What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis
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{"title"=>"What are the main drivers of the bitcoin price? Evidence from wavelet coherence analysis", "type"=>"journal", "authors"=>[{"first_name"=>"Ladislav", "last_name"=>"Kristoufek", "scopus_author_id"=>"36131650100"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"604107550", "doi"=>"10.1371/journal.pone.0123923", "pmid"=>"25874694", "arxiv"=>"1406.0268", "sgr"=>"84928818221", "scopus"=>"2-s2.0-84928818221", "isbn"=>"1932-6203"}, "id"=>"c1f0b9ef-1c82-3520-9bf1-3bc0d0afd3c3", "abstract"=>"Bitcoin has emerged as a fascinating phenomenon of the financial markets. Without any central authority issuing the currency, it has been associated with controversy ever since its popularity and public interest reached high levels. Here, we contribute to the discussion by examining potential drivers of Bitcoin prices ranging from fundamental to speculative and technical sources as well as a potential influence of the Chinese market. The evolution of the relationships is examined in both time and frequency domains utilizing the continuous wavelets framework so that we comment on development of the interconnections in time but we can also distinguish between short-term and long-term connections.", "link"=>"http://www.mendeley.com/research/main-drivers-bitcoin-price-evidence-wavelet-coherence-analysis", "reader_count"=>251, "reader_count_by_academic_status"=>{"Unspecified"=>10, "Professor > Associate Professor"=>18, "Researcher"=>13, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>7, "Student > Master"=>71, "Other"=>9, "Student > Bachelor"=>62, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>10, "Professor > Associate Professor"=>18, "Researcher"=>13, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>7, "Student > Master"=>71, "Other"=>9, "Student > Bachelor"=>62, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>15, "Agricultural and Biological Sciences"=>1, "Arts and Humanities"=>1, "Business, Management and Accounting"=>42, "Computer Science"=>64, "Decision Sciences"=>3, "Earth and Planetary Sciences"=>1, "Economics, Econometrics and Finance"=>80, "Engineering"=>9, "Materials Science"=>1, "Mathematics"=>9, "Medicine and Dentistry"=>3, "Neuroscience"=>1, "Physics and Astronomy"=>8, "Psychology"=>1, "Social Sciences"=>12}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Social Sciences"=>{"Social Sciences"=>12}, "Decision Sciences"=>{"Decision Sciences"=>3}, "Physics and Astronomy"=>{"Physics and Astronomy"=>8}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>9}, "Unspecified"=>{"Unspecified"=>15}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>9}, "Neuroscience"=>{"Neuroscience"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>80}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>64}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>42}}, "reader_count_by_country"=>{"Hong Kong"=>1, "United States"=>1, "Japan"=>1, "United Kingdom"=>1, "Switzerland"=>1, "Spain"=>1, "Czech Republic"=>1, "Luxembourg"=>1, "Finland"=>1, "Poland"=>2, "Brazil"=>1, "France"=>1, "Germany"=>2}, "group_count"=>13}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2021824"], "description"=>"<p>The description and interpretation of relationships hold from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123923#pone.0123923.g002\" target=\"_blank\">Fig 2</a>. Bitcoin prices in USD and CNY <i>(top left)</i> move together at almost all scales and during the entire examined period. There is no evident leader in the relationship, though the USD market appears to slightly lead the CNY at lower scales. However, at the lowest scales (the highest frequencies), the correlations vanish. For the volumes <i>(top right)</i>, the two markets are strongly positively correlated at high scales. However, for the lower scales, the correlations are significant only from the beginning of 2013 onwards. There is again no dominant leader in the relationship. The CNY exchange volume then leads the USD prices in the long run <i>(bottom left)</i>. However, when we control for the effect of the USD exchange volume <i>(top right)</i>, we observe that the correlations vanish.</p>", "links"=>[], "tags"=>["Main Drivers", "Wavelet Coherence Analysis", "asset", "frequency domains", "Bitcoin forms", "Financial markets", "Bitcoin Price", "Bitcoin prices", "Chinese market", "wavelets framework"], "article_id"=>1380595, "categories"=>["Uncategorised"], "users"=>["Ladislav Kristoufek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0123923.g005", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Influence_of_the_Chinese_market_/1380595", "title"=>"Influence of the Chinese market.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-15 02:59:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/2021805"], "description"=>"<p>Values of the index are shown in the USD (for the USD markets) and in the logarithmic scale.</p>", "links"=>[], "tags"=>["Main Drivers", "Wavelet Coherence Analysis", "asset", "frequency domains", "Bitcoin forms", "Financial markets", "Bitcoin Price", "Bitcoin prices", "Chinese market", "wavelets framework"], "article_id"=>1380581, "categories"=>["Uncategorised"], "users"=>["Ladislav Kristoufek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0123923.g001", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Bitcoin_price_index_/1380581", "title"=>"Bitcoin price index.