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LOGARITHMIC

Optimizing Technical Analysis with Logarithmic Scales▮ Introduction In the realm of technical analysis, making sense of market behavior is crucial for traders and investors. One foundational aspect is selecting the right scale to view price charts. This educational piece delves into the significance of logarithmic scaling and how it can enhance your technical analysis. ▮ Understanding Scales - Linear Scale This is a common graphing approach where each unit change on the vertical axis represents the same absolute value. - Logarithmic Scale Unlike the linear scale, the logarithmic scale adjusts intervals to represent percentage changes. Here, each step up/down the axis signifies a constant percentage increase/decrease. ▮ Why Use the Logarithmic Scale? The logarithmic scale offers a more insightful way to analyze price movements, especially when the price range varies significantly. By focusing on percentage changes rather than absolute values, long-term trends and patterns become more apparent, making it easier to make informed trading decisions. ▮ Comparative Examples Consider the Bitcoin price movement: - On a linear scale, a 343% increase from $3,124 to $13,870 looks smaller compared to the same percentage increase from $13,870 to $61,769. This disparity occurs because the linear scale emphasizes absolute changes. - On the logarithmic scale, both 343% increases appear proportional, giving a clearer representation. Additionally, in a falling price scenario, a linear graph might show a smaller box for an 84% drop compared to a 77% drop, simply because of absolute values' significance. The logarithmic scale corrects this, showing the true extent of percentage declines. ▮ Advantages and Disadvantages Advantages: - Fairer comparison of price movements. - Consistent representation of percentage changes. - More reliable support and resistance lines. Disadvantages: - Potential misalignment of alerts (www.tradingview.com). - Drawing inclined lines might create distortions when switching scales: A possible solution is the use the "Object Tree" feature on TradingView to manage graphical elements distinctly for each scale. ▮ How to Apply Logarithmic Scale on TradingView Enabling the logarithmic scale on TradingView is straightforward: - Click on the letter "L" in the lower right corner of the graph (the column where prices are shown); - Another option is use of the keyboard shortcut, pressing ALT + L . ▮ Conclusion The logarithmic scale is an invaluable tool for technical analysis, providing a more accurate representation of percentage changes and simplifying long-term pattern recognition. While it has its limitations, thoughtful application alongside other analytical tools can greatly enhance your market insights.
INDEX:BTCUSDEducation
by andre_007
5
Trend Following, Guide and StrategyTrend Following: A Comprehensive Guide with a Detailed Strategy Using Three Complementary Indicators Trend Following is a trading strategy that seeks to capitalize on the momentum of financial markets by identifying and riding the existing market trends. By focusing on the direction and strength of price movements, trend followers aim to profit from both upswings and downswings in various asset classes. This article will delve into the principles of trend following, discuss the benefits and drawbacks, and provide a detailed strategy using three complementary indicators, including a custom logarithmic trend channel indicator. Principles of Trend Following 1. Market direction: Trend followers believe that price movements are more likely to continue in their current direction rather than reverse. They look for long-term trends and position themselves accordingly, either by going long (buying) in an uptrend or short (selling) in a downtrend. 2. Risk management: Trend followers employ strict risk management techniques to protect their capital and limit losses. This typically involves using stop-loss orders, position sizing based on risk tolerance, and regularly monitoring market conditions to adjust positions as needed. 3. Market adaptability: Trend followers do not try to predict market movements or rely on fundamental analysis. Instead, they focus on adapting to the current market environment and following the trend as it unfolds. 4. Persistence: Trend following requires patience and discipline, as traders must withstand temporary market fluctuations and stick to their strategy even during periods of underperformance. A Detailed Strategy Using Three Complementary Indicators 1. Logarithmic Trend Channel Indicator This custom indicator is a modified version of TradingView's built-in "linear regression" script that can be plotted correctly on logarithmic charts. It helps traders identify and follow the trend by drawing a central trend line and multiple parallel deviation lines above and below it. It is important to set the logarithmic scale in the settings. 