Linear vs. Log Scale charts
Please read this article beforehand:
http://www.investopedia.com/ask/answers/05/logvslinear.asp
In this volatile world of crypto with BIG percentage increases. A linear scale chart will probably not show a lot of patterns compared to the log scale, especially in long-term charts. Take a look at bitcoin:
These 2 charts represent the exact SAME data; the only thing that changes is the y-axis scale. In my opinion, the log-scale chart looks a lot cleaner in the long-run and yields more accurate predictions on trend lines, especially in volatile times. You may see a headline: “Bitcoin drops $200!” and it may seem like a lot, but based on today’s price, that is only a 5% drop. The log-chart helps mitigate this big linear change and focuses on the percent change.
The reason why I knew that BTC would probably not drop below $2,800 during the recent dip was due to the trend line I drew on the log-chart. As you can see, the green line showed a good support level for a possible bounce since it already did so twice before. That same trend line in the linear scale would be at around $2,400, another 15% drop! The channel is much cleaner in the log-scale and can put big linear moves in a less extravagant, yet true manner.
However, linear data is also good to draw lines and see trends. From my experience, most traders use linear charts when posting on twitter and doing their analysis, but this is mostly on short-term charts. That is because the difference between log and linear charts in short time frames is not that extravagant as in the long-term. So, it is important to look at both. In addition, there are a few patterns and trends that can be seen in the linear scale chart that may not be as clear in the log-chart.
At the end of the day, I draw most of my analysis in the log-scale chart because I care more about the percent change of a specific token or currency over the absolute change of it. But I still first look at the linear chart to simply see if I may have missed any pattern and to predict what most of the market is looking at.
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This article was originally posted on Steemit in October
