7% of the time explains 90% of bitcoin (BTC) performance.

7% of the time explains 90% of bitcoin (BTC) performance.

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Thomas A.

Our study will focus on the role of rare changes in the performance of bitcoin (BTC). This exclusive study shows amazing results. In fact, it seems in particular that 7% of the time explains up to 90% of bitcoin’s (BTC) performance. So, this is clearly not in line with what would be expected. This is also consistent with the conclusions of our previous article. Our study here will aim to detect the differences “rare” which explains the performance of bitcoin (BTC).

Distribution of daily changes in bitcoin (BTC)

We first selected the daily data set for bitcoin between May 2018 and May 2023. That is to say over a period of 5 years which we consider to be quite representative, with more than 1800 days. We then combined all these variations according to their range to obtain the following distribution.

Distribution of daily changes in bitcoin (BTC). Graphics and data processing by Thomas ANDRIEU.

Therefore, we can specify that the average daily change of bitcoin (BTC) is exactly +0.128%. Moreover, one sees rather intuitively that there are differences “big”those located at the ends of the bell curve, yes “unusual” enough. The two limits in red shown on the graph represent the limits that include a daily change of +7% (right) or -7% (left). This will help us in our reasoning.

In addition, we note that the proportion of bearish days is greater than the proportion of bullish days. Similarly, the share of bearish days is greater than the share of bearish weeks, months, or years on the price of bitcoin (BTC). In fact, according to another study we conducted in August 2021, “between 2016 and 2021, out of more than 2,000 daily changes, the risk of loss is 63.9% of the time”.

How to measure the importance of major changes?

Our study first requires a brief explanation of the method used. From the more than 1800 data we have, we establish the next steps.

  • Firstly we rewrite the data set by including the most extreme data (over the threshold we have set for ourselves). For example, we will replace all variations above and below 8% with zero performance. The number of days over this threshold is counted in parallel.
  • Then we the average of all the daily changes we have rewritten.
  • Finally, we get a new average daily performance that can be compared to the global average daily performance mentioned above (+0.128% per day). We also compare in parallel with the number of days “big” compared to the total number of days (1800).

In other words, we measure the daily performance deficit due to the lack of significant changes that we have eliminated. As a result, this enables us to deduct the resulting performance (respectively the share of performance absent from the total initial performance) according to the changes. “big”.

7% of the time explains up to 90% of the performance!

The heart of our work is summarized in the graphic below. We separately studied the average daily performance of bitcoin in the event that we put variations above + / – 3%, then 4%, then 5%, and this, up to 11%… For example, if we exclude variations above 3% or below -3%, then we deduce that changes above this threshold account for 73% of all bitcoin (BTC) average daily performance.. Likewise, the number of days where the daily variations exceeded + / – 3% was calculated. As a result, daily variation appears to be greater than 3% or less than -3% in 27.6% of days.

Proportion of the overall daily performance caused by the “extreme” changes according to the “extreme” variation threshold considered. Graphics and data processing by Thomas ANDRIEU.

The graph above shows in dotted lines the proportion of time including changes above (and below) the percentage determined on the abscissa. Therefore, more than 27% of the time we notice variations of + / – 3% on bitcoin (BTC). In addition, the continuous curve in black shows the share of bitcoin performance that would be caused by changes beyond the threshold on the abscissa. The larger the gap between the two curves, the more a small portion of the time concentrates most of the performance.

Major considerations

For example, variances above 10% or below -10% account for 2.3% of the time. However, they explain more than 30% of the average daily performance of bitcoin (BTC). But the most significant disparity is for extreme variations of + / – 7%. Changes below -7% or above +7% account for 6.5% of the time. However, they account for almost 90% of bitcoin’s (BTC) average daily performance.

This can be seen visually on the distribution graph shown above. Over the red marker on the right, “extreme” positive variations are overrepresented between +7.5% and +8.5%. In other words A trader who misses most of these daily variations would see his average performance drop significantly. Finally, we note that large swings of +/- 11% have less impact on explaining bitcoin’s performance.

Deduction on bitcoin (BTC) transport

An antinomy seems to appear. Large variations at 7% have a greater impact on bitcoin performance than large variations at 10%. This means that extreme variations of +/- 10% are less likely to outperform the market and more often lead to at least a partial recovery in the opposite direction.

For extreme divergences at 7%, this means that divergences of this order rarely lead to an upward movement. The market is more impulsive and less hesitant and understands these variations most of its variations, and consequently, its performance.

The importance of large differences

We have already discussed, in previous posts, the importance of large differences. In fact, it seems that most trend reversals appear around these variations “big”. We said above that large variations of + / – 10% represent 2.3% of the time since 2018. That is to say, in a year of 365 days, those variations will be concentrated between 8 and 9 days. Which means that there is such a change “big” it takes effect on average every 6 to 7 weeks. Finally, it is relevant to recall that Bitcoin is a volatile asset and its behavior depends a lot on the rotation of its changes. We already wrote about this (fractals): A study of fractals on bitcoin (BTC) – Cointribune.

Big changes in bitcoin (BTC): over 11% (green) and under 10% (red). Compare the price of bitcoin (BTC). Graphics and data processing by Thomas ANDRIEU.

The graph above shows with vertical lines of the times of appearance of these great changes. Such movements are usually what trigger bullish or bearish reversals. The recurrence of major changes is a strong indication change in investor psychology and often provides information on the state of the trend. Finally, these variations are often around the peaks. In fact, bitcoin volatility tends to be greater in uptrends.

Bad news for short-term trading?

We have seen that a minority of the variances, namely the strongest variances, explain almost the performance of bitcoin (BTC). This is not without consequence on how to approach their strategy for investors and traders. Indeed, how to generate bullish expressions if most of these expressions are concentrated for a few days?

An investor positioned for the period studied would benefit from this phenomenon. He wouldn’t miss any major market movements, so he wouldn’t miss most of the market’s performance. The risk for the trader who does a lot of back and forth is to stay away during these days that the market performs.

But the conclusions we have reached can be interpreted in another way. A trader who could position himself on these exceptional days would be able, at least in theory, to outperform the market. However, it is difficult to support this hypothesis as it would require great abilities to expect it. Most traders react to volatility but not necessarily in a good way and not early enough. It’s no surprise that most cryptocurrency traders lose in the long run.


Our study looked at a large data set from 2018 to 2023. The studied sample clearly shows that a minority of the daily variations of bitcoin (BTC) has a major impact on the overall performance of the latter. The most scientific figure comes with the extreme variations at 7%, that is to say the variations below -7% and above +7%. Although these differences account for only 7% of the time, they explain up to 90% of the observed performance in the price of bitcoin (BTC). We have a lot to do, according to the statistics, at a “Pareto’s law” worse!

Extreme variations in bitcoin performance are clearly overrepresented. Additionally, it is important to remember that bitcoin (BTC) is a volatile asset by its very nature. So we already knew that extreme and frequent variations played a key role. But this study confirms to us that these days “exceptional” it is clear that you will have an even greater impact than one could imagine. The impact of great diversity is greater in that it can push clear trends forward, without reversing them.

In this context, an investor (or trader) would lose most of these differences “big” the market would underperform. This observation is also common in most markets and reminds us once again of the ineffectiveness of certain traditional models, and certain behaviours, be “step” with the market.

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Thomas A. avatar

Thomas A.

Author of several books, economic and financial editor of various sites, over many years I developed a real passion for the analysis and study of markets and the economy.

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