2. Moving Averages Moving averages smooth out price data, making it easier to identify trends. Two commonly used moving averages in trend following are the simple moving average (SMA) and the exponential moving average (EMA). Traders can use a combination of short-term and long-term moving averages to confirm the trend direction and generate entry/exit signals. 3. Average Directional Index (ADX) The ADX is a popular trend strength indicator that measures the strength of a trend without regard to its direction. A rising ADX indicates a strengthening trend, while a falling ADX suggests a weakening trend. Traders can use the ADX to filter out weak trends and focus on strong ones, increasing the effectiveness of their trend following strategy. Implementing the Strategy 1. Identify the trend using the logarithmic trend channel: Plot the custom indicator on a weekly chart, focusing on the central trend line and the deviation lines. If the price is consistently above the central trend line, the market is in an uptrend. If it is below the line, it is in a downtrend. It is important to set the logarithmic scale in the settings 2. Confirm the trend using moving averages: Apply a short-term and a long-term moving average to the chart. For instance, a 50-day SMA and a 200-day SMA can be used. If the short-term moving average is above the long-term moving average, it confirms an uptrend, and vice versa for a downtrend. 3. Assess trend strength using the ADX: Plot the ADX on the chart, with a commonly used threshold of 25 to differentiate between strong 4. Determine the entry and exit points: Once the trend has been identified and confirmed, determine the entry and exit points for the trade. The entry point should be near the support or resistance levels, and the exit point should be near the opposite level. 5. Apply risk management: Use appropriate risk management techniques, such as stop loss orders, to manage the risk of the trade. A stop loss order can be placed just below the support level for a long position and just above the resistance level for a short position. 6. Monitor the trade: Once the trade has been entered, monitor it regularly to ensure that it is moving in the desired direction. If the market moves against the trade, consider exiting the position with a small loss rather than risking a large loss. 7. Take profit: When the price reaches the opposite level of the support or resistance, take profit and exit the trade. Alternatively, consider trailing the stop loss order to capture additional gains if the market continues to move in the desired direction. Conclusion : This strategy can be an effective way to trade trends in the financial markets. By identifying the trend using the channel and confirming it with moving averages, traders can determine entry and exit points and apply appropriate risk management techniques. With careful monitoring and a disciplined approach, this strategy can help traders achieve consistent profits over time. However, as with any trading strategy, there is always a risk of losses, so traders should carefully consider their risk tolerance and only trade with funds that they can afford to lose.
AMEX:SPYEducation
by Julien_Eche
Advantages of Using Logarithmic Scale and when to use itThe financial markets are constantly evolving, and as such, traders and analysts need to stay ahead of the curve. One tool that has proven to be invaluable in financial analysis is the logarithmic scale. In this detailed guide, we will explore the logarithmic scale in financial analysis and its various applications in technical indicators. 1. The Logarithmic Scale: Definition and Purpose The logarithmic scale represents data on a chart by plotting the value's logarithm, rather than the value itself. This representation can better visualize exponential growth or decay and provide a more accurate depiction of price trends in markets that experience large price changes. 2. Advantages of Using Logarithmic Scale a. Better visualization of percentage changes: The logarithmic scale provides a better visualization of percentage changes in assets. This is because the scale compresses the larger movements and stretches the smaller ones. As such, traders can better analyze the percentage movements in an asset and make informed decisions. b. Equal treatment of percentage movements: The logarithmic scale treats percentage movements equally, regardless of the asset's price. This is important because it allows traders to compare assets with different price ranges, which would not be possible using a linear scale. c. More accurate representation of long-term trends: The logarithmic scale provides a more accurate representation of long-term trends in assets. This is because it takes into account the compounding effect of percentage changes over time, which is not possible with a linear scale. 