Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices

@article{Georgoula2015UsingTA,
  title={Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices},
  author={Ifigeneia Georgoula and Demitrios Pournarakis and Christos Bilanakos and Dionisios N. Sotiropoulos and George M. Giaglis},
  journal={ERN: Management of Technological Innovation \& R\&D in Developing Economies (Topic)},
  year={2015}
}
This paper uses time-series analysis to study the relationship between Bitcoin prices and fundamental economic variables, technological factors and measurements of collective mood derived from Twitter feeds. Sentiment analysis has been performed on a daily basis through the utilization of a state-of-the-art machine learning algorithm, namely Support Vector Machines (SVMs). A series of short-run regressions shows that the Twitter sentiment ratio is positively correlated with Bitcoin prices. The… 
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References

SHOWING 1-10 OF 24 REFERENCES
Exploring the Determinants of Bitcoin Exchange Rate
Bitcoin, a digital currency created based on modern P2P and cryptograph technologies, has ignited much discussion among professionals. However, there is a lack of empirical understanding about the
Twitter mood predicts the stock market
Nowcasting the Bitcoin Market with Twitter Signals
TLDR
The conclusion of this paper is that the microblogging platform Twitter is Bitcoin's virtual trading floor, emotionally reflecting its trading dynamics.
The economics of BitCoin price formation
ABSTRACT This is the first article that studies BitCoin price formation by considering both the traditional determinants of currency price, e.g., market forces of supply and demand, and digital
BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era
TLDR
It is shown that not only are the search queries and the prices connected but there also exists a pronounced asymmetry between the effect of an increased interest in the currency while being above or below its trend value.
Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
This book gives a detailed mathematical and statistical analysis of the cointegrated vector autoregresive model. This model had gained popularity because it can at the same time capture the short-run
The Purchasing Power of Money; Its Determination and Relation to Credit, Interest and Crises . By Irving Fisher, assisted by Harry G. Brown. New York, The Macmillan Company. 1911. Pp. xxii + 505.
RareBooksClub. Paperback. Book Condition: New. This item is printed on demand. Paperback. 142 pages. Dimensions: 9.7in. x 7.4in. x 0.3in.This historic book may have numerous typos and missing text.
Widespread Worry and the Stock Market
TLDR
It is demonstrated that estimating emotions from weblogs provides novel information about future stock market prices, and how the mood of millions in a large online community, even one that primarily discusses daily life, can anticipate changes in a seemingly unrelated system.
Applied Econometric Time Series
PREFACE. ABOUT THE AUTHOR. Chapter DIFFERENCE EQUATIONS . 1 Time-Series Models. 2 Difference Equations and Their Solutions. 3 Solution by Iteration. 4 An Alternative Solution Methodology. 5 The
...
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