Session KillZones [7Bridges]Session Killzones by 7Bridges indicator display the killzones of asian, LND and NY sessions. There is also a custom session of your choice.
The times of each killzone are GMT time and you can adjust it in the settings.
You have also the beginning of the day, GMT and EST timezones.
By default the killzones are set like that on the GMT/UTC timezone :
-> Asia : 00:00 - 06:00
-> Pre London : 06:00 - 07:00
-> London : 07:00 - 10:00
-> New York : 12:00 - 15:00
-> Custom session : choose your own time
What makes the indicator very different is that the session is not overlapping the price but you have bars below and above the price.
Settings:
-> you can chose to display the Killzones (Asia, pre LND, LND and NY)
-> you can manages the time of the sessions
-> you can chose to display the start of the day (GMT/UTC and EST )
The indicator is displayed by default only for all the timeframes below 60min.
Volatility
Intraday Mean Reversion MainThe Intraday Mean Reversion Indicator works well on certain stocks. It should be used for day trading stocks but need to be applied on the Day to Day timeframe.
The logic behind the indicator is that stocks that opens substantially lower than yesterdays close, very often bounces back during the day and closes higher than the open price, thus the name Intraday Mean reversal. The stock so to speak, reverses to the mean.
The indicator has 7 levels to choose from:
0.5 * standard deviation
0.6 * standard deviation
0.7 * standard deviation
0.8 * standard deviation
0.9 * standard deviation
1.0 * standard deviation
1.1 * standard deviation
The script can easily be modified to test other levels as well, but according to my experience these levels work the best.
The info box shows the performance of one of these levels, chosen by the user.
Every Yellow bar in the graph shows a buy signal. That is: The stocks open is substantially lower (0.5 - 1.1 standard deviations) than yesterdays close. This means we have a buy signal.
The Multiplier shows which multiplier is chosen, the sum shows the profit following the strategy if ONE stock is bought on every buy signal. The Ratio shows the ratio between winning and losing trades if we followed the strategy historically.
We want to find stocks that have a high ratio and a positive sum. That is More Ups than downs. A ratio over 0.5 is good, but of course we want a margin of safety so, 0.75 is a better choice but harder to find.
If we find a stock that meets our criteria then the strategy will be to buy as early as possible on the open, and sell as close as possible on the close!
PhenomIt is a simple and effective tool for trading on moving averages.
The main advantage is that an ATR-based risk management system is included here. The system is based on the work of FullTimeTradingRu and the FBMA indicator
How to use the system:
1. I recommend using a daily timeframe.
2. Look for a rebound from the moving average, the most effective 20 Ema. For convenience, the colors of the bars are painted green in an uptrend.
3. Enter the transaction using hints. The recommended number of shares to buy is indicated in the table, taking into account your deposit and the risk per transaction from the deposit (by default 1%). Stop 1.5 ATR. Everything is the same for opening short positions.
4. I recommend entering the second trade only if the previous one passed 0.5 ATR, thereby confirming the trend and the fact that you correctly guessed the movement.
There are ATR settings in the script
Last bar show — How many bars to show
ATR lines ATR Step — For a more convenient view, ATR lines can be turned into a ladder.
Strat Trail Stop by AlexsOptionsWhat does this script do?
This script plots previous aggregation highs or lows based on the trend of the candles.
Scenario 1 -> Up Trend
If the previous high of a candle is violated the green trail line will trail using the lows of the prior candle. It will continue until a previous low is violated. Once a previous low is violated it will switch to scenario 2
Scenario 2 -> Down Trend
If the previous low of a candle is violated the red trail line will trail using the highs of the prior candle. It will continue until a previous high is violated. Once a previous high is violated it will switch to scenario 1
This indicator has two trails. One is expected to be a lower timeframe the other a higher timeframe.
The higher timeframe has an option to instead use the open of the higher timeframe instead of the trail logic in the scenarios above.
If selected it will plot the open of the designated timeframe, the color will be green if trading above and red if trading below
This script is best used in conjunction with a good understanding of #TheStrat trading strategy. You are then able to create alerts for when your positions fall out of favor.
Rainbow Drift BetaRainbow Drift Beta is an indicator that detects the triggers of long and short positions at any TF.
It's based on two different type of approaches to the EMAs periods:
- Classic EMAs periods: 10 and 50
- Cycle EMAs perdios: 16, 64 and 256
The 256 period EMA (Annual Cycle) detects the trend: if the EMA 64 (Three-Weekly Cycle) is above, it shows an uptrend; while the EMA 64 is below, it means that the price action is in downtrend.
10 and 16 periods EMAs are working together as well as the 50 and the 64. The first couple reacts faster than the second one and as soon as the 10 is above the 16, the band shows the first attempt of the price action to go in the uptrend direction. The same concept is applied to the second couple (50, 64): when EMA 50 > EMA 64 it's a confirmation of the faster EMAs long direction. Viceverca happens for the downtrend but with the same concept.
As the EMA periods taken in consideration are quite often a sensitive level of reaction of the price, the indicator detects when there is trigger of a long or a short set up and plots a label on the chart. It's possibile to set up an alert as well.
Quite important, the indicator is looking for sideways patterns as the breakout of them shows a clear direction of the price.
Moreover, in order to privide the first and the best entry possibile, the indicator has a function that is triggering only one time as the trend reverted: for example, a long entry on the EMA 10-16 happens only one time since they crossover the EMA 64.
As included in the name, this is a beta version and new improvements will be added in the near future like suggested price entry, SL and TP, and the focus of the development is to avoid as much as possibile the false triggers.
Of course the best way to improve the code is to receive the users' feedbacks, so please feel free to post your comments and questions.
Donchian Channels [Gu5]█ OVERVIEW
I changed the design of the classic indicator "Donchian Channels", for easy reading.
█ CONCEPTS
Donchian Channels is an indicator made up of upper and lower bands around a mid-band or Basis.
The upper band marks the highest price of a security for N periods, while the lower band marks the lowest price of a security for N periods. The area between the upper and lower bands.
In this version, when there are new Higher High (HH), the trend is Bullish and the channel is painted green.
When there are new Lower Low (LL), the trend is Bearish and the channel is painted Red
█ OTHER SECTIONS
A plus in this script: When there are no new highs or new lows, there is no certain trend
The channel is painted yellow
www.tradingview.com
• HOW TO USE
Menu "Display"
• '■ Basis On/Off': Shows the midline Basis
• '■ Alert On/Off': Shows alerts labels
• '■ Fill On/Off': Paint the entire channel the color of the trend
• '■ Bar Color On/Off': Paint the candle the color of the trend
• '■ Close Alert On/Off': Shows alerts end of trend
• NOTES:
This code was written using the recommendations from the Pine Script™ User Manual's Style Guide
• RAMBLINGS:
You can use the "Basis" line as Trailing Stop.