3. When to Use Logarithmic Scale a. Analyzing stocks with significant price movements: Stocks that experience significant price movements are better analyzed using a logarithmic scale. This is because the scale provides a more accurate depiction of percentage changes in the stock's price. b. Evaluating historical data over extended periods: Historical data that spans an extended period is better analyzed using a logarithmic scale. This is because the scale provides a more accurate representation of the compounding effect of percentage changes over time. c. Comparing assets with different price ranges: Assets with different price ranges are better compared using a logarithmic scale. This is because the scale treats percentage movements equally, regardless of the asset's price. 4. Logarithmic Scale in Technical Indicators Incorporating logarithmic scale in technical indicators can help improve their accuracy and usability. One such example is the "Logarithmic Trend Channel" indicator, which has been adapted to work effectively on logarithmic charts. 5. How the Logarithmic Trend Channel Indicator Works The Logarithmic Trend Channel indicator is a modified version of the built-in "linear regression" script from Tradingview. The code plots the linear regression on a logarithmic chart, providing a more accurate representation of the trend when price movements are substantial. The indicator also provides options for different deviation levels, which can be adjusted according to the user's preference. 6. Applications: a. Identifying trends in assets with exponential growth or decay: The Logarithmic Trend Channel indicator can be used to identify trends in assets with exponential growth or decay. This is because the indicator provides a more accurate representation of the trend when price movements are substantial. b. Analyzing long-term price movements: The Logarithmic Trend Channel indicator can be used to analyze long-term price movements in assets. This is because the indicator takes into account the compounding effect of percentage changes over time, which is not possible with a linear scale. c. Setting support and resistance levels based on percentage changes: The Logarithmic Trend Channel indicator can be used to set support and resistance levels based on percentage changes. This is because the indicator provides a more accurate representation of percentage movements in the asset's price. Conclusion: The logarithmic scale is a powerful tool in financial analysis, providing a more accurate representation of price trends and movements, especially for assets with significant price changes. By incorporating the log scale into technical indicators, such as the Logarithmic Trend Channel, traders can better analyze market trends and make informed decisions.
NASDAQ:AAPLEducation
by Julien_Eche
25 Metrics to a Perfect Trading Journal First let’s begin with… What is a trading journal? This is a log book where you plot every trade you make with the metrics to show how your portfolio is performing and will continue to do so. I’m going to briefly list the items you’ll need to track your trading performance. 25 Items to plot in your trading journal… The trade No. The market traded (stock, index, crypto…) The entry date for your trade The exit date for your trade No. of days held Current portfolio value Max risk per trade (currency) Max risk % per trade Initial margin per instrument (CFD Spread betting) No. Volume traded The reason for entry Total margin paid Type of trade (Long / Short) Entry price Take profit price Stop loss price Closing price Risk in trade (Entry – Stop loss) Move in trade (close) Interest costs Brokerage costs Gearing Trade exposure (In and Out) Gross P+L Net P+L Don’t waste your time with calculations. Make sure you have the journal and log book with all formulas in each item. … When you record these details, you’ll be able to keep up to date with whether your portfolio is profitable and sustainable for the long run and where it’s lacking. Hope that helps!
JSE:J200Education
by Timonrosso
The unknown obvious: when to use log-scaleThere's a semi-wide-spread snake oil "wisdom" in near-quant circles that you need to use log-charts/log-scale/log-transform all the time. No, you need to use it only when the range of the data been processed exceeds one order of magnitude (data maximum at least 10 times data minimum). Before dat, no-no! Please, don't stabilize the variance unless it'll asks you to. Now bringing your attention to the important detail -> data 'being processed'. It means that you don't push the log button when your chart's arbitrary time range is 456-986755. You push dat button when the particular domain (part of the chart) you analyze does exceed one order of magnitude. P.S.: disregard the studies applied, it's all R&D
