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Analyzing Bitcoin in R - Part 6 - Charting Bitcoin data

Pub: 04.12.17

| By Anonymous

In Finance.

Tags: coding r bitcoin analysis .

Using the quantmod package we can do pretty charts based on our aggregated daily time series.

library(quantmod)

I start all the time series from October 2017 so that the chart features are more visible.

png('btc_plot_daily_chart1.png')
chartSeries(rawdailyohlc['2017-10-01/'], name = 'Bitcoin USD')
addMACD()
dev.off()

Daily Bitcoin Chart 1

png('btc_plot_daily_chart2.png')
barChart(rawdailyohlc['2017-10-01/'], theme = 'white.mono', bar.type = 'hlc', name = 'Bitcoin USD') 
dev.off()

Daily Bitcoin Chart 2

png('btc_plot_daily_chart3.png')
candleChart(rawdailyohlc['2017-10-01/'], multi.col = TRUE, theme = 'white', name = 'Bitcoin USD')
dev.off()

Daily Bitcoin Chart 3

png('btc_plot_daily_chart4.png')
lineChart(rawdailyohlc['2017-10-01/'], line.type='h', TA = NULL, name = 'Bitcoin USD') 
dev.off()

Daily Bitcoin Chart 4

png('btc_plot_daily_chart5.png')
lineChart(rawdailyohlc['2017-10-01/'], line.type='h', TA = 'addVo();addBBands();addCCI()', name = 'Bitcoin USD')
dev.off()

Daily Bitcoin Chart 5

png('btc_plot_daily_chart6.png')
chartSeries(rawdailyohlc['2017-10-01/'], theme = 'white', TA = 'addVo();addBBands();addCCI()', name = 'Bitcoin USD')
dev.off()

Daily Bitcoin Chart 6

Moving on to calculating some summary statistics: Preliminary return analysis with plots

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