• THANKS:
Donchian Channels developed by Richard Donchian
and many MANY thanks to @PineCoders
Z-Score(Slope(OBV(LBC)))Summary : Market price is simply a dance of liquidity to the specific market.
tl;dr: "Cash come-in, market moon; Cash go-out, market doom"
In Simple Language : Large changes in the money flow to an asset often mark local price extremia.
Academic paper:
Title: Z-Score(Slope(OBV)): An Efficient Indicator for Identifying Local Extremes in Asset Prices
Abstract: This paper presents a novel trading indicator, Z-Score(Slope(OBV)), that aims to predict local extremes in asset prices by analyzing the patterns of money flow. The indicator is constructed using the Z-score of the slope of the On Balance Volume (OBV).
Hypothesis: The price levels at which the money flows into and out of an asset often mark local extremes. This notion underpins our exploration of the Z-Score(Slope(OBV)) indicator's potential in identifying these critical points.
1. On Balance Volume (OBV): The OBV is a momentum indicator that leverages the volume flow to forecast potential changes in asset prices. It operates on the premise that changes in volume often presage shifts in price. The OBV algorithm adds a period's volume to the cumulative total when the closing price is up and subtracts it when the closing price is down. Therefore, an ascending OBV suggests positive volume pressure, potentially heralding higher prices, while a declining OBV signifies negative volume pressure, possibly indicating lower prices.
2. Slope: In this context, the slope represents the rate of change of the OBV. It is a measure of the rise-over-run for a linear regression line through the OBV data points. By evaluating the slope of the OBV, we can extract valuable insights into the momentum of the volume. A positive slope indicates increasing volume momentum, suggesting growing interest in the asset, while a negative slope implies declining volume momentum, potentially reflecting dwindling interest.
3. Z-Score: The Z-score is a statistical measure that delineates a data point's relationship to the mean of a group of values, expressed in terms of standard deviations from the mean. For instance, a Z-score of 0 reveals that the data point's score aligns with the mean score. Positive Z-scores indicate values higher than the mean, and negative Z-scores represent values lower than the mean. Applying the Z-score to the slope of the OBV allows us to comprehend the degree of deviation of the current OBV slope from its historical mean.
A Z-score of 1 suggests that the OBV's slope is one standard deviation from the mean, which implies that the slope is within the range of values where approximately 68% (not 67%) of all values lie.
A Z-score of 2 implies that the slope is two standard deviations from the mean, thus within the range where roughly 95% of all values lie.
A Z-score of 3 indicates that the slope is three standard deviations from the mean, putting it within the range where about 99.7% of all values lie.
Z-scores of 4 and 5 and beyond are increasingly rare and represent extreme values.
4. The Z-Score(Slope(OBV)) Indicator and Line Break Chart Synergy: The Z-Score(Slope(OBV)) indicator's efficiency is further amplified when visualized using a Line Break chart. This chart type disregards time, concentrating solely on price changes, thus providing a clear visualization of market trends. When combined with the Line Break chart, the Z-Score(Slope(OBV(LBC))) indicator can help traders identify trend shifts more accurately and promptly, reinforcing the hypothesis that price levels where money flows into and out of an asset often mark local extremes.
In summary, the Z-Score(Slope(OBV)) indicator, combining volume, momentum, and statistical analysis, provides a robust tool for traders to predict local extremes in asset prices.
Regarding Implementation:
- This is implemented using Pinescript V5
- Uses inbuilt ta module
- Very effective and simple and efficient computation in 30 lines of code
ATR CandlesAverage true range (ATR) is a market volatility indicator used to show the average range prices swing over a specified period.
The ATR Candles indicator has two primary functions. First, it measures a short-term ATR against a longer-term ATR to show if volatility is contracting or expanding.
Secondly, this indicator goes a step further by highlighting individual candles that exceed or fall below user selected ATR thresholds.
Moments of volatility contraction often lead to expansion and vice versa. By using the ATR Candles traders can identify potential imminent breakouts/breakdowns or healthy pullbacks vs a volatile correction.
Indicator Features
Selectable ATR lengths
Selectable threshold limits (1 contraction / 2 expansion)
Calculate current candles range from open / previous close / daily range
Custom colors
Show or hide every element
Absolute Momentum IntensityNo lag, no boundaries, real momentum indicator.
Momentum = mass × velocity
In trading, this would be: volume × candle size. But due to the huge differences in volumes and volatility in the market, strong momentum crushes (flattens) average momentum, making it unpractical in an indicator. AMI provides a usable and adjustable workaround to this problem.
HOW DOES AMI WORK?
AMI measures and plots the momentum of each candle individually, with a formula I invented (or so I believe).
Formula: (Actual volume / Moving average of the volumes) × (Actual size of the candle / Moving average of the size of the candles)
Put simply, it multiplies the ratio between actual and past volumes, by the ratio between actual and past candles' sizes.
The length of the moving averages used in AMI's calculation is called "Contrast" in the settings.
A contrast of 20 shows every single impulse.
100 flattens small moves, thus revealing when the momentum is at its strongest.
Feel free to adjust the contrast of AMI to fit your needs.
The result is plotted starting from the last point. So the angle of each segment expresses the momentum of the corresponding candle.
Note: AMI will not run without enough candles or volume datas, on higher timeframes for example (W,M...).
HOW TO READ AMI?
AMI's line color, angle, and backgrounds help identify the current momentum as bullish, bearish, weak, or strong.
When AMI crosses the closest ribbon's line (which is in gray by default), its color changes, signaling a shift in momentum.
When the 3 ribbons are fully deployed, separated by large backgrounds, the momentum can be considered strong. This is what we are looking for.
When the momentum decreases, the background color changes (gray by default). It can be nothing, or it can be an early sign of consolitation or even reversal, especially if more do follow.
AMI adjusts to the size of its pane. Therefore, it is a good idea to keep a period of strong momentum in the screen, as a scale.
Comparing the actual momentum with the past ones sheds some light on the intensity of the price action.
DIVERGENCES
Divergences are relevant as long as there's amplitude in the chart. But it is still hard to estimate how far the expected move will go.
AMI comes with a divergence detection system. It won't show all the divergences though. Just the ones it can pick. So you might look for more, and adjust the settings to your needs.
This part of the script is independant from AMI, and easy to identify, so you can delete it if you don't need it.
DO NOT BASE YOUR TRADING DECISIONS ON 1 SINGLE INDICATOR'S SIGNALS.
Always confirm your ideas by other means, like price action and indicators of a different nature.
Volatility patterns / quantifytools- Overview
Volatility patterns detect various forms of indecisive price action, on a larger scale as a compressed range and on a smaller scale as indecision candles. Indecisive and volatility suppressing price action can be thought of as a spring being pressed down. The more suppression, the more tension is built and eventually released as a spike or series of spikes in volatility. Each volatility pattern is assigned an influence period, during which average and peak relative volatility is recorded and stored to volatility metrics.