NYMEX:NG1!Education
by gorx1
Jumping S-curvesIn this post, I will explain what jumping S-curves means and how you can identify potential S-curves before they jump . First, let's begin with the chart above (also copied below). This is a yearly chart of McKesson Corporation (MCK), a medical supplies company. As you can see in the chart below, this stock has been soaring over the past year despite most other stocks being significantly lower. Here is the performance of the S&P 500 over the same time period. Whenever I see something highly unusual in a chart, such as extreme outperformance, I check the higher timeframes to see what's driving price on a technical level. Below is the yearly chart for MCK. When I examine price action over a long time period, I always log adjust my chart. Below is the log-adjusted chart. Upon seeing this chart I immediately knew what was going on: the stock price jumped S-curves. I will try to illustrate below how I reached this conclusion. To begin, I drew Fibonacci levels from the last reaction low to the last reaction high on the yearly timeframe. The previous reaction low was the bottom of 2008 because that bottom was a Fibonacci retracement of some earlier reaction high, the reaction high is the top in 2015 because price did not surpass that high without first undergoing a Fibonacci retracement (to the golden ratio). As you can see above, from 2015 to 2018 the price retraced down to the golden ratio (0.618) on the yearly chart. It is often from this retracement level that the base of the second S-curve is created. (For simplicity, I only included the 0.618 Fibonacci level on the chart). Some may say that this pattern is merely a bull flag or pennant. (See chart below) Indeed, bull flags and pennants can be another way to visualize S-curve jumps. Whereas, on a deeper, more mathematical level, S-curve jumps are logarithmic spirals (approximated as Fibonacci spirals or Golden spirals). If you wish to delve deeper into logarithmic spirals, including the Golden spiral, you can check out this Wikipedia page: en.wikipedia.org These Fibonacci or Golden spirals are present on mostly every chart and they appear on mostly every timeframe (hence they are fractal ). One of the best charts you can use to visualize these spirals is the chart of Bitcoin. Below are charts of Bitcoin which attempt to show the endless fractal nature of Fibonacci spirals (or "S-curve jumps"). I've only illustrated a few of the spirals, but indeed there are numerous spirals. (I tried to do my best using the tools on Trading View to draw these spirals, but it can be quite hard to manipulate the curves perfectly to price action.) One may ask what about when price falls? That is obviously not an S-curve jump since the price is falling. Actually, when price is crashing it is usually just an S-curve jump, or Fibonacci spiral, on the inverted chart. Although I have not tested it with scientific rigor, I do hypothesize that Bitcoin's price movement is a series of infinitely fractal and competing Fibonacci spirals on various timeframes, including Fibonacci spirals on inverted scales. Price movement can be thought of as an infinite series of S-curve dilemmas where infinitely fractal S-curves, including those of which are inverse S-curves, compete to govern the next price move. Each dilemma is resolved when an S-curve reaches its inflection point, such that it governs price movement and price moves rapidly in that direction until it approaches capacity and faces its next dilemma. Those who know Calculus may recognize this chart. Indeed this is the graph of a logistic function. The mathematical terminology for an "S-curve" is sigmoid function . Here are some more interesting charts of S-curves (none of which is intended to be investment advice) Meridian Bioscience (VIVO) jumps S-curves on its yearly chart The U.S. Dollar Index jumps S-curves on its yearly chart The entire price action of Chinese EV Company (NIO) is an S-curve that just completed a perfect golden ratio retracement Japan's faces a population S-curve dilemma Citigroup underwent S-curve growth up until the Great Recession. Then it crashed or underwent S-curve growth on the inverted chart. In summary, price movement involves an endless series of S-curves or Fibonacci spirals. Identifying an S-curve on a high time frame before it reaches its inflection point and breaks out can lead to tremendous gains (among the most lucrative gains one can realistically make in the financial markets).