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-15 02:59:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/2021820"], "description"=>"<p>The descriptions and interpretation of relationships hold from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123923#pone.0123923.g002\" target=\"_blank\">Fig 2</a>. Searches on both engines <i>(top)</i> are positively correlated with the Bitcoin price in the long run. For both, we observe that the relationship somewhat changes over time. In the first third of the analyzed period, the relationship is led by the prices, whereas in the last third of the period, the search queries lead the prices. Unfortunately, the most interesting dynamics remain hidden in the cone of influence, and this result is thus not very reliable. Apart from the long run, there are several significant episodes at the lower scales with varying phase directions, hinting that the relationship between search queries and prices depends on the price behavior. Moving to the safe haven region, we find no strong and lasting relationship between the Bitcoin price and either the financial stress index <i>(bottom left)</i> or gold price <i>(bottom right)</i>. The significant regions at medium scales for gold are generally connected to the dynamics of the Swiss franc exchange rate.</p>", "links"=>[], "tags"=>["Main Drivers", "Wavelet Coherence Analysis", "asset", "frequency domains", "Bitcoin forms", "Financial markets", "Bitcoin Price", "Bitcoin prices", "Chinese market", "wavelets framework"], "article_id"=>1380591, "categories"=>["Uncategorised"], "users"=>["Ladislav Kristoufek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0123923.g004", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Search_engines_and_safe_haven_value_/1380591", "title"=>"Search engines and safe haven value.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-15 02:59:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/2021815"], "description"=>"<p>Wavelet coherence is represented by a colored contour:the hotter the color is, the higher the local correlation in the time-frequency space (with time on the <i>x</i>-axis and scale on the <i>y</i>-axis). The matching of colors and correlation levels is represented by the scale on the right hand side of the upper graph. Regions with significant correlations tested against the red noise are contrasted by a thick black curve. The cone of influence separating the regions with reliable and less reliable estimates is represented by bright and pale colors, respectively. Phase (lag-lead) relationships are shown by the arrows—a positive correlation is represented by an arrow pointing to the right, a negative correlation by one to the left, leadership of the first variable is shown by a downwards pointing arrow and if it lags, the relationship is represented by an upward pointing arrow. The latter two relationships hold for the in-phase relationship (positive correlation); for the anti-phase (negative correlation), it holds vice versa. Henceforth, specifically for the fundamental drivers, Bitcoin price is negatively correlated to the Trade-Exchange ratio <i>(top)</i> over the long-term for the entire analyzed period, and there is no evident leader in the relationship. The Bitcoin price level is negatively correlated with the Bitcoin price in the long-term for the entire analyzed period as well <i>(bottom left)</i>, with no evident leader. For the relatively calm period between 05/2013 and 09/2013, the price level led the prices in the medium term. The supply of bitcoins is positively correlated with the price in the long-term <i>(bottom right)</i>, with no evident leader.</p>", "links"=>[], "tags"=>["Main Drivers", "Wavelet Coherence Analysis", "asset", "frequency domains", "Bitcoin forms", "Financial markets", "Bitcoin Price", "Bitcoin prices", "Chinese market", "wavelets framework"], "article_id"=>1380586, "categories"=>["Uncategorised"], "users"=>["Ladislav Kristoufek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0123923.g002", "stats"=>{"downloads"=>2, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Fundamental_drivers_/1380586", "title"=>"Fundamental drivers.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-15 02:59:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/2021818"], "description"=>"<p>The descriptions and interpretation of relationships hold from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123923#pone.0123923.g002\" target=\"_blank\">Fig 2</a>. Both the hash rate <i>(top left)</i> and difficulty <i>(top right)</i> are positively correlated with the Bitcoin price in the long-term. The price leads both relationships as the phase arrow points to southeast in most cases, and the interconnection remains quite stable in time. The trade volume <i>(bottom left)</i> is again connected to the Bitcoin price primarily in the long-term. However, the relationship is not very stable over time. Until 10/2012, we observe a negative correlation between the two, and the price is the leader. The relationship then becomes less significant and the leader position is no longer evident. For the trade transactions <i>(bottom right)</i>, the relationship is positive in the long-term, and the transactions lead the Bitcoin price. However, the relationship becomes weaker over time, and it is not statistically significant from 01/2013.</p>", "links"=>[], "tags"=>["Main Drivers", "Wavelet Coherence Analysis", "asset", "frequency domains", "Bitcoin forms", "Financial markets", "Bitcoin Price", "Bitcoin prices", "Chinese market", "wavelets framework"], "article_id"=>1380589, "categories"=>["Uncategorised"], "users"=>["Ladislav Kristoufek"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0123923.g003", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Currency_mining_and_trade_usage_/1380589", "title"=>"Currency mining and trade usage.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-15 02:59:03"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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