Policy News and Stock Market Volatility
By Scott R. Baker, Nicholas Bloom, Steven J. Davis, Kyle J Kost. Social Science Research Network, 2019
286 citations recorded by the source corpus.
We create a newspaper-based Equity Market Volatility (EMV) tracker that moves with the VIX and with the realized volatility of returns on the S&P 500. Parsing the underlying text, we find that 72 percent of EMV articles discuss the Macroeconomic Outlook, and 44 percent discuss Commodity Markets. Policy news is another major source of volatility: 35 percent of EMV articles refer to Fiscal Policy (mostly Tax Policy), 30 percent discuss Monetary Policy, 25 percent refer to one or more forms of Regulation, and 13 percent mention National Security matters. The contribution of particular policy areas fluctuates greatly over time. Trade Policy news, for example, went from a virtual nonfactor in equity market volatility to a leading source after Donald Trump’s election and especially after the intensification of U.S-China trade tensions. The share of EMV articles with attention to government policy rises over time, reaching its peak in 2017-18. We validate our measurement approach in various ways. For example, tailoring our EMV tracker to news about petroleum markets yields a measure that rises and falls with the implied and realized volatility of oil prices.
Subfields: Economics and Econometrics, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/ce0b13937e630c6e3902396093898ae04e7813b2
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In Economics and Econometrics
- Steven J. Davis
- Scott R. Baker
- Nicholas Bloom
- Kyle J Kost
- Efrem Castelnuovo
- Giovanni Caggiano
- Rangan Gupta
- Angus Moore
In Management Science and Operations Research
Citations in the corpus
- The Unprecedented Stock Market Reaction to COVID-19 (2020, background): “The same is true with respect to realized stockmarket volatility, as shown by Baker et al. (2019).”
- Policy Uncertainty in Japan (2017, unknown): “Alexopoulos and Cohen (2015), Hlatshwayo and Saxegaard (2016), Azzimonti (2018), Caldara and Iacoviello (2018), Hassan et al. (2019), Husted, Rogers and Sun (2020) and Baker et al. (2019, 2022), among others, also use text analysis to quantify policy uncertainty and related concepts.”