3.12 Scaling Graphs

1. Linear scaling: applications and limitations

Objective: To understand the applications and limitations of linear scaling in technical analysis of price charts.

 

What is linear scaling?

Linear scaling is a method of visualizing data on a graph where the distances between successive values on the Y axis (price axis) are equal. This means that each unit of price change is represented by the same distance on the chart regardless of what price level it is at.

How does linear scaling work?

1. Equal distances: In a line graph, a price difference of 10 units will look identical whether the change is from 10 to 20, from 50 to 60 or from 1000 to 1010. All these changes are represented by the same distance on the Y axis.

2. Fixed step: Each successive value on the Y axis is a fixed unit away from the previous one. For example, if the graph shows price changes in dollars, the difference between $10 and $20, $20 and $30, and so on, will be the same size on the Y axis.

 

Example of linear scaling

Suppose we have a price chart of any cryptocurrency whose value changes over time:

• Price 1: $10

• Price 2: $20

• Price 3: $30

• Price 4: $40

On a line graph, the difference between the price of $10 and $20 will be represented by the same distance as the difference between the price of $30 and $40. Each $10 jump upward will look identical in terms of distance on the chart.

 

Applications of linear scaling

Linear scaling is a versatile tool in technical analysis, particularly useful for short-term analysis of price movements and for simple identification of basic trends and price formations. Its applications are discussed in detail below.

Short-term analysis

Linear scaling is often used to analyze short-term price movements. It is a method that works well when traders focus on small, rapid price changes.

Advantages:

1. Accurate tracking of small price changes: Linear scaling allows you to accurately monitor small price changes, which is crucial for short-term investment strategies.

2. Intuitiveness: With its simple and direct presentation of data, linear scaling is easy to understand, making it ideal for novice traders.

3. Quick opportunity identification: In short-term analysis, where decisions must be made quickly, the ease of interpreting line charts enables traders to react more quickly to market changes.

Example: Analyzing a 1-minute or 5-minute chart for scalping and daytrading strategies. A trader who uses a scalping strategy can track very short-term price movements to buy and sell assets quickly, taking advantage of small price fluctuations.

 

Simple trend interpretation

Linear scaling makes it easy to identify underlying trends and price formations. With equal distances between values on the Y-axis, price movements are presented simply and clearly.

Advantages:

1. Ease of pattern recognition: Allows quick and easy recognition of price patterns such as support and resistance lines, head-and-shoulders formations, flag formations, etc.

2. Intuitive visualization: Since each unit of price change is represented by the same distance on the Y-axis, line graphs are easy to read and interpret.

3. Helpful for beginners: The simplicity of linear scaling makes it an ideal tool for novice traders who are just learning technical analysis.

Examples:

 

1. Support and resistance lines: 

   • Description: Support and resistance lines are price levels at which the price of an asset tends to stop and reverse its direction.

   • Advantages: Linear scaling makes it easy to identify these levels on the chart, which is crucial for deciding whether to enter or exit a trade.

   • Example: The price of BTC has bounced off the $30,000 level several times, suggesting that it is a support level.

2. Head and Shoulders formation (Head and Shoulders):

   • Description: A formation consisting of three peaks, where the middle one (head) is higher than the two lateral ones (shoulders). It is a classic trend reversal formation.

   • Advantages: Linear scaling makes it easier to identify this formation due to equal distance on the Y axis.

   • Example: BTC forms a head-and-shoulders formation at the $40,000 level, suggesting a possible reversal of the uptrend.

3. Flag formation (Flag):

   • Description: A short-term trend continuation pattern where the price consolidates in a narrow range after a strong upward or downward movement.

   • Advantages: Linear scaling makes it easy to recognize a flag formation, which helps traders decide whether to continue a position.

   • Example: BTC rises from $30,000 to $40,000 and then consolidates between $38,000 and $40,000, forming a flag formation. A breakout above $40,000 may suggest a continuation of the uptrend.

Summary

Linear scaling is an invaluable tool in technical analysis, especially in the short-term analysis of price movements and in the simple identification of basic trends and price formations. Thanks to its intuitiveness and simplicity, it is an ideal method for both beginners and experienced traders. Understanding the advantages and limitations of linear scaling allows you to use this tool more effectively in your daily market analysis.

 

Limitations of linear scaling

Although linear scaling has many advantages, there are some important limitations that can affect its effectiveness in some analytical situations. Below, we will discuss two major limitations of linear scaling: ratio deformation at large price ranges and unsuitability for long-term analysis.

Deformation of proportions at large price ranges

Linear scaling represents absolute price changes in such a way that each unit of price change is represented by the same distance on the Y axis. This means that a $10 price change will always have the same distance on the graph, regardless of the price level. This approach can lead to distorted proportions for large price changes, as the percentage differences are not adequately represented.

