and po...
International audienceFinancial market participants and policy-makers can benefit from a better unde...
Financial time-series may exhibit breakpoints in unconditional variance due, possibly, to institutio...
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and poo...
The paper evaluates the performance of several recently proposed tests for structural breaks in cond...
The volatility of financial instruments is rarely constant, and usually varies over time. This creat...
The paper evaluates the performance of several recently proposed tests for structural breaks in cond...
Outliers can lead to model misspecifications, poor forecasts and invalid inferences. Their identific...
In this article, we contribute to the discussion of volatility persistence in the presence of sudden...
In this article, we test for the presence of structural breaks in volatility by two alternative app...
Outliers of moderate magnitude cause large changes in financial time series of prices and returns an...
This article tests for periodic breaks in the unconditional variance of stock return data on two Chi...