- Patterns
The following scenarios are qualified as indecision candles: inside candles, indecision engulfing candles and volatility shifts.
By default, each indecision candle is considered a valid pattern only when another indecision candle has taken place within 3 periods, e.g. prior inside candle + indecision engulfing candle = valid volatility pattern. This measurement is taken to filter noise by looking for multiple hints of pending volatility, rather than just one. Level of tolerated noise can be changed via input menu by using sensitivity setting, by default set to 2.
Sensitivity at 1: Any single indecision candle is considered a valid pattern
Sensitivity at 2: 2 indecision candles within 3 bars is considered a valid pattern
Sensitivity at 3: 2 indecision candles within 2 bars (consecutive) is considered a valid pattern
The following scenarios are qualified as range patterns: series of lower highs/higher lows and series of low volatility pivots.
A pivot is defined by highest/lowest point in price, by default within 2 periods back and 2 periods forward. When 4 pivots with qualities mentioned above are found, a box indicating compressed range will appear. Both required pivots and pivot definition can be adjusted via input menu.
- Influence time and metrics
By default, influence time for each volatility pattern is set to 6 candles, a period for which spike(s) in volatility is expected. For each influence period, average relative volatility (volatility relative to volatility SMA 20) and peak relative volatility is recorded and stored to volatility metrics. All metrics used in calculations are visible in "Data Window "tab. Average and peak volatility during influence period will vary depending on chart, timeframe and chosen settings. Tweaking the settings might result in an improvement and is worth experimenting with.
- Visuals
By default, indecision candles are visualized as yellow lines and range patterns as orange boxes. Influence time periods are respectively visualized as colored candle borders, applied as long as influence time period is active. All colors are fully customizable via input menu.
- Practical guide
Volatility patterns depict moments of equal strength from both bulls and bears. While this equilibrium is in place, price is stagnant and compresses until either side initiates volatility, releasing the built up tension. On top of hedging and playing the volatility using volatility based instruments, some other methods can be applied to take advantage of the somewhat tricky areas of indecision.
Example #1: Trading volatility
Volatility is not a bad thing from a trading perspective, but can actually be fertile ground for executing trade setups. Trading volatility influence periods from higher timeframes on lower timeframes gives greater resolution to work with and opportunities to take advantage of the wild swings created.
Example #2: Finding bias for patterns
Points of confluence where it anyway makes sense to favor one side over the other can be used for establishing bias for indecisive price action as well. At face value, it makes sense to expect bearish reactions at range highs and bullish reactions at range low, for which volatility patterns can provide a catalyst.
Example #3: Betting on initiation direction
Betting on direction of the first volatile move can easily go against you, but if risk/reward is able to compensate for the poor win rate, it's a valid idea to consider and explore.
[TT] Sectors Dist % From MA- The script shows the distance in percentages from the 200 MA (or any other MA period) , for the 11 SP500 sectors.
- It works based on the current time frames.
Could be useful when working with mean reversion strategies to detect extremes zones and overbought/oversold conditions in the given sectors compared others.
Expected VolatilityExpected Volatility
Hello and welcome to my first indicator! I'm publishing this indicator as free to use and modify because I think it's a great place to learn and I hope I can teach you something.
There are some terms which you need to understand before I begin explaining this indicator and what it does for you:
Daily Settlement - The price at which a market closes when the trading day closes (RTH or Regular Trading Hours close)
Standard Deviation - A measure in statistics that declares how far away a data point is from the mean when compared with all the data points before it to an extent
Now for the history behind this indicator:
Rule of 16. This goes back to the VIX, or S&P 500 volatility index. The idea behind the volatility index is to determine what magnitude of movement could be expected from the market the following day based on recent movement. The rule of 16 is an easier way to refer to the square root of the number of trading days in a year. There are 252 trading days in a year and the square root of 252 is approximately 15.87. We estimate it to be 16 because it's easier to talk about when it's easier to say and therefore easier to remember.
The relevance of this rule is that when the VIX is at 16, we can expect a market movement of 1% or so unless some special circumstances overrule this estimate. To get the expected market movement, we take 16 and divide by 16 and get 1, or 1%. If the VIX is trading at 24, we get 24/16 or 1.5 which is 1.5% movement. This indicator seeks to simplify the math and lay it out in a visual way to show the highest probability of range the market is expected to trade.
Thanks for taking the time to read my description, I hope you like my indicator.
Special thanks to my trading friends and coaches for helping me complete this indicator.
SuperBollingerTrend (Expo)█ Overview
The SuperBollingerTrend indicator is a combination of two popular technical analysis tools, Bollinger Bands, and SuperTrend. By fusing these two indicators, SuperBollingerTrend aims to provide traders with a more comprehensive view of the market, accounting for both volatility and trend direction. By combining trend identification with volatility analysis, the SuperBollingerTrend indicator provides traders with valuable insights into potential trend changes. It recognizes that high volatility levels often accompany stronger price momentum, which can result in the formation of new trends or the continuation of existing ones.
█ How Volatility Impacts Trends
Volatility can impact trends by expanding or contracting them, triggering trend reversals, leading to breakouts, and influencing risk management decisions. Traders need to analyze and monitor volatility levels in conjunction with trend analysis to gain a comprehensive understanding of market dynamics.
█ How to use
Trend Reversals: High volatility can result in more dramatic price fluctuations, which may lead to sharp trend reversals. For example, a sudden increase in volatility can cause a bullish trend to transition into a bearish one, or vice versa, as traders react to significant price swings.
Volatility Breakouts: Volatility can trigger breakouts in trends. Breakouts occur when the price breaks through a significant support or resistance level, indicating a potential shift in the trend. Higher volatility levels can increase the likelihood of breakouts, as they indicate stronger market momentum and increased buying or selling pressure. This indicator triggers when the volatility increases, and if the price is near a key level when the indicator alerts, it might trigger a great trend.
█ Features
Peak Signal Move
The indicator calculates the peak price move for each ZigZag and displays it under each signal. This highlights how much the market moved between the signals.
Average ZigZag Move
All price moves between two signals are stored, and the average or the median is calculated and displayed in a table. This gives traders a great idea of how much the market moves on average between two signals.
Take Profit
The Take Profit line is placed at the average or the median price move and gives traders a great idea of what they can expect in average profit from the latest signals.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Keltner Trend V3It's just a simple keltner trend with options added to:
Eradicate repainting
more MAs
Json alerts (useful for bots)
I recommend using "open" option for all sources if you are going to use it with a bot, or if you want to be safe and enter with confirmations. Using the default settings would also show you all the entries without repainting as it uses high and low prices to check breakouts and not solely the close price (which is generally a false representative in historic analysis).
