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Examining the relationships among cryptocurrencies using Google Trends
Název práce v češtině: Zkoumání vztahů mezi kryptoměnami pomocí nástroje Google Trends
Název v anglickém jazyce: Examining the relationships among cryptocurrencies using Google Trends
Klíčová slova: Bitcoin, Litecoin, Ethereum, Ethereum classic, kryptoměny, finanční trhy, vektorová autoregrese, Google Trends
Klíčová slova anglicky: Bitcoin, Litecoin, Ethereum, Ethereum classic, cryptocurrencies, financial markets, vector autoregression analysis, Google Trends
Akademický rok vypsání: 2017/2018
Typ práce: bakalářská práce
Jazyk práce: angličtina
Ústav: Institut ekonomických studií (23-IES)
Vedoucí / školitel: prof. PhDr. Ladislav Krištoufek, Ph.D.
Řešitel: skrytý - zadáno vedoucím/školitelem
Datum přihlášení: 11.05.2018
Datum zadání: 11.05.2018
Datum a čas obhajoby: 10.06.2019 09:00
Místo konání obhajoby: Opletalova - Opletalova 26, O314, Opletalova - místn. č. 314
Datum odevzdání elektronické podoby:09.05.2019
Datum proběhlé obhajoby: 10.06.2019
Oponenti: Mgr. Hana Džmuráňová, Ph.D.
 
 
 
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Seznam odborné literatury
Bibliography

1. KRISTOUFEK, Ladislav. BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports [online]. 2013, 3(1), - [cit. 2018-05-17]. DOI: 10.1038/srep03415. ISSN 2045-2322. Dostupné z: http://www.nature.com/articles/srep03415

2. YELOWITZ, Aaron a Matthew WILSON. Characteristics of Bitcoin users: an analysis of Google search data. Applied Economics Letters [online]. 2015, 22(13), 1030-1036 [cit. 2018-05-17]. DOI: 10.1080/13504851.2014.995359. ISSN 1350-4851. Dostupné z: http://www.tandfonline.com/doi/full/10.1080/13504851.2014.995359

3. GARCIA, D., C. J. TESSONE, P. MAVRODIEV a N. PERONY. The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy. Journal of The Royal Society Interface [online]. 2014, 11(99), 20140623-20140623 [cit. 2018-05-17]. DOI: 10.1098/rsif.2014.0623. ISSN 1742-5689. Dostupné z: http://rsif.royalsocietypublishing.org/cgi/doi/10.1098/rsif.2014.0623

4. CHEAH, Eng-Tuck a John FRY. Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters [online]. 2015, 130, 32-36 [cit. 2018-05-17]. DOI: 10.1016/j.econlet.2015.02.029. ISSN 01651765. Dostupné z: http://linkinghub.elsevier.com/retrieve/pii/S0165176515000890

5. KRISTOUFEK, Ladislav a Enrico SCALAS. What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis. PLOS ONE [online]. 2015, 10(4), e0123923- [cit. 2018-05-17]. DOI: 10.1371/journal.pone.0123923. ISSN 1932-6203. Dostupné z: http://dx.plos.org/10.1371/journal.pone.0123923

6. LÜTKEPOHL, Helmut a Markus KRÄTZIG, ed. Applied time series econometrics. Cambridge: Cambridge University Press, c2004. ISBN 0-521-83919-X.

7. KOČENDA, Evžen a Alexandr ČERNÝ. Elements of time series econometrics: an applied approach. Third edition. Prague: Charles University in Prague, Karolinum Press, 2015. ISBN 978-80-246-3199-8.

Předběžná náplň práce v anglickém jazyce
Research question and motivation

In recent years, there have emerged two interesting phenomena - cryptocurrencies and Google Trends (Kristoufek, 2013). Cryptocurrencies has no fundamental value, what can lead to interesting dynamics at financial market with cryptocurrencies (Kristoufek, 2013). On the other side, there is a google search analysis tool Google Trends, which is based on Google Search. The Google Trends shows how often a particular query is searched relatively to the total search-volume across various regions of the world, and in various languages (Insights into what the world is searching for -- the new Google Trends, Yossi Matias, Insights Search, The official Google Search blog, September 28, 2012).
It would be interesting to find out if there are some relationships among cryptocurrencies as Bitcoin, Litecoin, Ethereum and Ethereum classic. The time series data of queries regarding each cryptocurrency can be collected from Google Trends. Then the time series data of prices and volumes of all these cryptocurrencies can be obtained.

Contribution

According to my best knowledge, there are some theses examining relationships between Bitcoin and Google Trends data but there is no thesis using Google Trends to examine the relationships between Litecoin and the other cryptocurrencies.
The results of this thesis will form plausible evidence for building an investment portfolio through trading with cryptocurrencies. This thesis could broaden the awareness about the behaving of cryptocurrencies at financial markets.

Methodology

The vector autoregression methodology will be applied in order to examine the relationships among cryptocurrencies with the aim to answer two specific questions. First question is the variation of volume of the Litecoin traded at some financial market in the volume searched by Google Trends and prices of each other cryptocurrencies traded at some financial market. The second one is the variation of price of the Litecoin in volume searched by Google Trends and price of each other cryptocurrencies traded at some financial market.
The time series for Google Trends queries will be obtained from http://www.google.com/trends and the time series for prices and volumes of the cryptocurrencies from http://www.bitcoincharts.com or from https://www.bfxdata.com/datadownload/.
After obtaining the data, the Augmented Dickey-Fuller test and the KPSS test for testing the stationarity will be used. If the unit root in both analyzed series would be found, the time series for the cointegration would have to be tested. If there would be the stationarity present in the time series, then the vector autoregression will be applied.

Outline

1. Introduction
2. Introduction to vector autoregression analysis
3. Data analysis and testing stationarity of the data
4. Applying the vector autoregression analysis for the data
5. Discussion of results and comparison with other conclusions from previous research
6. Conclusions and suggestions for further research
 
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