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Title: Asset pricing using time-frequency dependent network centrality Authors:  Michael Ellington - University of Liverpool (United Kingdom) [presenting]
Jozef Barunik - UTIA AV CR vvi (Czech Republic)
Abstract: A framework is provided where time-frequency dependent network centrality links to expected excess return of financial assets. Noting that investors trade on different horizons, it is essential to understand how the connectedness of a system influences risk premium over the short-, medium- and long-term. Viewing the market as being generated by a time-varying parameter VAR model implies that a shock to the $j$-th asset is time-frequency dependent. This creates a network of time-frequency connections among all assets in the market. We propose a new measure of time-frequency dependent network centrality and apply this to all stocks listed on the S\&P500. Our findings indicate that our time-frequency dependent measures significantly price assets; particularly over the longer-term.