News effects in a high‐frequency model of the sterling‐dollar exchange rate

TLDR

The study investigates how news events influence very short‑term movements in the sterling‑dollar exchange rate using an extremely high‑frequency data set. The authors analyze 130,000 high‑frequency observations over eight weeks, applying regression models with time‑varying conditional variance and incorporating news announcement effects on both the exchange‑rate level and its volatility. Adding news effects and a time‑varying variance model markedly alters the conclusions relative to simpler models.

Abstract

Abstract This paper uses an extremely high frequency data set on the dollar‐sterllng exchange rate to investigate the impact of news events on the very short‐term movements in exchange rates. The data set is a continuous record of the quoted price for the exchange rate on the Reuters screen. As such it records some 130,000 observations over an 8‐week period. The paper investigates the time‐series properties of the data using orthodox regression models, and then by making allowance for a time‐varying conditional variance. The conclusions vary significantly in moving to this more sophisticated model. The exercises are repeated now incorporating news announcement effects, letting these affect the level of the exchange rate and then the conditional variance process. Again it is found that the conclusions are radically altered in moving to the increasingly sophisticated model.