Monetary policy on Twitter and its effect on asset prices: Evidence from computational text analysis - Jochen Lüdering; Peter Tillmann (Philipps-University Marburg, School of Business and Economics, 2016)
In this paper we dissect the public debate about the future course of monetary policy and trace the effects of selected topics of this discourse on U.S. asset prices. We focus on the "taper tantrum" episode in 2013, a period with large revisions in expectations about Fed policy. Based on a novel data set of 90,000 Twitter messages ("tweets") covering the entire debate of Fed tapering on Twitter we use Latent Dirichlet Allocation, a computational text analysis tool to quantify the content of the discussion. Several estimated topic frequencies are then included in a VAR model to estimate the effects of topic shocks on asset prices. We find that the discussion about Fed policy on social media contains price-relevant information. Shocks to shares of "tantrum"-, "QE"- and "data"-related topics are shown to lead to significant asset price changes. We also show that the effects are mostly due to changes in the term premium of yields consistent with the portfolio balance channel of unconventional monetary policy.
Keywords: E32; E44; E52; 330; Monetary Policy; Fed; Latent Dirichlet Allocation; Text Analysis; VAR