February 5th, 2015
0. Introduction
I was inspired by a visualisation today, retweeted today by Martti Malmi from a months old tweet from Tuur Demeester. It shows the visualisation from this reddit post. I thought it was an interesting way to present the data, and I thought of a few visualisations that riff off this example and might help readers visualise the historical returns from investing bitcoin during certain time periods.
Data is the daily volume weighted average USD price from various of the larger exchanges (with a sanity check to avoid market outliers such as the collapse of MTGox).
1. Historical returns, 2010 to present.
This is simply a repeat of the visualisation presented in the reddit post. I do like this plot - it's easy for me to follow and understand. Simply pick an investment date and follow along the divestment dates (x axis) to see how well your investment performed.
The colour scale is the return as a percentage of the original investment:
2. Some specific examples
As a further example, lets take some specific investment dates and plot the returns over the history of the price index. I've taken the first day of trading at MTGox as the first investment date, and subsequent investment dates are on the first day of each year.
3. Distribution of returns by date of divestment
From the plot above it seems obvious that until last year every investment performed well. However this is not correct - if I had chosen other dates, the results would have been quite different. Unfortunately, that type of time series plot fails when you try to present too much data (such as hundreds of investment dates as a comparison); instead it's better to present it as a 2D histogram.
The relationship between this plot and the last is shown by the tan line, which is the same tan line from the previous plot, that is an investment starting on January 1st, 2011. Increasing darkness of she shade of each hex bin indicates an increasing number of investments at this point. Therefore a darker shade suggests a stable price around the date of investment, and a lighter shade more volatility in the USD price around the time of investment.
4. Distribution of returns as a function of time held
Another way the historical returns data can be interpreted is as a function of time held. Since the majority of daily prices are more than previous daily prices we would expect this to be generally positive, which is what we see. However, the details are quite interesting. Holding for around 200 days results in the distribution of returns that includes the poorest performances has a distribution of returns from 10% to 10,000%. As the length held increases, the distribution narrows and the mean increases.
This doesn't mean that we can be certain that holding bitcoin today is a good investment, only that historically even short term bitcoin investments have tended to be better more often than worse.
Data is the daily volume weighted average USD price from various of the larger exchanges (with a sanity check to avoid market outliers such as the collapse of MTGox).
1. Historical returns, 2010 to present.
This is simply a repeat of the visualisation presented in the reddit post. I do like this plot - it's easy for me to follow and understand. Simply pick an investment date and follow along the divestment dates (x axis) to see how well your investment performed.
The colour scale is the return as a percentage of the original investment:
% return = divestment value / investment value * 100
- 100% return means that your investment was unchanged,
- 10% return means that it was reduced to ten percent of its initial USD value,
- 1000% return means the USD value your investment increased ten-fold.
2. Some specific examples
As a further example, lets take some specific investment dates and plot the returns over the history of the price index. I've taken the first day of trading at MTGox as the first investment date, and subsequent investment dates are on the first day of each year.
3. Distribution of returns by date of divestment
From the plot above it seems obvious that until last year every investment performed well. However this is not correct - if I had chosen other dates, the results would have been quite different. Unfortunately, that type of time series plot fails when you try to present too much data (such as hundreds of investment dates as a comparison); instead it's better to present it as a 2D histogram.
The relationship between this plot and the last is shown by the tan line, which is the same tan line from the previous plot, that is an investment starting on January 1st, 2011. Increasing darkness of she shade of each hex bin indicates an increasing number of investments at this point. Therefore a darker shade suggests a stable price around the date of investment, and a lighter shade more volatility in the USD price around the time of investment.
4. Distribution of returns as a function of time held
Another way the historical returns data can be interpreted is as a function of time held. Since the majority of daily prices are more than previous daily prices we would expect this to be generally positive, which is what we see. However, the details are quite interesting. Holding for around 200 days results in the distribution of returns that includes the poorest performances has a distribution of returns from 10% to 10,000%. As the length held increases, the distribution narrows and the mean increases.
This doesn't mean that we can be certain that holding bitcoin today is a good investment, only that historically even short term bitcoin investments have tended to be better more often than worse.
5. Summary
Organofcorti lives!
- Holding for around 100 days results in the distribution of returns that includes the poorest performances has a distribution of returns from 20% to 1,000%.
- Holding for around 200 days has a distribution of returns from 10% to 10,000%.
- Holding for around 300 days has a distribution of returns from 20% to 50,000%.
- Holding for around 500 days has a distribution of returns from 50% to 10,000%.
Organofcorti lives!
organofcorti.blogspot.com is a reader supported blog:
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Created using R and various packages, especially data.table and ggplot2.
Thank you to bitcoincharts.com for use of their data.
Find a typo or spelling error? Email me with the details at organofcorti@organofcorti.org and if you're the first to email me I'll pay you 0.01 btc per ten errors.
Please refer to the most recent blog post for current rates or rule changes.
I'm terrible at proofreading, so some of these posts may be worth quite a bit to the keen reader.
Exceptions:
- Errors in text repeated across multiple posts: I will only pay for the most recent errors rather every single occurrence.
- Errors in chart texts: Since I can't fix the chart texts (since I don't keep the data that generated them) I can't pay for them. Still, they would be nice to know about!
I write in British English.
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