Investor Sentiment and (Anti-)Herding in the Currency Market: Evidence from Twitter Feed Data
Xolani Sibande (),
Rangan Gupta (),
Riza Demirer () and
Elie Bouri ()
Additional contact information
Xolani Sibande: Department of Economics, University of Pretoria, Pretoria, South Africa
No 202088, Working Papers from University of Pretoria, Department of Economics
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
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: Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
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 ().