My favorite lengths are 7, 14, and 21. There is no specific reason, they just seem to work well most of the time. You can (and should) optimize it to your purposes.
Thanks to the original author @jaggedsoft this script is just a improved version of theirs.
Fetch ATR + MA StrategyA trend following indicator that allows traders/investors to enter trades for the long term, as it is mainly tested on the daily chart. The indicator fires off buy and sell signals. The sell signals can be turned off as trader can decide to use this indicator for long term buy signals. The buy signals are indicated by the green diamonds, and the red diamonds show the points on then chart where the asset can be sold.
The indicator uses a couple indicators in order to generate the buy signals:
- ADX
- ATR
- Moving Average of ATR
- 50 SMA
- 200 SMA
The buy signal is generated at the cross overs of the 50 and 200 SMA's while the ATR is lower than then Moving Average of the ATR. The buy signal is fired when these conditions are met and if the ADX is lower than 30.
The thought process is as follows:
When the ATR is lower than its moving average, the price should be in a low volatilty environment. An ADX between 25 and 50 signals a Strong trend. Every value below 25 is an absent or weak trend. So entering a trade when the volatilty is still low but increasing, you'll be entering a trade at the start of a new uptrend. This mechanism also filters out lots of false signals of the simple cross overs.
The sell signals are fired every time the 50 SMA drops below the 200 SMA.
Line Colorizer - DurbtradeThe Line Colorizer is a simple indicator that can plot up/down-colorized lines for up to 10 unique individual sources!
Plot up/down colors are based on whether the current value is above or below the previous value.
Also included is a separate color for when the current value is equal to the previous value.
All colors can be modified, along with the plot styles.
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Here is the Inputs tab of the Settings menu :
As you can see, you can plot a colorized line of up to 10 individual sources!
Checking the checkbox turns on that particular colorized plot,
and clicking on the drop down menu allows you select the source for that plot.
The plot styles, up/equal/down colors, and opacities
are customizable under the Style tab within the Settings menu :
Overall, it is pretty easy to use.
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Let's look at some examples of the Line Colorizer being used...
Colorize a basic Bollinger Bands indicator :
Want to colorize 3 EMA's? Go for it :
Spice up the standard MACD salad :
Customize the colors of your RSI's :
Try using the Line Colorizer on all of your favorite indicators.
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Script Stats :
Pinescript Version : 5
Code Length : 44 Lines
Max Unique Input Sources : 10
Max Visible Plots : 10
Total Colors/Opacities : 30
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Tips :
Typically you will want this indicator to be on a layer above (in front of) the source plot layer.
Stay mindful of line thicknesses,
and whether the original source plot is still visible or not.
The final output of the colorized plots are drawn in numerical order,
so, Colorized Source #1 is drawn first, and will appear below Colorized Source #2 on the chart...
and so on, with Colorized Source #10 being drawn last, at the very top.
Final Thoughts :
I like having this indicator.
The idea and script is simple, and the indicator is practical.
It's one method of easily separating some of the aspects of color from your favorite indicators and scripts,
and then customizing those aspects to your liking.
Especially practical for those who do not want to learn about writing their own scripts.
I think that this indicator can be a useful tool in the shed,
used for customizing the visuals of multiple unique sources
that are all on the same price/value scale.
It can help increase chart clarity and/or detail...
whether using it on top of a main chart that is simple,
or on top of a standalone indicator that is crowded with oscillating information.
I hope that you enjoy it and find it useful!
- Please feel free to comment your thoughts, critiques, or suggestions. They are all very helpful!
- Also, please feel free to comment any positive feedback, or awesome screencaps/ideas of the indicator in action!
- Check out my other Pinescript indicators if you like this one... they work well together.
- May your trades be successful!
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// Durbtrade
Directional ATROANDA:EURUSD
TLDR: A custom volatility indicator that combines Average True Range with candle direction.
The Directional ATR (DATR) is an indicator that enhances the traditional Average True Range (ATR) by incorporating the direction of the candle (bullish or bearish).
This indicator is designed to help traders identify trend strength, potential trend reversals, and market volatility.
Key Features:
Trend Confirmation: Positive and increasing DATR values suggest a bullish trend, while negative and decreasing values indicate a bearish trend. A higher absolute DATR value signifies a stronger trend.
Trend Reversal: A change in the direction of the DATR from positive to negative or vice versa may signal a potential trend reversal.
Volatility: Like the standard ATR, the DATR can be used to gauge market volatility, with larger absolute values indicating higher volatility and smaller values suggesting lower volatility.
Divergence: Divergence between the price and the DATR could signal a potential weakening of the trend and an upcoming reversal.
Overbought/Oversold Levels: Extreme DATR values can be used to identify overbought or oversold market conditions, signaling potential reversals or corrections.
Please note that the Directional ATR is just an indicator, and the interpretations provided are based on its underlying logic.
It is essential to combine the DATR with other technical analysis tools and test the indicator on historical data before using it in your trading strategy. Additionally, consider other factors such as risk management, and your own trading style.
ATR ControlThis indicator shows the following values:
ATR value of the current symbol
Size of the full position based on the maximum risk set
Three sizes that are percents of the full size already present in this indicator
Customizable settings are:
Show/hide single rows
ATR Timeframe
ATR Lenght
First percent of the split to apply
Second percent of the split to apply
Maximum risk
The last percent is automatically calculated using the first two.
Example:
Full size: 500
First percent: 10
Second percent: 40
The third percent is calculated as 100 - first percent - second percent = 50
The split sizes shown are: 50/200/250
Turtle tradingA minimal breakout trend following indicator (Turtle trading). Entry is on the break of a Donchian channel and exit is on the reversal at a shorter-term Donchian channel (trailing stop).
Entry levels are hidden in an active trend, and only the active exit level is shown. Levels and entry/exit markers can be shown or hidden independently.
FibonRSI / ErkOziHello,
This software is a technical analysis script written in the TradingView Pine language. The script creates a trading indicator based on Fibonacci retracement levels and the RSI indicator, providing information about price movements and asset volatility by using Bollinger Bands.
There are many different scripts in the market that draw RSI and Fibonacci retracement levels. However, this script was originally designed by me and shared publicly on TradingView.
***The indicator uses RSI (Relative Strength Index) and Bollinger Bands (BB) as the basis for the FibonRSI strategy. RSI measures the strength of a price movement, and BB measures the volatility of an asset. The FibonRSI strategy is based on the idea that the Fibonacci ratios and RSI can be used to predict a asset's price retracement levels.
***The script allows for various parameters to be adjusted. Users can specify the price source type and adjust the periods for RSI and Bollinger Bands. The standard deviation number for Bollinger Bands can also be customized.
***The script calculates the current RSI indicator position and the basic, upper, and lower levels of Bollinger Bands. It then calculates and draws the Fibonacci retracement levels. The color of the RSI line is determined by the upper and lower distribution levels of Bollinger Bands. Additionally, the color of the Fibonacci retracement levels can also be customized by the user.
