ATR Based Stoploss - TakeProfit [CharmyDexter]
This script combines the power of Average True Range (ATR) and a Moving Average (MA) to dynamically set stop-loss and take-profit levels. It introduces a volatility surge condition and includes a risk management table for comprehensive trade insights.
1) **Originality:**
- This script is original in its approach to combining Average True Range (ATR) with a Moving Average (MA) to create a dynamic stop-loss and take-profit strategy. The addition of a volatility surge condition and the inclusion of a risk management table further contribute to its uniqueness.
2) **Functionality:**
- The script aims to provide traders with a dynamic stop-loss and take-profit strategy based on ATR, incorporating a volatility surge condition and a moving average. The risk management table displays crucial information, including the fund size, potential profit/loss, ATR values, and risk.
3) **Operation:**
- The script uses ATR to calculate volatility, identifying surges in volatility. It adjusts the stop-loss and take-profit levels based on the average of ATR during these surge periods. The moving average acts as a trend indicator, and the script dynamically adjusts stop-loss and take-profit levels accordingly.
4) **Usage:**
- Traders can use this script by applying it to their preferred financial instrument's chart. The script automatically plots the moving average and dynamically adjusts stop-loss and take-profit levels based on ATR and volatility surges. Users can observe the levels on the chart for potential trade management.
5) **Concepts:**
- The script employs concepts of ATR for volatility, moving average for trend identification, and a dynamic adjustment mechanism during volatility surges. Risk management is incorporated by calculating potential profit/loss percentages based on user-defined risk.
6) **Mashup Explanation:**
- The script combines ATR, moving average, and volatility conditions to create a comprehensive strategy. ATR determines the market's volatility, the moving average serves as a trend indicator, and volatility surges trigger dynamic adjustments to stop-loss and take-profit levels. The risk management table enhances the script's utility.
7) **Line Descriptions:**
- Blue Line (Moving Average): Indicates the trend direction.
- Lime Line (Long Take Profit): Represents the level for taking profit in a long position.
- Maroon Line (Short Take Profit): Represents the level for taking profit in a short position.
- Fuchsia Line (Short Stop Loss): Represents the level for setting a stop loss in a short position.
- Orange Line (Long Stop Loss): Represents the level for setting a stop loss in a long position.
8) **Line Usage:**
- Use the blue line for trend identification.
- When taking long positions, the close should be above the blue line.
- For long positions, the lime line is a potential take-profit level, and the orange line is a potential stop-loss level.
- For short positions, the maroon line is a potential take-profit level, and the fuchsia line is a potential stop-loss level.
- The risk management table provides insights into fund size, potential profit/loss, ATR values, and risk.
Note: The profit/loss calculations in this script may not be entirely accurate due to factors like market execution. Market execution may not always occur at the exact levels specified by the script due to slippage or delays in order processing. This can impact the realized profit or loss compared to the calculated levels.
It is crucial to note that this ATR Based Stop-loss - Take-Profit indicator is merely one tool among many that traders can employ to establish trading targets. Additional technical indicators are essential for taking trades and making informed decisions.
Commented-out sections for alerts and shape plotting are provided, allowing for visual and auditory notifications if desired.
It's crucial for traders to be aware of these factors and use the script as a tool within a broader trading strategy. Additionally, regular monitoring and adjustments based on real-time market conditions are recommended to enhance the accuracy of profit/loss assessments.
ATR
Anchored Chandelier ExitThe Chandelier Exit is a popular tool among traders used to help determine appropriate stop loss levels. Originally developed by Chuck LeBeau, the Chandelier Exit takes into account market volatility and adjusts the stop loss level dynamically. This indicator builds upon the original Chandelier Exit by allowing the trader to select an anchor date or starting point for the indicator to begin calculating from.
The Original Chandelier Exit
Before we get into the details of the Anchored Chandelier Exit, let's review the original. Essentially a dynamic ATR stop loss, the Chandelier Exit provides a trailing stop that moves higher or lower based on volatility.
The Chandelier Exit is calculated based on the following criteria:
🔶ATR - The ATR is used to measure the volatility of a security over a lookback period. The ATR length determines the number of bars to consider when calculating the average true range. The shorter the length, the more responsive the level will be.