Example: Consider two price changes:

1. A price change from $10 to $20:

   • This is a change of $10, which is an increase of 100%.

   • On a line graph, this change will be represented as a certain distance, such as 1 cm.

2. Price change from $100 to $110:

   • This is also a change of $10, but represents an increase of only 10%.

   • On a line graph, this change will also be represented as the same distance of 1 cm.

These two price changes are presented in the same way on a line chart, even though the first change (100%) is much larger in percentage terms than the second change (10%). This distortion can lead to misinterpretation of the actual magnitude of price movements, especially when analyzing cryptocurrencies with high volatility.

Consequences:

• Misjudgment of the strength of a price movement: Investors may misjudge the significance of price movements, leading to inappropriate investment decisions.

• Lack of proportionality: Large percentage changes may appear less significant on line charts, making it difficult to identify key market moments.

Unsuitable for long-term analysis

Linear scaling may not reflect long-term price trends well, especially for assets that experience large changes in value. In long-term analysis, it is important to consider percentage changes in prices, not just absolute values. Linear scaling often distorts these changes, which can lead to misleading conclusions about long-term market trends.

Example: Consider a long-term chart of an asset whose price has increased from $10 to $1,000 over several years:

• Initial rise: At the beginning of the chart, the price rose from $10 to $20, a 100% increase.

• Subsequent growth: At the end of the chart, the price rose from $900 to $1,000, representing only an 11% increase.

On a line chart, both of these changes will be shown as certain distances, which can distort the true picture of a company's long-term growth. Initial large percentage increases may be downplayed, and later small percentage increases may be exaggerated.

 

Consequences:

• Difficulties in identifying long-term trends: Line charts can make it difficult to identify actual long-term trends, especially for assets that have experienced significant changes in value.

• Inaccurate forecasts: Analysis based on line charts can lead to inaccurate forecasts and investment strategies, which is particularly risky over the long term.
   

Summary

Linear scaling has its uses, especially in short-term analysis and simple identification of basic trends and price formations. However, its limitations, such as ratio deformation at large price ranges and inappropriateness for long-term analysis, can lead to misleading conclusions and investment decisions. Therefore, it is important for investors to be aware of these limitations and consider alternative scaling methods, such as logarithmic scaling, depending on the analysis context and investment objectives.

 

2. Logarithmic scaling: when is it more appropriate?

Objective: To acquire knowledge of when logarithmic scaling is more appropriate and what advantages it has in technical analysis.

In technical analysis, a particularly valued feature of logarithmic scaling is its ability to represent percentage price changes proportionally. Unlike linear scaling, which represents price changes in constant units, logarithmic charts allow for a more realistic representation of price movements, especially in the context of highly volatile assets. In this section, we will discuss when logarithmic scaling is more appropriate for analyzing financial markets, with a particular focus on cryptocurrencies. We will analyze the advantages of this approach in the context of long-term trend analysis, evaluation of key support and resistance levels, and interpretation of large price swings. As a result, you will be able to better understand how and when to use logarithmic scaling in your investment strategies for more precise and reliable results.

Definition of logarithmic scaling

Logarithmic scaling means that the Y-axis is scaled logarithmically, meaning that equal distances on the axis correspond to equal percent changes in price.

Logarithmic scaling:

• Description: Logarithmic scaling represents price changes in proportion to percentage changes in value. Each equal distance on the Y axis corresponds to an equal percentage change in price.

• Advantages:

  • Proportionality: Better representation of percentage price changes, making it easier to identify real trends.

  • Long-term analysis: Ideal for analyzing long-term price movements and assets with high volatility.

• Example: On a logarithmic chart, a price change from $10 to $20 (100%) will have a greater distance than a change from $100 to $110 (10%), more realistically reflecting actual changes in value.
   

Applications of logarithmic scaling

Logarithmic scaling is an invaluable tool in technical analysis, particularly useful in long-term trend analysis and in the analysis of highly volatile assets. Its applications are discussed in detail below.

Long-term trend analysis

Logarithmic scaling is ideal for analyzing long-term price movements because it better represents percentage changes in asset values than linear scaling. This allows investors to get a more realistic picture of long-term market trends.

Advantages:

1. Better representation of percentage price changes: In logarithmic charts, each equal distance on the Y axis corresponds to an equal percentage price change. This means that a price change from $10 to $20 (100%) will have the same distance on the chart as a change from $100 to $200 (100%).

2. Realistic representation of long-term trends: Logarithmic scaling provides a better understanding of real changes in asset values, especially over the long term, which is crucial for strategic analysis and investment decision-making.

Example: Analysis of the monthly chart of bitcoin since its inception.

Bitcoin has gone through many phases of rapid price increases and decreases. On a line chart, early price changes can be difficult to see compared to later, more dramatic movements. In contrast, on a logarithmic chart, early ups and downs are more visible because they represent percentage changes in value in a more proportional way.
 

