Investor Sentiment and (Anti-)Herding in the Currency Market: Evidence from Twitter Feed Data

Xolani Sibande (), Rangan Gupta, Riza Demirer and Elie Bouri ()

No 202088, Working Papers from University of Pretoria, Department of Economics

Abstract: This paper investigates (anti) herding in the US foreign exchange market while assessing the role of investor happiness as a predictor of herding. To achieve this objective, it uses dispersion metrics (CSAD and CSSD) and applies OLS regressions with rolling window and quantile-on-quantile regressions (QQR). The results show that the US foreign exchange market is characterized by a strong anti-herding behavior. In normal times, anti-herding and investor happiness are negatively related. However, in extreme bearish and bullish times, investor happiness is associated with more severe anti-herding. The findings are of particular interest to policymakers who are concerned with the stability of the US foreign exchange market.

Keywords: Herding; Exchange Rates; Time-varying Regression; Investor Happiness (search for similar items in EconPapers)
JEL-codes: G15 G40 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2020-09
New Economics Papers: this item is included in nep-isf and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Investor Sentiment and (Anti) Herding in the Currency Market: Evidence from Twitter Feed Data (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202088

Access Statistics for this paper

More papers in Working Papers from University of Pretoria, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Rangan Gupta ().