***This script can be used to determine potential buy and sell signals using Fibonacci retracement levels and RSI. For example, when the RSI is oversold and the price is close to a Fibonacci retracement level, it can be interpreted as a buying opportunity. Similarly, when the RSI is overbought and the price is close to a Fibonacci retracement level, it can be interpreted as a selling opportunity.
***The script takes input parameters such as the price source used for calculation, the period for the RSI indicator, the period for the Moving Average in Bollinger Bands, and the number of standard deviations used in Bollinger Bands.
***The script's conditions include elements such as calculating the current position of the RSI indicator, calculating the upper and lower Bollinger Bands, calculating the dispersion factor, and calculating Fibonacci levels.
***The parameters in the code can be adjusted for calculation, including the price type used, the RSI period, the Moving Average period for BB, and the standard deviation count for BB. After this, the current position of the RSI, Moving Average, and standard deviation for BB are calculated. After calculating the upper and lower BB, the levels above and below the average are calculated using a specific dispersion constant.
CONDITIONS FOR THE SCRIPT
current_rsi = ta.rsi(src, for_rsi) // Current position of the RSI indicator
basis = ta.ema(current_rsi, for_ma)
dev = for_mult * ta.stdev(current_rsi, for_ma)
upper = basis + dev
lower = basis - dev
dispersion = 1
disp_up = basis + (upper - lower) * dispersion
disp_down = basis - (upper - lower) * dispersion
// Fibonacci Levels
f100 = basis + (upper - lower) * 1.0
f78 = basis + (upper - lower) * 0.78
f65 = basis + (upper - lower) * 0.65
f50 = basis
f35 = basis - (upper - lower) * 0.65
f23 = basis - (upper - lower) * 0.78
f0 = basis - (upper - lower) * 1.0
***When calculating Fibonacci levels, the distance between the average of BB and the upper and lower BB is used. These levels are 0%, 23.6%, 35%, 50%, 65%, 78.6%, and 100%. Finally, the RSI line that changes color according to a specific RSI position, Fibonacci levels, and BB are visualized. Additionally, the levels of 70, 30, and 50 are also shown.
The script then sets the color of the RSI position according to the EMA and draws Bollinger Bands, RSI, Fibonacci levels, and the 70, 30, and 50 levels.
In conclusion, this script enables traders to analyze market trends and make informed decisions. It can also be customized to suit individual trading strategies.
This script analyzes the RSI indicator using Bollinger Bands and Fibonacci levels. The default settings are 14 periods for RSI, 233 periods and 2 standard deviations for BB. The MA period inside BB is selected as the BB period and is used when calculating Fibonacci levels.
***The reason for selecting these settings is to provide enough time for BB period to confirm a possible trend. Additionally, the MA period inside BB is matched with the BB period and used when calculating Fibonacci levels.
***Fibonacci levels are calculated from the distance between the upper and lower bands of BB and show how RSI movement is related to these levels. Better results can be achieved when RSI periods are set to Fibonacci numbers such as 21, 55, and 89. Therefore, the use of Fibonacci numbers is recommended when adjusting RSI periods. Fibonacci numbers are among the technical analysis tools that can capture the reflection of naturally occurring movements in the market. Therefore, the use of Fibonacci numbers often helps to better track fluctuations in the market.
Finally, the indicator also displays the 70 and 30 levels and the middle level (50) with Fibonacci levels drawn in circles. Changing these settings can help optimize the Fibonacci levels and further improve the indicator.
Thank you in advance for your suggestions and opinions......
Price Extrapolator with Std DeviationPrice Extrapolator with Deviation Cones - A Powerful Tool for Predicting Future Prices
Subtitle: Discover how this custom indicator can help you forecast potential price movements with greater accuracy, using historical data.
Introduction
Predicting future price movements is always a challenge for traders and investors. However, by using historical data and statistical analysis, it is possible to make educated guesses about the likelihood of certain outcomes. One such tool for predicting future prices is the Price Extrapolator with Standard Deviation Cones. This custom indicator, can help you visualize potential price movements and their associated risks.
In this post, we will explain how the Price Extrapolator with Deviation Cones works, how to adjust its settings to suit your needs, and how to interpret its output. By the end of this article, you should have a better understanding of how this powerful tool can help you make more informed decisions when trading or investing in financial markets.
Understanding the Price Extrapolator with Deviation Cones
The Price Extrapolator with Deviation Cones is a custom indicator that uses historical price data to calculate the average log return and standard deviation of log returns over a specified period. It then uses this information to extrapolate a series of future price points, as well as upper and lower standard deviation bands that form the "deviation cones."
The average log return represents the expected price change, while the standard deviation of log returns provides a measure of the uncertainty or risk associated with the prediction. The deviation cones can help you visualize the range of potential price movements and assess the likelihood of different outcomes.
Configuring the Indicator
To use the Price Extrapolator with Deviation Cones, you will need to configure several input settings:
1. Length: This setting determines the number of historical data points used to calculate the average log return and standard deviation of log returns. A higher value will produce a smoother, less sensitive indicator, while a lower value will make the indicator more responsive to recent price changes.
2. Number of Future Price Points: This setting controls the number of future price points to extrapolate. Increasing this value will extend the deviation cones further into the future.
3. Multiplier: This setting adjusts the tightness of the deviation cones by controlling the standard deviation multiplier. A higher value will result in wider cones, indicating greater uncertainty, while a lower value will produce narrower cones, suggesting more confidence in the prediction.
Interpreting the Output
After configuring the indicator, you will see the following output on your chart:
1. Green Line: This line represents the extrapolated future price points based on the average log return. It provides a central estimate of potential price movements.
2. Red Lines: These lines form the upper and lower bounds of the deviation cones. They represent the range of potential price movements, taking into account the uncertainty associated with the prediction.
When using the Price Extrapolator with Deviation Cones, it is essential to remember that the output is only a prediction based on historical data and should not be taken as a guarantee of future price movements. However, by providing a visual representation of potential price movements and their associated risks, this indicator can help you make more informed decisions when trading or investing in financial markets.
The Extreme Limitations of the Price Extrapolator with Deviation Cones
While the Price Extrapolator with Deviation Cones can be a valuable addition to your trading toolbox, it is essential to recognize its limitations. As with any forecasting tool, it is not infallible and should be used in conjunction with other forms of analysis. In this section, we will discuss the extreme limitations of this indicator and provide insight into how to use it effectively despite these constraints.
1. Reliance on Historical Data
The Price Extrapolator with Deviation Cones relies heavily on historical price data to make its predictions. While this can provide valuable insights into past trends and patterns, it may not accurately predict future price movements in a constantly changing market.
Market conditions can change rapidly, and historical data may not be a reliable indicator of future performance. Economic events, geopolitical tensions, and changes in market sentiment can all influence price movements in ways that may not be captured by historical data alone.