Analysis of assets with high volatility

Assets with high volatility, such as cryptocurrencies, are better represented on logarithmic charts. Large price fluctuations are common in these assets, and logarithmic scaling allows for a more balanced and proportional representation of these changes.

Advantages:

1. A more balanced view of large price fluctuations: Logarithmic scaling provides a more realistic representation of large price fluctuations, helping investors understand real price movements and their significance.

2. Better understanding of actual price movements: With better representation of percentage price movements, investors can more easily identify key support and resistance levels, which is especially important in analyzing highly volatile assets.

Example: Analysis of Ether's long-term price movements.

Ethereum, like many other cryptocurrencies, exhibits high price volatility. On a logarithmic chart, price changes during periods of sharp ups and downs are presented in a more proportional manner, allowing for a better understanding of long-term trends and identification of key market moments.

 

Practical application of logarithmic scaling

1. Identification of long-term trends

   • Description: Logarithmic scaling allows for a more proportional and realistic representation of long-term trends.

   • Example: On a logarithmic chart of bitcoin, one can see a long-term upward trend that is more pronounced than on a line chart. This allows traders to better understand historical price movements and make more informed investment decisions.

2. Analysis of key support and resistance levels

   • Description: Using logarithmic scaling allows more accurate identification of key support and resistance levels.

   • Example: On a logarithmic chart of Ethereum, key support and resistance levels are more clearly identified, allowing traders to better plan trading strategies and set stop-loss orders.

3. Profit and loss evaluation

   • Description: Analyzing logarithmic charts allows for a more proportional understanding of potential gains and losses.

   • Example: An investor evaluating potential returns on Ether investments over the years can better understand how much percentage changes have affected the value of the asset, which is crucial for long-term investment planning.

Summary

Logarithmic scaling is a key tool in technical analysis, especially in long-term trend analysis and in the analysis of highly volatile assets. Better representation of percentage price changes allows investors to have a more realistic representation of long-term trends and price movements. As a result, investors can make more informed investment decisions, better manage risk and effectively plan their trading strategies.

 

Application of logarithmic scaling in long-term analysis

Objective: Acquire knowledge of how to apply various scaling methods to analyze long-term price trends and identify key support and resistance levels.

Technical analysis of cryptocurrency markets requires the use of various data visualization methods to accurately assess price trends and make informed investment decisions. Line charts and logarithmic charts are two basic scaling methods that can significantly affect the interpretation of long-term price trends. In this section, we will look at the differences between line and logarithmic charts, their applications and limitations. Understanding when and why to use each of these methods is key to effectively analyzing cryptocurrency price volatility and identifying key support and resistance levels. We will compare both types of charts to help traders better understand which approach may be more appropriate in different market analysis contexts.

Linear vs. logarithmic charts in long-term technical analysis in cryptocurrency markets

1. Linear charts

   • Uses: More often used for short-term analysis where absolute price changes are more important.

   • Limitations: May not realistically reflect long-term trends for assets with large changes in value.

2. Logarithmic charts

   • Application: Preferred for long-term analysis due to better representation of percentage price changes.

   • Advantages: Enable a more balanced view of large price swings and a better understanding of actual price movements.
      

Practical application of logarithmic scaling in long-term analysis

The use of appropriate scaling methods in technical analysis is crucial for understanding long-term trends and making informed investment decisions. In particular, logarithmic scaling offers a more proportional representation of percentage price changes, which is extremely useful in the context of highly volatile assets such as cryptocurrencies. In this section, we will discuss how to practically apply scaling in long-term analysis, focusing on identifying trends, analyzing key support and resistance levels, and evaluating gains and losses. We will look at how these techniques can support investors in effective portfolio management and planning long-term investment strategies.
 

1. Identifying long-term trends

   • Description: Logarithmic scaling provides a better understanding of long-term trends and price patterns.

   • Example: Analysis of the logarithmic chart of bitcoin since its inception shows clearer trends and support/resistance levels.

2. Analysis of key support and resistance levels

   • Description: Using logarithmic scaling allows more accurate identification of key support and resistance levels.

   • Example: On a logarithmic chart, a support level located near $10,000 for BTC may be clearer and more representative for long-term analysis.

3. Profit and loss assessment

   • Description: Analyzing logarithmic charts allows for a more proportional understanding of potential gains and losses.

   • Example: An investor evaluating potential returns on BTC investments over the years can better understand how much percentage changes have affected the value of the asset.
      

Summary

Chart scaling is a key tool in technical analysis that allows more accurate interpretation of price data.

Linear scaling is useful for short-term analysis, while logarithmic scaling is more suitable for long-term analysis and assets with high volatility.

Understanding when to use each type of scaling allows traders and investors to make more informed investment decisions, better manage risk and use technical analysis tools more effectively.