Konferenzbeitrag
Exchange rate predictability and dynamic Bayesian learning
This paper considers how an investor in foreign exchange markets might exploit predictive information in macroeconomic fundamentals by allowing for switching between multivariate time series regression models. These models are chosen to reflect a wide array of established empirical and theoretical stylized facts. In an application involving monthly exchange rates for seven countries, we find that an investor using our methods to dynamically allocate assets achieves significant gains relative to benchmark strategies. In particular, we find strong evidence for fast model switching, with most of the time only a small set of macroeconomic fundamentals being relevant for forecasting.
- Sprache
-
Englisch
- Erschienen in
-
Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2018: Digitale Wirtschaft - Session: Forecasting II ; No. E05-V1
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
Foreign Exchange
Asset Pricing; Trading Volume; Bond Interest Rates
International Financial Markets
Financial Forecasting and Simulation
- Thema
-
Exchange rates
economic fundamentals
Bayesian vector autoregression
forecasting
dynamic portfolio allocation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Schüssler, Rainer
Beckmann, Joscha
Koop, Gary
Korobilis, Dimitris
- Ereignis
-
Veröffentlichung
- (wer)
-
ZBW - Leibniz-Informationszentrum Wirtschaft
- (wo)
-
Kiel, Hamburg
- (wann)
-
2018
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Konferenzbeitrag
Beteiligte
- Schüssler, Rainer
- Beckmann, Joscha
- Koop, Gary
- Korobilis, Dimitris
- ZBW - Leibniz-Informationszentrum Wirtschaft
Entstanden
- 2018