0000000000731877
AUTHOR
S. Muzzioli
Wavelet Analysis Of Variance Risk Premium Spillovers
In this paper we construct a variance risk premium spillover index among France, Germany, UK, Switzerland and the US. The variance risk premium is measured by the difference between the difference between the (square) of implied volatility and expected realized variance of the stock market for next month. We also construct a spillover index for the constituents of the variance risk premium. The series under investigation exhibit long memory properties. The construction of a total spillover indicator suggested by Diebold-Yilmaz (2009) would then rely on modeling a fractionally integrated Vector Autoregressive Model, which might be subject to errors in specifying the correct lag length and th…
Volatility co-movements: a time scale decomposition analysis
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…
Wavelet analysis of variance risk premium spillovers
In this paper we construct a variance risk premium spillover index among France, Germany, UK, Switzerland and the US. The variance risk premium is measured by the difference between the difference between the (square) of implied volatility and expected realized variance of the stock market for next month. We also construct a spillover index for the constituents of the variance risk premium. The series under investigation exhibit long memory properties. The construction of a total spillover indicator suggested by Diebold-Yilmaz (2009) would then rely on modeling a fractionally integrated Vector Autoregressive Model, which might be subject to errors in specifying the correct lag length and th…
Volatility risk premia and financial connectedness
In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to construct an index of connectedness among five European stock markets: France, Germany, UK, Switzerland and the Netherlands, by using volatility risk premia. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. The…
A note on normalization schemes: The case of generalized forecast error variance decompositions
The aim of this paper is to propose new normalization schemes for the values obtained from the generalized forecast error variance decomposition, in order to obtain more reliable net spillover measures. We provide a review of various matrix normalization schemes used in different application domains. The intention is to contribute to the financial econometrics literature aimed at building a bridge between different approaches able to detect spillover effects, such as spatial regressions and network analyses. Considering DGPs characterized by different degrees of correlation and persistence, we show that the popular row normalization scheme proposed by Diebold and Yilmaz (2012), as well as t…