NYSE:MCKEducation
by SpyMasterTrades
22
How to Use Log ScaleIn this post, I will explain how traders can maximize their use of log scale on Trading View. I will give examples of when you should use log scale on your charts and when you should not, as well as provide an in-depth analysis of its use cases, including how you can actually visualize the entire lifecycle of an asset using the log scale. In the chart above, I highlight the difference that using the wrong scale can have on your trading. The chart shows the monthly candlesticks for the U.S. Dollar Index (DXY). If one applied Fibonacci levels on a log adjusted version of the chart, one would have been under the impression that the dollar index made a huge breakout above its Fibonacci level. However, if one had not applied log adjustment, one would have correctly noticed that price was actually being resisted by the Fibonacci level. From a mathematical perspective, the U.S. dollar index ordinarily should not be log adjusted. I'll explain why below. Log adjustment simply refers to adjusting data on a logarithmic scale. Log adjustment is most suitable for visualizing data of a financial instrument or asset that is moving exponentially or in logistic growth . I will explain and illustrate both of these patterns below, but before I do so, I will discuss assets that do not move in either of these two ways and therefore should not be log adjusted. Financial instruments that are range-bound or that oscillate up and down (e.g. the VIX), ordinarily, should not be log adjusted. Similarly, financial instruments that oscillate relative to another financial instrument, such as the U.S. dollar index (the dollar index oscillates relative to the strength of other currencies), should ordinarily not be log adjusted. Additionally, financial instruments that oscillate up or down solely due to monetary policy action, such as bonds and interest rates, ordinarily, should not be log-adjusted. In all of these oscillator examples, price action does not undergo exponential decay or logistic growth relative to time and therefore log adjustment is mostly inappropriate. Applying log scale to these assets can lead to the trader reaching the wrong conclusion, such as shown with the dollar index example above, and below with an example from the VIX. Regardless of which one of these charts ultimately proves to be right (support holding or breaking for the VIX) it illustrates the problem with using the wrong scale on your charts. Using the wrong scale can lead to the wrong conclusion and put you on the wrong side of a trade. On the other hand, most other financial instruments and assets move in patterns of either exponential decay or logistic growth and should be log adjusted. Most stocks, indices, derivatives, and cryptocurrencies move in patterns that should be log adjusted. Here's an example of exponential decay : Here's an example of logistic growth : Many people look at this chart and incorrectly think that Monster Beverage (MNST) is growing exponentially, but in fact it is not. Applying log adjustment can help show this. As you can see, log adjustment shows that MNST's past price action fits the S-curve of a logistic function almost perfectly. If MNST were growing exponentially, log adjustment would just show a straight line with an upward slope. In the above example, log adjustment can actually show you hints that MNST is in the late phase of its growth cycle as price reaches capacity. As far as I am aware, no financial asset grows exponentially, as there is a finite amount of capital and a finite amount of resources in the world. When a financial instrument appears to be growing exponentially, it is merely in the upward concavity phase/maximum growth period of a logistic function. Eventually, the financial instrument will reach its capacity and its growth will begin to flatten over time. In virtually all cases, assets decline at some point in the future after reaching their capacity. Using log adjustments can help you avoid entering into positions of assets that are near capacity. Log adjustment reveals where an asset is currently positioned in its lifecycle. Take a look at the below example of Citigroup. When the Great Recession hit, Citigroup began to undergo exponential decay (relative to the broader market). See the chart of Citigroup's price action relative to the broader market (S&P 500). In some rare cases, an asset can do the opposite of this: transition from exponential decay to logistic growth. Finding and entering a position just before the inflection point can be among the most lucrative investments one can possibly make in the financial markets. Log adjustment can help you find the inflection point. In the future, I will write a post on how to find inflection points using log adjustment, and I will provide an example of an asset that is about to break out from its inflection point. Aside from visualizing the lifecycle of a financial asset, log adjustment can help eliminate skewness to better visualize patterns. Here's an example below. Log adjustment also allows us to run linear-log regressions. In short, a linear log regression can identify areas where price action is unusually above or below the mean for financial instruments that move up or down exponentially. In the chart above, we see a log-adjusted chart of Money Supply (M2SL). Applying log adjustment to the money supply and then adding a linear-log regression channel shows us that the Federal Reserve was clearly adding too much money into circulation as evident by the M2SL reaching an abnormally high standard deviation from the mean and jumping above the upper line of the regression channel. Log scales help us understand and visualize data about the world around us and the natural cycles which characterize it. Log scales and logistic growth are used in many other scientific contexts from epidemiology (e.g. tracking the spread of a virus) to demography (e.g. analyzing population growth and decline). Take a look at a log scale of Japan's Nikkei Stock Average alongside the country's population from the post-World War II era to the present day. In summary, applying log adjustment is ordinarily suitable for assets that move exponentially or in logistic growth. Applying log adjustment on the price action of an asset that moves in this manner can better help us eliminate skewness, identify abnormal deviations using linear-log regression, and allow us to visualize the lifecycle of a financial asset. Note: Sometimes the wrong scale can be useful in trading because so many other traders are also making the same error and basing their trades on the wrong scale. I've seen this happen quite frequently for Fibonacci retracements. So sometimes it can be helpful to toggle between log scale on and off to see which is causing a price reaction. In general, though, log adjustment is mostly suitable for assets moving in exponential decay or logistic growth, from a mathematical perspective.
