Search results for " Realized Volatility"
showing 3 items of 3 documents
Volatility co-movements: a time-scale decomposition analysis
2015
In this paper, we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers collapse. The analysis is based on a factor decomposition of the covariance matrix, in the time and frequency domain, using wavelets. The analysis aims to disentangle two components of volatility contagion (anticipated and unanticipated by the market). Once we focus on standardized factor loadings, the results show no evidence of contagion (from the US) in market expectations (coming from implied volatility) and evidence of unanticipated contagion (coming from the volatility risk premium) for almost any European country. Finally, the estim…
Volatility co-movements: a time scale decomposition analysis
2014
In this paper we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers’ collapse. The analysis, based on a factor decomposition of the covariance matrix of implied and realized volatilities, is carried for different sub-samples (identified as normal and crisis periods) and across different (high) frequency bands. In particular, the analysis is split in two stages. In the first stage, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and, in a second stage, we apply Maximum Likelihood for a factor de…
Volatility co-movements: a time scale decomposition analysis
2013
In this paper we investigate short-run co-movements before and after the Lehman Brothers’ collapse among the volatility series of US and a number of European countries. The series under investigation (implied and realized volatility) exhibit long-memory and, in order to avoid missspecification errors related to the parameterization of a long memory multivariate model, we rely on wavelet analysis. More specifically, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and we apply Maximum Likelihood for a factor decomposition of the short-run covariance matrix. The empirical evidence…