US Equity Market Volatility Index

Download Data

We create a text-based Equity Market Volatility Index that tracks the CBOE Volatility Index (VIX). Our tracking method relies on frequency counts of articles about the (E)conomy, Stock (M)arket and (V)olatility in eleven major US newspapers: the Miami Herald, Dallas Morning News, Houston Chronicle, San Francisco Chronicle, USA Today, New York Times, Los Angeles Times, Boston Globe, Chicago Tribune, Wall Street Journal, and Washington Post.

To construct our monthly Equity Market Volatility (EMV) Index, we proceed in four steps: First, for each newspaper and month, we count articles that contain one or more terms in each of the following three sets:

  • E: economic, economy, financial
  • M: "stock market", equity, equities "Standard and Poors", "Standard & Poors", "Standard and Poor", "Standard and Poor's", "Standard & Poor's"
  • V: uncertain, uncertainty, risk, risky, volatile, volatility

Second, we scale the raw monthly counts of EMV articles by the total number of articles in the same newspaper and month. Third, we standardize each paper's scaled frequency counts to have a unit standard deviation from January 1985 to December 2017. This step gives us a standardized, scaled monthly index for each newspaper. Fourth, we average over the eleven newspaper-level indices by month to obtain an overall EMV Index, which we normalize to the same mean value as the VIX from 1985 to 2017.

We selected the E, M and V term sets from a larger set of candidate terms to maximize the fit in a time-series regression of the VIX on our EMV Index. See "Messages from a Text-Based Volatility Tracker" by Scott R. Baker, Nick Bloom, Steven J. Davis and Kyle Kost for details.

Our paper also specifies additional terms that we use to quantify the proximate forces behind equity market volatility and movements in our EMV Index over time. We allocate these forces to various policy and non-policy categories. Major categories include Macroeconomic News and Outlook, Commodities, Interest Rates, Fiscal Policy, Monetary Policy, Regulation, and National Security Policy. See our paper for details.

Finally, we combine our category-level allocations with our EMV Index to construct an Index of Policy-Related Equity Market Volatility. To do so, we compute the following ratio for each newspaper and month: (Number of EMV articles in policy-related categories)/(Number of EMV articles in all categories). We then average this ratio over newspapers by month. As a final step, we multiply this average policy ratio in a given month by the EMV Index value in the same month to obtain our Policy-Related EMV Index value for that month. We normalize the Policy-Related EMV Index to a mean of 100 from 1985 to 2009. See our paper for additional information.

Our daily US Equity Market Uncertainty Index, which relies on different text sources and a somewhat different methodology, is available here.