Title page for etd-0603118-164022


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URN etd-0603118-164022
Author Lun-Kang Liu
Author's Email Address No Public.
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Department Applied Mathematics
Year 2017
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title The Analysis and Forecasting of the Bitcoin Return
Date of Defense 2018-06-15
Page Count 47
Keyword
  • Text mining
  • Hidden Markov model
  • Cryptocurrency
  • Abstract The feasibility of cryptocurrency as an investment tool has been a topic of considerable concern in recent years. Bitcoin is a cryptocurrency that is universally used regardless of regional restrictions. When Bitcoin is considered as an investment tool, it operates in the same way as investing in legal currencies, such as: US Dollars, Euros, and British Pounds. However, due to the fluctuations of Bitcoin return are larger than the legal currencies, Bitcoin return forecasting is a big challenge compared to those for the legal currencies. In order to predict the return of Bitcoin, this thesis tries to build up a prediction model based on the historical data of the Bitcoin and other top five cryptocurrencies such as the Litecoin, Ethereum, Ripple, and Dash which have a longer development time. Moreover, we include the information obtained from text mining analyzing the Bitcoin online forum articles to find the keyword sentiment scores as explanatory variables into the prediction model as well. The hidden Markov model (HMM) has been used to predict the trend of the Bitcoin daily rate of return. The prediction of the ups and downs trend of Bitcoin on the next day with acceptable accuracy should be helpful for making decisions on the investment strategy of Bitcoin.
    Advisory Committee
  • Fu-Chuen Chang - chair
  • Mei-Hui Guo - co-chair
  • Huang, Shih-Feng - co-chair
  • Mong-Na Lo Huang - advisor
  • Files
  • etd-0603118-164022.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2018-07-03

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