- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2199-4730
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Forecasting cryptocurrency returns and volume using search engines ; volume:5 ; number:1 ; day:10 ; month:1 ; year:2019 ; pages:1-13 ; date:12.2019
Financial innovation ; 5, Heft 1 (10.1.2019), 1-13, 12.2019
- Classification
-
Wirtschaft
- Creator
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s40854-018-0119-8
- URN
-
urn:nbn:de:101:1-2019021623031250589743
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:52 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Nasir, Muhammad Ali
- Huynh, Toan Luu Duc
- Sang Phu Nguyen
- Duy Duong
- SpringerLink (Online service)
Other Objects (12)
Forecasting cryptocurrency returns and volume using search engines
Forecasting the returns of cryptocurrency: A model averaging approach
Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms
The Cross-Section of Cryptocurrency Risk and Return
Cryptocurrency returns: short-term forecast using Google Trends
Predictability of cryptocurrency returns: evidence from robust tests
Introduction to video search engines
Search Engines for Shape Selectivity
Cryptocurrency co-investment network: token returns reflect investment patterns
Recent developments in cryptocurrency markets: Co-movements, spillovers and forecasting
Cryptocurrency
Spatial data and the Search engines
Forecasting cryptocurrency returns and volume using search engines
Forecasting the returns of cryptocurrency: A model averaging approach
Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms
The Cross-Section of Cryptocurrency Risk and Return
Cryptocurrency returns: short-term forecast using Google Trends
Predictability of cryptocurrency returns: evidence from robust tests
Introduction to video search engines
Search Engines for Shape Selectivity
Cryptocurrency co-investment network: token returns reflect investment patterns
Recent developments in cryptocurrency markets: Co-movements, spillovers and forecasting
Cryptocurrency
Spatial data and the Search engines
Forecasting cryptocurrency returns and volume using search engines
Forecasting the returns of cryptocurrency: A model averaging approach
Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms
The Cross-Section of Cryptocurrency Risk and Return
Cryptocurrency returns: short-term forecast using Google Trends
Predictability of cryptocurrency returns: evidence from robust tests
Introduction to video search engines
Search Engines for Shape Selectivity
Cryptocurrency co-investment network: token returns reflect investment patterns
Recent developments in cryptocurrency markets: Co-movements, spillovers and forecasting
Cryptocurrency