🔶ATR Multiplier - The default multiplier is set to 3. This is used to determine the sensitivity of the Chandelier Exit. The higher the ATR multiplier the wider the stop levels will be. A lower multiplier will tighten stop levels.
🔶Highest / Lowest Points - Determine the highest high (bullish trade) or lowest low (bearish trade) during the lookback period. The default length is 22 bars.
Calculating the Chandelier Exit
Bullish trades - Highest High - ATR * Multiplier
Bearish trades - Lowest Low + ATR * Multiplier
The Anchored Chandelier Exit
The Anchored Chandelier Exit is a new twist on the original, allowing traders to adapt their stop loss levels based on specific market events, levels or bars.
Similar to the original, traders can select the ATR length and multiplier, however, the high or low from which the ATR is subtracted or added is first determined at the anchor bar.
As new bars form, the indicator checks for the previous high/low to be breached. If the high or low is exceeded, the highest/lowest point is updated and the Chandelier Exit is recalculated.
When the indicator is first loaded to your chart, it will ask you to select an anchor bar and choose the bias for the trade.
A bullish (long) bias trade will plot the Chandelier Exit below price action, while a bearish (short) bias trade will plot the Chandelier Exit above price action.
Indicator Features
🔶Custom Start Date
🔶Bullish or Bearish Bias
🔶Selectable ATR Length & Multiplier
🔶Custom Colors
🔶Exit With Close or Wicks
🔶Exit Alerts
With careful parameter optimization, the Anchored Chandelier Exit can be a useful tool for helping traders manage risk based on market volatility.
SuperTrend ToolkitThe SuperTrend Toolkit (Super Kit) introduces a versatile approach to trend analysis by extending the application of the SuperTrend indicator to a wide array of @TradingView's built-in or Community Scripts . This tool facilitates the integration of the SuperTrend algorithm with various indicators, including oscillators, moving averages, overlays, and channels.
Methodology:
The SuperTrend, at its core, calculates a trend-following indicator based on the Average-True-Range (ATR) and price action. It creates dynamic support and resistance levels, adjusting to changing market conditions, and aiding in trend identification.
pine_st(simple float factor = 3., simple int length = 10) =>
float atr = ta.atr(length)
float up = hl2 + factor * atr
up := up < nz(up ) or close > nz(up ) ? up : nz(up )
float lo = hl2 - factor * atr
lo := lo > nz(lo ) or close < nz(lo ) ? lo : nz(lo )
int dir = na
float st = na
if na(atr )
dir := 1
else if st == nz(up )
dir := close > up ? -1 : 1
else
dir := close < lo ? 1 : -1
st := dir == -1 ? lo : up
@TradingView's native SuperTrend lacks the flexibility to incorporate different price sources into its calculation.
Community scripts, addressed the limitation by implementing the option to input different price sources, for example, one of the most popular publications, @KivancOzbilgic's SuperTrend script.
In May 2023, @TradingView introduced an update allowing the passing of another indicator's plot as a source value via the input.source() function. However, the built-in ta.atr function still relied on the chart's price data, limiting the formerly mentioned scripts to the chart's price data alone.
Unique Approach -
This script addresses the aforementioned limitations by processing the data differently.
Firstly we create a User-Defined-Type (UDT) replicating a bar's open, high, low, close (OHLC) values.
type bar
float o = open
float h = high
float l = low
float c = close
We then use this type to store the external input data.
src = input.source(close, "External Source")
bar b = bar.new(
nz(src ) , open 𝘷𝘢𝘭𝘶𝘦
math.max(nz(src ), src), high 𝘷𝘢𝘭𝘶𝘦
math.min(nz(src ), src), low 𝘷𝘢𝘭𝘶𝘦
src ) close 𝘷𝘢𝘭𝘶𝘦
Finally, we pass the data into our custom built SuperTrend with ATR functions to derive the external source's version of the SuperTrend indicator.
supertrend st = b.st(mlt, len)
- Setup Guide -
Utility and Use Cases:
Universal Compatibility - Apply SuperTrend to any built-in indicator or script, expanding its use beyond traditional price data.
- A simple example on one of my own public scripts -
Trend Analysis - Gain additional trend insights into otherwise mainly mean reverting or volume indicators.
- Alerts Setup Guide -
The Super Kit empowers traders and analysts with a tool that adapts the robust SuperTrend algorithm to a myriad of indicators, allowing comprehensive trend analysis and strategy development.