TVC:DXYEducation
by SpyMasterTrades
17
How to use "Auto Trendline and Breakout Alert" IndicatorIn this tutorial, we will learn how to use the "Auto Trendline & Breakout Alert (Linear / Log)" indicator. Note: You can find it in the scripts section of my profile Auto Trendline & Breakout Alert(Linear / Log) Full-Version by BobRivera990 Overall Introduction This indicator is the best tool for breakout traders. Drawing and evaluating the trend lines of multiple charts in different time frames is a very time-consuming and tedious task. In addition, being aware of breakouts in the shortest possible time requires constant monitoring. With this tool, you can draw and classify trend lines in a fraction of a second and by placing an alert on any chart, you can receive notifications about breakouts, wherever you are. The classification of trend lines is done based on the reaction of the price chart to the trend lines and the analysis of the trading volume . This indicator is designed to reclassify trend lines with each reaction of the price chart. These lines are classified into 6 levels and these levels are distinguished by different colors. Thus, any touching or crossing of the price chart can make a difference. Features This indicator is designed for use on both linear and logarithmic scales. It works linearly by default. If you are using a logarithmic chart, enter the settings menu and set the chart scale parameter to “Log”. The indicator is equipped with the volume status tool to identify and avoid false breakouts. Note that you can't completely avoid false breakouts, but you can minimize risk and loss. I have already published volume status as a separate script. Several filters are provided to customize alerts. You can limit alerts based on the level and strength of broken trend lines , volume status, and type of breakout (Cross-Over, Cross-Under, or both). The last breakouts panel gives an overview of the current market situation. You can activate it in the settings menu. the figure below shows the panel: How to setup There are many parameters in the settings menu, but two are more important. One is “Chart Scale” and the other is the “Max Operational Range Length". Set the “chart scale” parameter according to the chart, otherwise the trend lines drawn by the indicator do not match the price chart. If you are using a linear chart, select the "Linear" option or if you are using a logarithmic chart, select the "Log" option. Max Operational Range Length Limits the range of the price chart that is processed by the indicator. By increasing this parameter: The strength and durability of the trend lines increases. The number of breakout signals decreases. The importance of breakout signals increases. The indicator processing load increases. The best range for "Max Operational Range" is from 300 to 1200,Change it until you get the best view possible. Also by changing the "Filter" parameter from 1X to 5X, you can reduce the clutter in the chart. The following figure shows the results of correct and incorrect settings: Use it well...
BEducation
by BobRivera990
28
Is the logarithmic scale of the Tradingview really logarithmic?I've been looking for the correct equation for a straight line on Semi-logarithmic scale for some time. The base equation is as follows: log y = mx + log k m = slope of line = (log y1 - log y0) / (x1 - x0) k = y-intercept: value of y where line crosses the x = 0 axis While this equation is absolutely correct, the result of plotting it on logarithmic scale was a curve. Then I realized that apparently in the price < 0.001 range, the logarithmic chart of Tradingview is not working logarithmically! I am so confused. Does anyone know the cause? What is the equation corresponding to the chart scale? Please help if you can.