2. Assumption of Lognormal Distribution
The indicator assumes that price returns follow a lognormal distribution, which may not always be the case. Financial markets can exhibit skewness and kurtosis, resulting in distributions that are not symmetrical or normally distributed. This can lead to inaccurate predictions and a false sense of security when relying on the deviation cones.
3. No Consideration of Fundamental Factors
The Price Extrapolator with Deviation Cones is a purely technical analysis tool, meaning it does not take into account fundamental factors that can influence price movements. Changes in company earnings, interest rates, or economic data can significantly impact asset prices and may not be factored into the indicator's predictions.
4. Limited Time Horizon
The indicator only provides predictions for a limited number of future price points, which may not be sufficient for long-term investors or traders with longer holding periods. Additionally, the accuracy of the predictions may decrease as the time horizon extends, due to the compounding effects of uncertainty and the limitations of historical data.
5. Potential for Overfitting
When adjusting the settings of the Price Extrapolator with Deviation Cones, there is a risk of overfitting the model to the historical data. This can result in an indicator that appears to have excellent predictive power on past data but performs poorly on unseen, future data. It is crucial to be cautious when optimizing the settings and use out-of-sample testing to validate the indicator's performance.
Using the Price Extrapolator with Deviation Cones Effectively
Despite these limitations, the Price Extrapolator with Deviation Cones can still be a valuable tool when used correctly. To use this indicator effectively, consider the following tips:
1. Supplement with Other Forms of Analysis: Use the Price Extrapolator with Deviation Cones alongside other technical and fundamental analysis methods to gain a more comprehensive understanding of potential price movements.
2. Diversify your Trading Strategies: Do not rely solely on the Price Extrapolator with Deviation Cones for your trading decisions. Instead, diversify your strategies and consider multiple indicators and methods to reduce the risk of overreliance on a single tool.
3. Be Cautious with Optimized Settings: When adjusting the indicator's settings, be mindful of the risk of overfitting and validate the performance with out-of-sample testing.
4. Keep an Eye on Market Conditions: Stay informed about current market conditions, economic events, and news that may impact your trading decisions. This will help you make more informed decisions when using the Price Extrapolator with Deviation Cones.
In conclusion, the Price Extrapolator with Deviation Cones is a powerful and versatile tool that can aid traders and investors in predicting potential future price movements. However, it is crucial to remember that this indicator has its limitations, which stem from its reliance on historical data, the assumption of lognormal distribution, its disregard for fundamental factors, limited time horizons, and the potential for overfitting. Despite these constraints, when used correctly and in conjunction with other forms of analysis, the Price Extrapolator with Deviation Cones can provide valuable insights and assist in making more informed trading and investing decisions.
By understanding the underlying mechanics of the indicator, adjusting its settings according to your needs, and being aware of its limitations, you can incorporate the Price Extrapolator with Deviation Cones into your trading arsenal effectively. Always remember that no single tool or indicator is infallible, and it is essential to use a diverse range of analysis methods and strategies to navigate the ever-changing financial markets successfully. Happy trading!
SuperTrend with Chebyshev FilterModified Super Trend with Chebyshev Filter
The Modified Super Trend is an innovative take on the classic Super Trend indicator. This advanced version incorporates a Chebyshev filter, which significantly enhances its capabilities by reducing false signals and improving overall signal quality. In this post, we'll dive deep into the Modified Super Trend, exploring its history, the benefits of the Chebyshev filter, and how it effectively addresses the challenges associated with smoothing, delay, and noise.
History of the Super Trend
The Super Trend indicator, developed by Olivier Seban, has been a popular tool among traders since its inception. It helps traders identify market trends and potential entry and exit points. The Super Trend uses average true range (ATR) and a multiplier to create a volatility-based trailing stop, providing traders with a dynamic tool that adapts to changing market conditions. However, the original Super Trend has its limitations, such as the tendency to produce false signals during periods of low volatility or sideways trading.
The Chebyshev Filter
The Chebyshev filter is a powerful mathematical tool that makes an excellent addition to the Super Trend indicator. It effectively addresses the issues of smoothing, delay, and noise associated with traditional moving averages. Chebyshev filters are named after Pafnuty Chebyshev, a renowned Russian mathematician who made significant contributions to the field of approximation theory.
The Chebyshev filter is capable of producing smoother, more responsive moving averages without introducing additional lag. This is possible because the filter minimizes the worst-case error between the ideal and the actual frequency response. There are two types of Chebyshev filters: Type I and Type II. Type I Chebyshev filters are designed to have an equiripple response in the passband, while Type II Chebyshev filters have an equiripple response in the stopband. The Modified Super Trend allows users to choose between these two types based on their preferences.
Overcoming the Challenges
The Modified Super Trend addresses several challenges associated with the original Super Trend:
Smoothing: The Chebyshev filter produces a smoother moving average without introducing additional lag. This feature is particularly beneficial during periods of low volatility or sideways trading, as it reduces the number of false signals.
Delay: The Chebyshev filter helps minimize the delay between price action and the generated signal, allowing traders to make timely decisions based on more accurate information.
Noise Reduction: The Chebyshev filter's ability to minimize the worst-case error between the ideal and actual frequency response reduces the impact of noise on the generated signals. This feature is especially useful when using the true range as an offset for the price, as it helps generate more reliable signals within a reasonable time frame.
The Great Replacement
The Modified Super Trend with Chebyshev filter is an excellent replacement for the original Super Trend indicator. It offers significant improvements in terms of signal quality, responsiveness, and accuracy. By incorporating the Chebyshev filter, the Modified Super Trend effectively reduces the number of false signals during low volatility or sideways trading, making it a more reliable tool for identifying market trends and potential entry and exit points.
In-Depth Guide to the Modified Super Trend Settings
The Modified Super Trend with Chebyshev filter offers a wide range of settings that allow traders to fine-tune the indicator to suit their specific trading styles and objectives. In this section, we will discuss each setting in detail, explaining its purpose and how to use it effectively.
Source
The source setting determines the price data used for calculations. The default setting is hl2, which calculates the average of the high and low prices. You can choose other price data sources such as close, open, or ohlc4 (average of open, high, low, and close prices) based on your preference.
Up Color and Down Color
These settings control the color of the trend line when the market is in an uptrend (up_color) and a downtrend (down_color). You can customize these colors to your liking, making it easier to visually identify the current market trend.
Text Color
This setting controls the color of the text displayed on the chart when using labels to indicate trend changes. You can choose any color that contrasts well with your chart background for better readability.
Mean Length
The mean_length setting determines the length (number of bars) used for the Chebyshev moving average calculation. A shorter length will make the moving average more responsive to price changes, while a longer length will produce a smoother moving average. It is crucial to find the right balance between responsiveness and smoothness, as a too-short length may generate false signals, while a too-long length might produce lagging signals. The default value is 64, but you can experiment with different values to find the optimal setting for your trading strategy.