Logical Trading Indicator V.1Features of the Logical Trading Indicator V.1
ATR-Based Trailing Stop Loss
The Logical Trading Indicator V.1 utilizes the Average True Range (ATR) to implement a dynamic trailing stop loss. You can customize the sensitivity of your alerts by adjusting the ATR Multiple and ATR Period settings.
Higher ATR Multiple values create wider stops, while lower values result in tighter stops. This feature ensures that your trades are protected against adverse price movements. For best practice, use higher values on higher timeframes and lower values on lower term timeframes.
Bollinger Bands
The Logical Trading Indicator V.1 includes Bollinger Bands, which can be customized to use either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as the basis.
You can adjust the length and standard deviation multiplier of the Bollinger Bands to fine-tune your strategy. The color of the basis line changes to green when price is above and red when price is below the line to represent the trend.
The bands show a range vs a single band that also represents when the price is in overbought and oversold ranges similar to an RSI. These bands also control the take profit signals.
You also have the ability to change the band colors as well as toggle them off, which only affects the view, they are still active which will still fire the take profit signals.
Momentum Indicator
Our indicator offers a momentum filter option that highlights market momentum directly on the candlesticks, identifying periods of bullish, bearish, or consolidation phases. You can enable or disable this filter as needed, providing valuable insights into market conditions.
By default, you will see the candlestick colors represent the momentum direction as green or red, and consolidation periods as white, but the filter on the BUY and SELL signals is not active. The view options and filter can be toggled on and off in the settings.
Buy and Sell Signals
The Logical Trading Indicator V.1 generates buy and sell signals based on a combination of ATR-based filtering, Bollinger Band basis crossover, and optional momentum conditions if selected in the settings. These signals help you make informed decisions about when to enter or exit a trade. You can also enable a consolidation filter to stay out of trades during tight ranges.
Basically a BUY signal fires when the price closes above the basis line, and the price meets or exceeds the ATR multiple from the previous candle length, which is also editable in the settings.
If the momentum filter is engaged, it will not fire BUY signals when in consolidation periods. It works just the opposite for SELL signals.
Take Profit Signals
We've integrated a Take Profit feature that helps you identify points to exit your trades with profits. The indicator marks Long Take Profit when prices close below the upper zone line of the Bollinger Bands after the previous candle closes inside the band, suggesting an optimal point to exit a long trade or consider a short position.
Conversely, Short Take Profit signals appear when prices close above the lower zone after the previous candle closes inside of it, indicating the right time to exit a short trade or contemplate a long position.
Alerts for Informed Trading
The Logical Trading Indicator V.1 comes equipped with alert conditions for buy signals, sell signals, take profit points, and more. Receive real-time notifications to your preferred devices or platforms to stay updated on market movements and trading opportunities.
Standardized SuperTrend Oscillator
The Standardized SuperTrend Oscillator (SSO) is a versatile tool that transforms the SuperTrend indicator into an oscillator, offering both trend-following and mean reversion capabilities. It provides deeper insights into trends by standardizing the SuperTrend with respect to its upper and lower bounds, allowing traders to identify potential reversals and contrarian signals.
Methodology:
Lets begin with describing the SuperTrend indicator, which is the fundamental tool this script is based on.
SuperTrend:
The SuperTrend is calculated based on the average true range (ATR) and multiplier. It identifies the trend direction by placing a line above or below the price. In an uptrend, the line is below the price; in a downtrend, it's above the price.
pine_st(float src = hl2, float factor = 3., simple int len = 10) =>
float atr = ta.atr(len)
float up = src + factor * atr
up := up < nz(up ) or close > nz(up ) ? up : nz(up )
float lo = src - factor * atr
lo := lo > nz(lo ) or close < nz(lo ) ? lo : nz(lo )
int dir = na
float st = na
if na(atr )
dir := 1
else if st == nz(up )
dir := close > up ? -1 : 1
else
dir := close < lo ? 1 : -1
st := dir == -1 ? lo : up
SSO Oscillator:
The SSO is derived from the SuperTrend and the source price. It calculates the standardized difference between the SuperTrend and the source price. The standardization is achieved by dividing this difference by the distance between the upper and lower bounds of the SuperTrend.
float sso = (src - st) / (up - lo)
Components and Features:
SuperTrend of Oscillator - An additional SuperTrend based on the direction and volatility of the oscillator, behaving as the SuperTrend OF the SuperTrend. This provides further trend analysis of the underlying broad trend regime.
