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Logscale

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.
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INDEX:BTCUSDEducation
by andre_007
5
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
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
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
Surprise! How to use fib correctly. Log fib!In a previous idea I said if it got 50 likes I would post a surprise. I think they don't want you to know... Some people might already know this but I know for a fact the vast majority does not. I hope this does not stop working now that I share it. I have plenty of other strats and if markets evolve and 1 strat stops working I know I'll be the first to evolve so I do not even mind. Now how to draw the log fib? You simply use "Fib channel" and voila. I think it is supposed to be a fib that gets drawn diagonally, but unlike the regular fib it scales with log. So it can be diverted from its main purpose and used this way. Some examples: It looks like the stock market retraces have been more shallow since investors have been telling people to buy & hold. Didn't stop billionaires from being made. On something that went up 10 years, +600%, like gold I am not sure which one is best. On really big moves it has to be the log one obviously. You can only see the top 10% on the linear chart and most of it is too smal because of the exponential rise. Amazon is a good example. I am not saying this works 100% of the time & don't go all in. There are not a whole lot of really large moves so not a huge sample size to work with. Since crypto has no intrisic value and most importantly is highly manipulated I expect this to keep working perfectly until the crypto cow is entirely milked and there is nothing left in. Crypto is still at a 150 billion market cap, at under 25 billion they might think it's not worth their time anymore. Since miners might bail out (I heard they were doing it little by little) and wash trading / ponzi exchanges are going to exit scam, it could only work once more and then suddenly end. Crypto was nice and all when it was only made up of noobs, but in 2017 the sophisticated crowd joined and they are interested in cold hard cash, not imaginary money they won't ever be able to cash out of and transform into real concrete money (since it has negative sum rate & no value). I wish I knew about it earlier and had money to spare. But we almost all have to deal with getting so close to making huge returns and just miss it by a hair. Those that accepted it have been able to move forward, and we can grow (as fast as our mightly lords the regulators that control our lives will allow). Those that are still in denial and cannot accept they missed their chance to buy early / cash out at the top, are stuck and will get milked to the last drop (until crypto is small enough the whales ignore it & they'll keep coming any time it grows). As a conclusion; when you look at really big timeframes / or moves of maybe 1000% in a short time, use the log fib ==> This is how you do it on tradingview. Until next bubble ;)
BITFINEX:BTCUSDEducation
by MrRenev
2