Browsing Research Output by Author "Luciani, Matteo"
Estimating and Forecasting Large Panels of Volatilities with Approximate Dynamic Factor ModelsVeredas, David; Luciani, Matteo (Journal of Forecasting, 2015)We introduce an approximate dynamic factor model for modeling and forecasting large panels of realized volatilities. Since the model is estimated by means of principal components and low-dimensional maximum likelihood, it does not suffer from the curse of dimensionality. We apply the model to a panel of 90 daily realized volatilities pertaining to S&P 100 from January 2001 to December 2008. Results show that our model is able to capture the stylized facts of panels of volatilities (comovements, clustering, long memory, dynamic volatility, skewness and heavy tails), and that it performs fairly well in forecasting, in particular in periods of turmoil, in which it outperforms standard univariate benchmarks. Copyright © 2015?John Wiley & Sons
Surfing through the GFC: Systemic Risk in AustraliaDungey, Mardi; Luciani, Matteo; Matei, Marius; Veredas, David (Economic Record, 2017)We provide empirical evidence on the degree of systemic risk in Australia before, during and after the global financial crisis. We calculate a daily index of systemic risk from 2004 to 2013 in order to understand how real economy firms influence the outcomes for the rest of the economy. This is done via a mapping of the interconnectedness of the financial and non-financial sectors. The financial sector is in general home to the most consistently systemically risky firms in the economy. The materials sector occasionally becomes as systemically risky as the financial sector, reflecting the importance of understanding these linkages.
Systemic risk in the US: Interconnectedness as a circuit breakerDungey, Mardi; Luciani, Matteo; Veredas, David (Economic Modelling, 2018)We measure systemic risk via the interconnections between the risks facing both financial and real economy firms. SIFIs are ranked by building on the Google PageRank algorithm for finding closest connections. For a panel of over 500 US firms over 2003–2011 we find evidence that intervention programs (such as TARP) act as circuit breakers in crisis propagation. The curve formed by the plot of firm average systemic risk against its variability clearly separates financial firms into three groups: (i) the consistently systemically risky (ii) those displaying the potential to become risky and (iii) those of little concern for macro-prudential regulators.