Reversion Tracer - The RSI of the direction of the original SuperTrend, providing a dynamic threshold for premium and discount price areas.
float rvt = ta.rsi(dir, len)
Heikin Ashi Transform - An option to apply the Heikin Ashi transform to the source price of the oscillator, providing a smoother visual representation of trends.
Display Modes - Choose between Line mode for a standard oscillator view or Candle mode, displaying the oscillator as Heikin Ashi candles for more in-depth trend analysis.
Contrarian and Reversion Signals:
Contrarian Signals - Based on the SuperTrend of the oscillator, these signals can act as potential buy or sell indications, highlighting potential trend exhaustion or premature reversals.
Reversion Signals - Generated when the oscillator crosses above or below the Reversion Tracer, signaling potential mean reversion opportunities or trend breakouts.
Utility and Use Cases:
Trend Analysis - Utilize the SSO as a trend-following tool with the added benefits of the oscillator's SuperTrend and Heikin Ashi transform.
Valuation Analysis - Leverage the oscillator's reversion signals for identifying potential mean reversion opportunities in the market.
The Standardized SuperTrend Oscillator enhances the capabilities of the SuperTrend indicator, offering a balanced approach to both trend-following and mean reversion strategies. Its customizable options and contrarian signals make it a valuable instrument for traders seeking comprehensive trend analysis and potential reversal signals.
ATR SpikeALWAYS TRADE THE DIRECTION OF THE TREND
This indicator is useful for 5-minute Bank Nifty intraday trading.
It compares the Open-Close value for a 5-minute bar with the current ATR value.
When a bar has higher than the ATR value then it means that the current bar has a higher Open-Close than the ATR.
This means that after a period of dull action, some action has taken place.
And more action will follow in the direction of the immediate trend.
It signals the start of momentum which I look for as a intraday trader.
Feel free to experiment and change values as it suits you.
I use it on Bank Nifty only on 5 minute timeframe with 14 period ATR.
[Spinn] Average True RangeThe "Average True Range" indicator is a popular tool that measures price volatility. In this modified indicator, I present two methods of calculating ATR: the outdated classical one based on RMA (EMA, SMA, WMA), and the modernized one using the Super Smoother filter.
Why has exponential smoothing become outdated?
Exponential smoothing (EMA) has drawbacks, especially when it comes to identifying cyclical components in the data (and RMA is a variant of EMA). EMA creates phase shifts and distortions, making it less predictable and accurate in tracking real price movements. Modern filters, such as Super Smoother, offer a higher degree of adaptability and precision while ensuring significantly less lag, better smoothness, and superior cycle detection.
Why use more contemporary filters like Super Smoother?
The Super Smoother filter combines exponential smoothing and trigonometric functions for more accurate and smooth tracking of price movements. This filter enhances cycle tracking and reduces the lag often found when using EMA. As a result, signals based on Super Smoother are often more precise and representative of real price movements.
Drawbacks of other smoothing filters commonly used with ATR:
SMA. The lag is (N-1)/2, where N = period. This is terrible.
WMA. According to John F. Ehlers, "It appears that the WMA was invented by a trader who did not have a firm grasp of filter theory in hopes of reducing lag". It has been proven that WMA has worse suppression than the equivalent SMA, and WMA has more delay in the passband than the equivalent EMA. In short, WMA has drawbacks but no advantages compared to other popular moving averages.
It is also a good idea to use the median to average the results.
Test, experiment, use!
ATR Adaptive RSI OscillatorThe " ATR Adaptive RSI Oscillator " is a versatile technical analysis tool designed to help traders make informed decisions in dynamic market conditions. It combines the Relative Strength Index (RSI) with the Average True Range (ATR) to provide adaptive and responsive insights into price trends.
Key Features :
Adaptive RSI Periods : The indicator introduces the concept of adaptive RSI periods based on the ATR (Average True Range) of the market. When enabled, it dynamically adjusts the RSI calculation period, offering longer periods during high volatility and shorter periods during low volatility. This adaptability enhances the accuracy of RSI signals across varying market conditions.
