Abstract
The aim of this paper is to compare different methods of forecasting exchange rates using methods of multivariate data analysis. Traditional forecasting models like the random walk, prominent structural models and approaches using the forward rate to forecast the spot rate are evaluated. Time series analysis is conducted employing univariate time series models as well as multivariate time series models and error correction models. Model identification, estimation and forecasting are examplified using the DM/US-Dollar exchange rate. Forecasting performance is measured by different criteria, within the scope of the investigation methods of multivariate data analysis are efficiently employed.
Item Type: | Conference or Workshop Item (Paper) |
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Form of publication: | Publisher's Version |
Faculties: | Munich School of Management > Institute for Market-based Management |
Subjects: | 300 Social sciences > 330 Economics |
Place of Publication: | Berlin; Heidelberg |
Language: | English |
Item ID: | 105244 |
Date Deposited: | 02. Aug 2023, 14:42 |
Last Modified: | 02. Aug 2023, 14:42 |