What Triggers Flights to Safety?

Abstract

We apply causality extraction (CE) algorithms on more than 36,000 articles from 2 major financial newspapers (WSJ, FT) and three major newswires (DJ, MNI Market News, Reuters) over the extended period 1980-2020 to shed light on the fundamental triggers of flights to safety. Our CE algorithm searches for sentences that causally-relate flight-to-safety terms to a “cause”, or candidate FTS trigger. Our method identifies nearly 3,000 unique triggers of FTS, which we subsequently allocate using a dictionary-based method to nine economically-motivated primitive categories. While some primitives such as “Funding Liquidity”, “Financial Intermediaries”, or “Pandemic” are only mentioned during specific FTS spells, others such as Political, Geopolitical, Macro, and terms broadly associated with Risk Aversion, Sentiment, and Uncertainty are more generally mentioned as potential triggers of FTS. We additionally show that causal FTS articles are associated with larger market responses (compared to days with noncausal FTS articles), especially if they refer to current (instead of future) FTS events.

Keywords: Flight-to-Safety, Causality Extraction, Textual Analysis

JEL Classification: G11, G12, G14, E43, E44