Volume-Based Smoothing : The indicator includes a smoothing feature that computes a time-decayed weighted moving average of RSI values over the last two bars, using volume-based weights. This approach offers a time-sensitive smoothing effect, reducing noise for a clearer view of trend strength compared to the standard RSI.
Divergence Detection : Traders can enable divergence detection to identify potential reversal points in the market. The indicator highlights regular bullish and bearish divergences, providing valuable insights into market sentiment shifts.
Customizable Parameters : Traders have the flexibility to customize various parameters, including RSI length, adaptive mode, ATR length, and divergence settings, to tailor the indicator to their trading strategy.
Overbought and Oversold Levels : The indicator includes overbought (OB) and oversold (OS) boundary lines that can be adjusted to suit individual preferences. These levels help traders identify potential reversal zones.
The "ATR Adaptive RSI Oscillator" is a powerful tool for traders seeking to adapt their trading strategies to changing market dynamics. Whether you're a trend follower or a contrarian trader, this indicator provides valuable insights to support your decision-making process.
TTP SuperTrend ADXThis indicator uses the strength of the trend from ADX to decide how the SuperTrend (ST) should behave.
Motivation
ST is a great trend following indicator but it's not capable of adapting to the trend strength.
The ADX, Average Directional Index measures the strength of the trend and can be use to dynamically tweak the ST factor so that it's sensitivity can adapt to the trend strength.
Implementation
The indicator calculates a normalised value of the ADX based on the data available in the chart.
Based on these values ST will use different factors to increase or reduce the factor use by ST: expansion or compression.
ST expansion vs compression
Expanding the ST would mean that the stronger a trends get the ST factor will grow causing it to distance further from the price delaying the next ST trend flip.
Compressing the ST would mean that the stronger a trends get the ST factor will shrink causing it to get closer to the price speeding up the next ST trend flip.
Features
- Alerts for trend flip
- Alerts for trend status
- Backtestable stream
- SuperTrend color gets more intense with the strength of the trend
Advanced Weighted Residual Arbitrage AnalyzerThe Advanced Weighted Residual Arbitrage Analyzer is a sophisticated tool designed for traders aiming to exploit price deviations between various asset pairs. By examining the differences in normalized price relations and their weighted residuals, this indicator provides insights into potential arbitrage opportunities in the market.
Key Features:
Multiple Relation Analysis: Analyze up to five different asset relations simultaneously, offering a comprehensive view of potential arbitrage setups.
Normalization Functions: Choose from a variety of normalization techniques like SMA, EMA, WMA, and HMA to ensure accurate comparisons between different price series.
Dynamic Weighting: Residuals are weighted based on their correlation, ensuring that stronger correlations have a more pronounced impact on the analysis. Weighting can be adjusted using several functions including square, sigmoid, and logistic.
Regression Flexibility: Incorporate linear, polynomial, or robust regression to calculate residuals, tailoring the analysis to different market conditions.
Customizable Display: Decide which plots to display for clarity and focus, including normalized relations, weighted residuals, and the difference between the screen relation and the average weighted residual.
Usage Guidelines:
Configure the asset pairs you wish to analyze using the Symbol Relations group in the settings.
Adjust the normalization, volatility, regression, and weighting functions based on your preference and the specific characteristics of the asset pairs.
Monitor the weighted residuals for deviations from the mean. Larger deviations suggest stronger arbitrage opportunities.
Use the difference plot (between the screen relation and average weighted residual) as a quick visual cue for potential trade setups. When this plot deviates significantly from zero, it indicates a possible arbitrage opportunity.
Regularly update and adjust the parameters to account for changing market conditions and ensure the most accurate analysis.
In the Advanced Weighted Residual Arbitrage Analyzer , the value set in Alert Threshold plays a crucial role in delineating a normalized band. This band serves as a guide to identify significant deviations and potential trading opportunities.
When we observe the plots of the green line and the purple line, the Alert Threshold provides a boundary for these plots. The following points explain the significance:
Breach of the Band: When either the green or purple line crosses above or below the Alert Threshold , it indicates a significant deviation from the mean. This breach can be interpreted as a potential trading signal, suggesting a possible arbitrage opportunity.
