Asset Pricing in the Frequency Domain: Theory and Empirics

By Ian Dew-Becker, Stefano Giglio. 2016

171 citations recorded by the source corpus.

We quantify investors’ preferences over the dynamics of shocks by deriving frequency-specific risk prices that capture the price of risk of consumption fluctuations at each frequency. The frequency-specific risk prices are derived analytically for leading models. The decomposition helps measure the importance of economic fluctuations at different frequencies. We precisely quantify the meaning of "long-run" in the context of Epstein-Zin preferences – centuries – and measure the exact relevance of business-cycle fluctuations. Finally, we estimate frequency-specific risk prices and show that cycles longer than the business cycle – long-run risks – are significantly priced in the equity market. Received January 13, 2015; accepted February 23, 2016 by Editor Leonid Kogan.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/a0550f4c4edb01a6a8850708c938289c8cf340f7

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Citations in the corpus

Measuring the frequency dynamics of financial connectedness and systemic risk (2015, unknown): “As argued by Diebold and Yilmaz (2014, 2012, 2009), variance decompositions can intuitively be used to measure connectedness between economic variables. A natural way to describe its frequency dynamics (the long-term, medium-term, or short-term connectedness) is to consider the spectral representati”
Exploring the dynamic relationships between cryptocurrencies and other financial assets (2018, methodology): “First, we provide the novel empirical evidence on the patterns of return and volatility transmission using the Diebold and Yilmaz [2012] methodology.”