Education
by BobRivera990
3
EDUCATION: Logarithm Growth Curve Hello, dear subscribers! Today we are going to examine very simple and intersting instrument which is applicable for the global price movement analysis. The logarithm growth curve is based on Fibonacchi retracement levels. As it is known the Fib retracement based on swing high and low levels. But in case of growth curve we use the logarithm scale to take in account the periods of the fast growth (to the moon periods). The price usually faces with difficulties to break through the Fibonacci levels. We can notice massive pullbacks near these levels or the price growth in cases of breakouts. Let's consider the current situation on the Bitcoin market. There is a rejection of 50% Fibonacci level. Now we should observe if the price break through this level or the drop began now. If the first scenario occurs we can see a massive growth to 61% or 100% Fibonacci levels. DISCLAMER: Information is provided only for the educational purposes and should not be used to take action in the markets.
BITSTAMP:BTCUSDEducation
by Skyrexio
6
The Ace Spectrum as a Template for Support ProjectionDemonstrating the big idea: That straight lines in log-space form exponential curves. This property of the log chart is useful for examining assets with exponential growth (like high-growth stocks, cryptos, etc). Because the log scale asymptotically approaches the absolute scale as y slice decreases, this indicator is really applicable to any time scale. This indicator samples a distribution of lines from the past and projects them into the future, these projected lines form indicators of prior support. The idea is longer support at those specific lines is indicative of support strength, which this indicator approximately captures. My initial goal was to capture this intuition about exponential growth in log spaces by applying a monte-carlo style sampling approach to visualize the latent support lines. After I had captured that in a slightly more complex version of this indicator, my goal was to distill the concept into the simplest possible implementation.
NASDAQ:AAPLEducation
by sheganinans
15
AMZN: Arithmetic and Logarithmic Charts ExplainedIn this post, I'll be shedding light on the difference between arithmetic and logarithmic scale charts, and how to best use both charts to your advantage. Arithmetic Chart - The chart on the left is a chart that uses the arithmetic scale - This is the chart most common to us all, and one that's easiest for traders and investors to comprehend - An arithmetic chart represents price on the y axis, using equidistant spacing between the prices - This is demonstrated on the arithmetic scale above; the distance between 1 and 2, is the same as the distance between 8 and 9 - Arithmetic charts demonstrate absolute value Logarithmic Chart - The log chart on the right side has a different approach to interpreting price movement - The y axis uses equidistant spacing between designated prices - This is demonstrated on the logarithmic scale above; the distance between 1 and 2, is the same as the distance between 2 to 4, 4 to 8, and so on. - The logarithmic chart demonstrates the percentage change in the underlying asset's price Case Study: Amazon (AMZN) - We can take a look at Amazon's arithmetic and logarithmic charts, dividing them by significant phases to better understand the differences - We can first see that the area marked by 'extreme volatility' on the log chart, is much more drastically demonstrated than that of the arithmetic chart - This is because price fluctuations in terms of percentages were drastic at the time, due to the Dot-com Bubble. - For more information on the Dot-com bubble and today's stock bubble, you can check out my other analysis below: - However, because in terms of the absolute value changes during the Dot-com bubble are minuscule compared to the price fluctuations today, the phase of extreme volatility is barely noticeable in the arithmetic chart - In the period of a 'steady uptrend', we can see a clear and steady uptrend in the logarithmic chart, indicating that the stock moved up at a consistent pace, percentage-wise - The arithmetic chart, while not drastic in the uptrend's degree, demonstrates parabolic momentum building up - We then have the 'exponential growth' phase. Here, we see a move from $400 to $3,400 on the arithmetic scale. - However, the logarithmic chart merely demonstrates a steady uptrend without much volatility. - This is because while the absolute value of the stock has risen significantly over time, the percentage change in the rise was consistent. Conclusion While the arithmetic chart is more familiar for the average trader/investor, logarithmic charts help us clearly view long term data, especially when price points show immense volatility during the short term. As such, log charts can be effectively used in for technical analysis of cryptocurrencies, as well as volatile tech stocks with long price history. The understanding of the log chart is an effective tool, but it must be used with caution, since most people intuitively interpret a chart as an arithmetic one. If you like this analysis, please make sure to like the post, and follow for more quality content! I would also appreciate it if you could leave a comment below with some original insight.
NASDAQ:AMZNEducation
by Michael_Wang_Official
7