Start Date
12-13-2015
Description
In a globalized world, the volume of international trade is based on both import and export prices, thereby making a country's economy highly dependent on exchange rates. In order to study exchange rate movements, one frequently exploits the so-called Dornbusch overshooting model. However, the model is controversial from a theoretical point of view: it presupposes the processing of information, though this is not directly reflected by the underlying variables. As a remedy, this paper investigates a potential cognitive bias by including textual news content, thus adjusting for information dissemination. As such, we perform a multivariate analysis to compare the classical overshooting model with an extended variant that includes news sentiment. Our results show that news has a substantial explanatory power of 11% of the exchange rate forecasting error variance. In addition, we also find statistical evidence that a shock in news sentiment may lead to overshooting.
Recommended Citation
Feuerriegel, Stefan; Wolff, Georg; and Neumann, Dirk, "Information Processing of Foreign Exchange News: Extending the Overshooting Model to Include Qualitative Information from News Sentiment" (2015). ICIS 2015 Proceedings. 21.
https://aisel.aisnet.org/icis2015/proceedings/EconofIS/21
Information Processing of Foreign Exchange News: Extending the Overshooting Model to Include Qualitative Information from News Sentiment
In a globalized world, the volume of international trade is based on both import and export prices, thereby making a country's economy highly dependent on exchange rates. In order to study exchange rate movements, one frequently exploits the so-called Dornbusch overshooting model. However, the model is controversial from a theoretical point of view: it presupposes the processing of information, though this is not directly reflected by the underlying variables. As a remedy, this paper investigates a potential cognitive bias by including textual news content, thus adjusting for information dissemination. As such, we perform a multivariate analysis to compare the classical overshooting model with an extended variant that includes news sentiment. Our results show that news has a substantial explanatory power of 11% of the exchange rate forecasting error variance. In addition, we also find statistical evidence that a shock in news sentiment may lead to overshooting.