Topic: Top 20 days for Bitcoin - page 132. (Read 105562 times)
This make sense to me. If you buy into this analysis, it basically says we need to fill in some more data points around $16 - $18 before moving higher with any stability. For the price to move higher with stability, it has to happen at a measured pace...basically to give the people that want or need to sell at these lower prices a chance to sell. If you quickly move to much higher prices (say $50), then you'll still have a lot of people that may have been willing to sell at lower prices that are still holding. As the price bounces around at $50, they may start to sell...and continue selling as the price experiences a substantial decline.
Interesting, what assumptions would you say are being made with this model? E.g., Why should price be modeled as the log of the rank?
This is the King effect. While the majority of data points fit onto the line, the top few are above it. This suggests that we are unlikely to have the top 10 days having a similar price, i.e. there will be a significant reduction after the top is reached. This has been particularly applicable to Bitcoin so far.They clearly don't though. The line overestimates price around 20 and underestimates around 14.
That's cause my line is slightly distorted by the three kings. Slightly tilting it towards the horizontal axis would illustrate it better.
Interesting, what assumptions would you say are being made with this model? E.g., Why should price be modeled as the log of the rank?
This is the King effect. While the majority of data points fit onto the line, the top few are above it. This suggests that we are unlikely to have the top 10 days having a similar price, i.e. there will be a significant reduction after the top is reached. This has been particularly applicable to Bitcoin so far.They clearly don't though. The line overestimates price around 20 and underestimates around 14.
Interesting, what assumptions would you say are being made with this model? E.g., Why should price be modeled as the log of the rank?
This is the King effect. While the majority of data points fit onto the line, the top few are above it. This suggests that we are unlikely to have the top 10 days having a similar price, i.e. there will be a significant reduction after the top is reached. This has been particularly applicable to Bitcoin so far.
Interesting, what assumptions would you say are being made with this model? E.g., Why should price be modeled as the log of the rank?
Going a bit more in-depth, we have the king effect clearly seen in Bitcoin prices:
The king effect means that when Bitcoin goes back up above $30, it will either continue to rise before a sizable collapse, or collapse immediately. For example, all of the following are plausible scenarios:
The king effect means that it is unlikely we will see both new highs and stability. One has to go.
The king effect means that when Bitcoin goes back up above $30, it will either continue to rise before a sizable collapse, or collapse immediately. For example, all of the following are plausible scenarios:
- Price remains below ~$25, with stability
- Price rises above ~$25, then quickly collapses below ~$25, with some stability
- Price rises above ~$25, then continues rising to around $40 before returning to the $25 to $30 level, with little stability
- Price rises above ~$25, then continues rising to far above $25 before collapsing but remaining above $25, with almost no stability
The king effect means that it is unlikely we will see both new highs and stability. One has to go.
1. 2011-06-09 W. Avg: 29.58
2. 2011-06-08 W. Avg: 27.25
3. 2011-06-10 W. Avg: 24.67
4. 2011-06-13 W. Avg: 20.11
5. 2011-06-07 W. Avg: 19.90
6. 2011-06-15 W. Avg: 19.68
7. 2011-06-14 W. Avg: 19.25
8. 2011-06-16 W. Avg: 18.86
9. 2011-06-06 W. Avg: 18.46
10. 2011-06-19 W. Avg: 17.77
11. 2011-06-11 W. Avg: 17.61
12. 2011-06-05 W. Avg: 17.32
13. 2013-01-22 W. Avg: 17.15
14. 2011-06-27 W. Avg: 17.01
15. 2011-06-28 W. Avg: 16.93
16. 2011-06-29 W. Avg: 16.88
17. 2011-06-30 W. Avg: 16.51
18. 2011-06-04 W. Avg: 16.41
19. 2013-01-21 W. Avg: 16.38
20. 2011-06-12 W. Avg: 16.21
(w. avgs rounded to 5 decimal places (mBTC) or 2 decimal places (BTC), Mt. Gox USD data before June 10, 2013; Bitstamp USD data after June 10, 2013)
Every one of the entries is in June 2011 except for the two previous days, which now rank 13th and 19th. I have a feeling that we'll break top ten soon.
2. 2011-06-08 W. Avg: 27.25
3. 2011-06-10 W. Avg: 24.67
4. 2011-06-13 W. Avg: 20.11
5. 2011-06-07 W. Avg: 19.90
6. 2011-06-15 W. Avg: 19.68
7. 2011-06-14 W. Avg: 19.25
8. 2011-06-16 W. Avg: 18.86
9. 2011-06-06 W. Avg: 18.46
10. 2011-06-19 W. Avg: 17.77
11. 2011-06-11 W. Avg: 17.61
12. 2011-06-05 W. Avg: 17.32
13. 2013-01-22 W. Avg: 17.15
14. 2011-06-27 W. Avg: 17.01
15. 2011-06-28 W. Avg: 16.93
16. 2011-06-29 W. Avg: 16.88
17. 2011-06-30 W. Avg: 16.51
18. 2011-06-04 W. Avg: 16.41
19. 2013-01-21 W. Avg: 16.38
20. 2011-06-12 W. Avg: 16.21
(w. avgs rounded to 5 decimal places (mBTC) or 2 decimal places (BTC), Mt. Gox USD data before June 10, 2013; Bitstamp USD data after June 10, 2013)
Every one of the entries is in June 2011 except for the two previous days, which now rank 13th and 19th. I have a feeling that we'll break top ten soon.
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