What are the advantages of using logarithmic scaling in cryptocurrency analysis?

3 answers

• Nov 27, 2021 · 3 years ago
  Logarithmic scaling is widely used in cryptocurrency analysis due to its ability to display price movements in a more meaningful way. Unlike linear scaling, which represents each unit on the y-axis with an equal distance, logarithmic scaling compresses the higher price range and expands the lower price range. This allows traders and analysts to better visualize and interpret price changes across different price levels. By using logarithmic scaling, it becomes easier to identify and analyze significant price movements, trends, and support/resistance levels in the cryptocurrency market.
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• Nov 27, 2021 · 3 years ago
  Using logarithmic scaling in cryptocurrency analysis has several advantages. Firstly, it helps to mitigate the impact of extreme price fluctuations that are common in the volatile cryptocurrency market. By compressing the higher price range, logarithmic scaling allows for a clearer representation of price movements, making it easier to identify trends and patterns. Additionally, logarithmic scaling can help to highlight long-term price trends and support/resistance levels, which can be useful for making informed investment decisions. Overall, logarithmic scaling provides a more accurate and comprehensive view of price movements in the cryptocurrency market.
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• Nov 27, 2021 · 3 years ago
  Logarithmic scaling is a popular choice for cryptocurrency analysis because it offers a more balanced perspective on price movements. Unlike linear scaling, which can make small price changes appear insignificant and overshadowed by larger price movements, logarithmic scaling ensures that both small and large price changes are given appropriate attention. This helps traders and analysts to identify potential breakout points, support/resistance levels, and overall market trends more effectively. Many cryptocurrency trading platforms, including BYDFi, provide logarithmic scaling as an option to enhance the analysis capabilities of their users.
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