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Author
Chojnowski Michał (Warsaw School of Economics, Poland), Dybka Piotr (Warsaw School of Economics, Poland)
Title
Is exchange rate moody? forecasting exchange rate with google trends data
Source
Econometric Research in Finance, 2017, vol. 2, nr 1, s. 1-21, tab., wykr., bibliogr. 13 poz.
Keyword
Kurs walutowy, Prognozowanie, Analizy głównych komponentów
Exchange rates, Forecasting, Principal Component Analysis (PCA)
Note
JEL clasiffication: C53, F31, F37, G17
summ.
Abstract
This paper proposes a novel method of exchange rate forecasting. We extend the present value model based on observable fundamentals by including three unobserved fundamentals: credit-market, nancial-market, and price-market sentiments. We develop a method of sentiments extraction from Google Trends data on searched queries for different markets. Our method is based on evolutionary algorithms of variable selection and principal component analysis (PCA). Our results show that the extended vector autoregressive model (VAR) which includes markets' sentiment, shows better forecasting capabilities than the model based solely on fundamental variables or the random walk model (naïve forecast).(original abstract)
Accessibility
The Library of Warsaw School of Economics
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Bibliography
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Cited by
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ISSN
2451-1935
2451-2370
Language
eng
URI / DOI
https://doi.org/10.33119/ERFIN.2017.2.1.1
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