Subjective Currency Risk Premia and Deviations from Moving Averages
Steve Furnagiev and
Josh Stillwagon ()
No 1506, Working Papers from Trinity College, Department of Economics
Abstract:
This paper examines the empirical performance of an alternative model of the currency risk premium. The model predicts that the premium on foreign exchange will depend positively on the gap between the exchange rate and its benchmark value. In this paper, we relate the benchmark not to relative prices but to a moving average process in accord with technical analysis. The model is tested against a novel data set of traders' exchange rate forecasts, from 1986:08 to 2013:09, to measure the subjective, ex ante premium. This eliminates the need for a joint hypothesis of rational expectations and enables more direct focus on risk behavior. Using the Cointegrated VAR (CVAR), strong support is found for this hypothesis, as the exchange rate's deviation from a one-year moving average is significant at the 1% level and forms a stationary cointegrating relationship with the premium for the four USD exchange rates examined (against the Swiss franc, Japanese yen, British pound, and Canadian dollar).
Keywords: Exchange rates; risk premia; survey data; IKE gap model; moving average; CVAR (search for similar items in EconPapers)
JEL-codes: F31 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2015-07
New Economics Papers: this item is included in nep-mon and nep-opm
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www3.trincoll.edu/repec/WorkingPapers2015/WP15-06.pdf First version, 2015 (application/pdf)
Related works:
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:tri:wpaper:1506
Access Statistics for this paper
More papers in Working Papers from Trinity College, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Miguel Ramirez ().