Mean Ripple
The mean_ripple setting influences the Chebyshev filter's ripple effect in the passband (Type I) or stopband (Type II). The ripple effect represents small oscillations in the frequency response, which can impact the moving average's smoothness. The default value is 0.01, but you can experiment with different values to find the best balance between smoothness and responsiveness.
Chebyshev Type: Type I or Type II
The style setting allows you to choose between Type I and Type II Chebyshev filters. Type I filters have an equiripple response in the passband, while Type II filters have an equiripple response in the stopband. Depending on your preference for smoothness and responsiveness, you can choose the type that best fits your trading style.
ATR Style
The atr_style setting determines the method used for calculating the Average True Range (ATR). By default (false), it uses the traditional high-low range. When set to true, it uses the absolute difference between the open and close prices. You can choose the method that works best for your trading strategy and the market you are trading.
ATR Length
The atr_length setting controls the length (number of bars) used for calculating the ATR. Similar to the mean_length, a shorter length will make the ATR more responsive to price changes, while a longer length will produce a smoother ATR. The default value is 64, but you can experiment with different values to find the optimal setting for your trading strategy.
ATR Ripple
The atr_ripple setting, like the mean_ripple, influences the ripple effect of the Chebyshev filter used in the ATR calculation. The default value is 0.05, but you can experiment with different values to find the best balance between smoothness and responsiveness.
Multiplier
The multiplier setting determines the factor by which the ATR is multiplied before being added
Super Trend Logic and Signal Optimization
The Modified Super Trend with Chebyshev filter is designed to minimize false signals and provide a clear indication of market trends. It does so by using a combination of moving averages, Average True Range (ATR), and a multiplier. In this section, we will discuss the Super Trend's logic, its ability to prevent false signals, and the early warning crosses added to the indicator.
Super Trend Logic
The Super Trend's logic is based on a combination of the Chebyshev moving average and ATR. The Chebyshev moving average is a smooth moving average that effectively filters out market noise, while the ATR is a measure of market volatility.
The Super Trend is calculated by adding or subtracting a multiple of the ATR from the Chebyshev moving average. The multiplier is a user-defined value that determines the distance between the trend line and the price action. A larger multiplier results in a wider channel, reducing the likelihood of false signals but potentially missing out on valid trend changes.
Preventing False Signals
The Super Trend is designed to minimize false signals by maintaining its trend direction until a significant change in the market occurs. In a downtrend, the trend line will only decrease in value, and in an uptrend, it will only increase. This helps prevent false signals caused by temporary price fluctuations or market noise.
When the price crosses the trend line, the Super Trend does not immediately change its direction. Instead, it employs a safety logic to ensure that the trend change is genuine. The safety logic checks if the new trend line (calculated using the updated moving average and ATR) is more extreme than the previous one. If it is, the trend line is updated; otherwise, the previous trend line is maintained. This mechanism further reduces the likelihood of false signals by ensuring that the trend line only changes when there is a significant shift in the market.
Early Warning Crosses
To provide traders with additional insight, the Modified Super Trend with Chebyshev filter includes early warning crosses. These crosses are plotted on the chart when the price crosses the trend line without the safety logic. Although these crosses do not necessarily indicate a trend change, they can serve as a valuable heads-up for traders to monitor the market closely and prepare for potential trend reversals.
In conclusion, the Modified Super Trend with Chebyshev filter offers a significant improvement over the original Super Trend indicator. By incorporating the Chebyshev filter, this modified version effectively addresses the challenges of smoothing, delay, and noise reduction while minimizing false signals. The wide range of customizable settings allows traders to tailor the indicator to their specific needs, while the inclusion of early warning crosses provides valuable insight into potential trend reversals.
Ultimately, the Modified Super Trend with Chebyshev filter is an excellent tool for traders looking to enhance their trend identification and decision-making abilities. With its advanced features, this indicator can help traders navigate volatile markets with confidence, making more informed decisions based on accurate, timely information.
Probability Envelopes (PBE)Introduction
In the world of trading, technical analysis is vital for making informed decisions about the future direction of an asset's price. One such tool is the use of indicators, mathematical calculations that can help traders predict market trends. This article delves into an innovative indicator called the Probability Envelopes Indicator, which offers valuable insights into the potential price levels an asset may reach based on historical data. This in-depth look explores the statistical foundations of the indicator, highlighting its key components and benefits.
Section 1: Calculating Price Movements with Log Returns and Percentages
The Probability Envelopes Indicator provides the option to use either log returns or percentage changes when calculating price movements. Each method has its advantages:
Log Returns: These are calculated as the natural logarithm of the ratio of the current price to the previous price. Log returns are considered more stable and less sensitive to extreme price fluctuations.
Percentage Changes: These are calculated as the percentage difference between the current price and the previous price. They are simpler to interpret and easier to understand for most traders.
Section 2: Understanding Mean, Variance, and Standard Deviation
The Probability Envelopes Indicator utilizes various statistical measures to analyze historical price movements:
Mean: This is the average of a set of numbers. In the context of this indicator, it represents the average price movement for bullish (green) and bearish (red) scenarios.
Variance: This measure represents the dispersion of data points in a dataset. A higher variance indicates a greater spread of data points from the mean. Variance is calculated as the average of the squared differences from the mean.
Standard Deviation: This is the square root of the variance. It is a measure of the amount of variation or dispersion in a dataset. In the context of this indicator, standard deviations are used to calculate the width of the bands around the expected mean.
Section 3: Analyzing Historical Price Movements and Probabilities
The Probability Envelopes Indicator examines historical price movements and calculates probabilities based on their frequency:
The indicator first identifies and categorizes price movements into bullish (green) and bearish (red) scenarios.
It then calculates the probability of each price movement occurring by dividing the frequency of the movement by the total number of occurrences in each category (bullish or bearish).
The expected green and red movements are calculated by multiplying the probabilities by their respective price movements and summing the results.
The total expected movement, or weighted average, is calculated by combining the expected green and red movements and dividing by the total number of occurrences.
Section 4: Constructing the Probability Envelopes
The Probability Envelopes Indicator utilizes the calculated statistics to construct its bands:
The expected mean is calculated using the total expected movement and applied to the current open price.
An exponential moving average (EMA) is used to smooth the expected mean, with the smoothing length determining the degree of responsiveness.
The upper and lower bands are calculated by adding and subtracting the mean green and red movements, respectively, along with their standard deviations multiplied by a user-defined multiplier.
Section 5: Benefits of the Probability Envelopes Indicator
The Probability Envelopes Indicator offers numerous advantages to traders:
Enhanced Decision-Making: By providing probability-based estimations of future price levels, the indicator can help traders make more informed decisions and potentially improve their trading strategies.
Versatility: The indicator is applicable to various financial instruments, such as stocks, forex, commodities, and cryptocurrencies, making it a valuable tool for traders in different markets.
Customization: The indicator's parameters, including the use of log returns, multiplier values, and smoothing length, can be adjusted according to the user's preferences and trading style. This flexibility allows traders to fine-tune the Probability Envelopes Indicator to better suit their needs and goals.
Risk Management: The Probability Envelopes Indicator can be used as a component of a risk management strategy by providing insight into potential price movements. By identifying potential areas of support and resistance, traders can set stop-loss and take-profit levels more effectively.
Visualization: The graphical representation of the indicator, with its clear upper and lower bands, makes it easy for traders to quickly assess the market and potential price levels.
Section 6: Integrating the Probability Envelopes Indicator into Your Trading Strategy
When incorporating the Probability Envelopes Indicator into your trading strategy, consider the following tips:
Confirmation Signals: Use the indicator in conjunction with other technical analysis tools, such as trend lines, moving averages, or oscillators, to confirm the strength and direction of the market trend.
Timeframes: Experiment with different timeframes to find the optimal settings for your trading strategy. Keep in mind that shorter timeframes may generate more frequent signals but may also increase the likelihood of false signals.
Risk Management: Always establish a proper risk management strategy that includes setting stop-loss and take-profit levels, as well as managing your position sizes.
Backtesting: Test the Probability Envelopes Indicator on historical data to evaluate its effectiveness and fine-tune its parameters to optimize your trading strategy.
Section 7: Cons and Limitations of the Probability Envelopes Indicator
While the Probability Envelopes Indicator offers several advantages to traders, it is essential to be aware of its potential cons and limitations. Understanding these can help you make better-informed decisions when incorporating the indicator into your trading strategy.
Lagging Nature: The Probability Envelopes Indicator is primarily based on historical data and price movements. As a result, it may be less responsive to real-time changes in market conditions, and the predicted price levels may not always accurately reflect the market's current state. This lagging nature can lead to late entry and exit signals.
False Signals: As with any technical analysis tool, the Probability Envelopes Indicator can generate false signals. These occur when the indicator suggests a potential price movement, but the market does not follow through. It is crucial to use other technical analysis tools to confirm the signals and minimize the impact of false signals on your trading decisions.
Complex Statistical Concepts: The Probability Envelopes Indicator relies on complex statistical concepts and calculations, which may be challenging to grasp for some traders, particularly beginners. This complexity can lead to misunderstandings and misuse of the indicator if not adequately understood.
Overemphasis on Past Data: While historical data can be informative, relying too heavily on past performance to predict future movements can be limiting. Market conditions can change rapidly, and relying solely on past data may not provide an accurate representation of the current market environment.
No Guarantees: The Probability Envelopes Indicator, like all technical analysis tools, cannot guarantee success. It is essential to approach trading with realistic expectations and understand that no indicator or strategy can provide foolproof results.
To overcome these limitations, it is crucial to combine the Probability Envelopes Indicator with other technical analysis tools and utilize a comprehensive risk management strategy. By doing so, you can better understand the market and increase your chances of success in the ever-changing financial markets.
Section 8: Probability Envelopes Indicator vs. Bollinger Bands
Bollinger Bands and the Probability Envelopes Indicator are both technical analysis tools designed to identify potential support and resistance levels, as well as potential trend reversals. However, they differ in their underlying concepts, calculations, and applications. This section will provide a deep dive into the differences between these two indicators and how they can complement each other in a trading strategy.
Underlying Concepts and Calculations:
Bollinger Bands:
Bollinger Bands are based on a simple moving average (SMA) of the price data, with upper and lower bands plotted at a specified number of standard deviations away from the SMA.
The distance between the bands widens during periods of increased price volatility and narrows during periods of low volatility, indicating potential trend reversals or breakouts.
The standard settings for Bollinger Bands typically involve a 20-period SMA and a 2 standard deviation distance for the upper and lower bands.
Probability Envelopes Indicator:
The Probability Envelopes Indicator calculates the expected price movements based on historical data and probabilities, utilizing mean and standard deviation calculations for both upward and downward price movements.
It generates upper and lower bands based on the calculated expected mean movement and the standard deviation of historical price changes, multiplied by a user-defined multiplier.
The Probability Envelopes Indicator also allows users to choose between using log returns or percentage changes for the calculations, adding flexibility to the indicator.
Key Differences:
Calculation Method: Bollinger Bands are based on a simple moving average and standard deviations, while the Probability Envelopes Indicator uses statistical probability calculations derived from historical price changes.
Flexibility: The Probability Envelopes Indicator allows users to choose between log returns or percentage changes and adjust the multiplier, offering more customization options compared to Bollinger Bands.
Risk Management: Bollinger Bands primarily focus on volatility, while the Probability Envelopes Indicator incorporates probability calculations to provide additional insights into potential price movements, which can be helpful for risk management purposes.
Complementary Use:
Using both Bollinger Bands and the Probability Envelopes Indicator in your trading strategy can offer valuable insights into market conditions and potential price levels.
Bollinger Bands can provide insights into market volatility and potential breakouts or trend reversals based on the widening or narrowing of the bands.
The Probability Envelopes Indicator can offer additional information on the expected price movements based on historical data and probabilities, which can be helpful in anticipating potential support and resistance levels.
Combining these two indicators can help traders to better understand market dynamics and increase their chances of identifying profitable trading opportunities.
In conclusion, while both Bollinger Bands and the Probability Envelopes Indicator aim to identify potential support and resistance levels, they differ significantly in their underlying concepts, calculations, and applications. By understanding these differences and incorporating both tools into your trading strategy, you can gain a more comprehensive understanding of the market and make more informed trading decisions.
In conclusion, the Probability Envelopes Indicator is a powerful and versatile technical analysis tool that offers unique insights into expected price movements based on historical data and probability calculations. It provides traders with the ability to identify potential support and resistance levels, as well as potential trend reversals. When compared to Bollinger Bands, the Probability Envelopes Indicator offers more customization options and incorporates probability-based calculations for a different perspective on market dynamics.
Although the Probability Envelopes Indicator has its limitations and potential cons, such as the reliance on historical data and the assumption that past performance is indicative of future results, it remains a valuable addition to any trader's toolkit. By using the Probability Envelopes Indicator in conjunction with other technical analysis tools, such as Bollinger Bands, traders can gain a more comprehensive understanding of the market and make more informed trading decisions.
Ultimately, the success of any trading strategy relies on the ability to interpret and apply multiple indicators effectively. The Probability Envelopes Indicator serves as a unique and valuable tool in this regard, providing traders with a deeper understanding of the market and its potential price movements. By utilizing this indicator in combination with other tools and techniques, traders can increase their chances of success and optimize their trading strategies.