Convergence to the Mean: If the green line converges with the purple line , it denotes that the price relation has reverted to its mean. This convergence typically suggests that the arbitrage opportunity has been exhausted, and the market dynamics are returning to equilibrium.
Trade Execution: A trader can consider entering a trade when the lines breach the Alert Threshold . The return of the green line to align closely with the purple line can be seen as a signal to exit the trade, capitalizing on the reversion to the mean.
By monitoring these plots in conjunction with the Alert Threshold , traders can gain insights into market imbalances and exploit potential arbitrage opportunities. The convergence and divergence of these lines, relative to the normalized band, serve as valuable visual cues for trade initiation and termination.
When you're analyzing relations between two symbols (for instance, BINANCE:SANDUSDT/BINANCE:NEARUSDT ), you're essentially looking at the price relationship between the two underlying assets. This relationship provides insights into potential imbalances between the assets, which arbitrage traders can exploit.
Breach of the Lower Band: If the purple line touches or crosses below the lower Alert Threshold , it indicates that the first symbol (in our example, SANDUSDT ) is undervalued relative to the second symbol ( NEARUSDT ). In practical terms:
Action: You would consider buying the first symbol ( SANDUSDT ) and selling the second symbol ( NEARUSDT ).
Rationale: The expectation is that the price of the first symbol will rise, or the price of the second symbol will fall, or both, thereby converging back to their historical mean relationship.
Breach of the Upper Band: Conversely, if the difference plot touches or crosses above the upper Alert Threshold , it suggests that the first symbol is overvalued compared to the second. This implies:
Action: You'd consider selling the first symbol ( SANDUSDT ) and buying the second symbol ( NEARUSDT ).
Rationale: The anticipation here is that the price of the first symbol will decrease, or the price of the second will increase, or both, bringing the relationship back to its historical average.
Convergence to the Mean: As mentioned earlier, when the green line aligns closely with the purple line, it's an indication that the assets have returned to their typical price relationship. This serves as a signal for traders to consider closing out their positions, locking in the gains from the arbitrage opportunity.
It's important to note that when you're trading based on symbol relations, you're essentially betting on the relative performance of the two assets. This strategy, often referred to as "pairs trading," seeks to capitalize on price imbalances between related financial instruments. By taking opposing positions in the two symbols, traders aim to profit from the eventual reversion of the price difference to the mean.
LNL Trend SystemLNL Trend System is an ATR based day trading system specifically designed for intra-day traders and scalpers. The System works on any chart time frame & can be applied to any market. The study consist of two components - the Trend Line and the Stop Line. Trend System is based on a special ATR calculation that is achieved by combining the previous values of the 13 EMA in relation to the ATR which creates a line of deviations that visually look similar to the basic moving average but actually produce very different results ESPECIALLY in sideways market.
Trend Line:
Trend Line is a simple line which is basically a fast gauge represented by the 13 EMA that can change the color based on the current trend structure defined by multiple averages (8,13,21,34 EMAs). Trend Line is there to simply add the confluence for the current trend. Colors of the line are pretty much self-explanatory. Whenever the line turns red it states that the current structure is bearish. Vice versa for green line. Gray line represents neutral market structure.
Stop Line:
Stop Line is an ATR deviaton line with special calculation based on the previous bar ATRs and position of the price in relation to the current and previous values of 13 EMA. As already stated, this creates an ATR deviation marker either above or below the price that trails the price up or down until they touch. Whenever the price comes into the Stop Line it means it is making an ATR expansion move up or down .This touch will usually resolve into a reaction (a bounce) which provides trade opportunities.
Trend Bars:
When turned ON, Trend Bars can provide additional confulence of the current trend alongside with the Trend Line color. Trend Bars are based on the DMI and ADX indicators. Whenever the DMI is bearish and ADX is above 20 the candles paint themselfs red. And vice versa applies for the green candles and bullish DMI. Whenever the ADX falls below the 20, candles are netural (Gray) which means there is no real trend in place at the moment.
Trend Mode:
There are total of 5 different trend modes available. Each mode is visualizing different ATR settings which provides either aggressive or more conservative approach. The more tigher the mode, the more closer the distance between the price and the Stop Line. First two modes were designed for slower markets, whereas the "Loose" and "FOMC" modes are more suitable for products with high volatility.
Trend Modes:
1. Tight
Ideal for the slowest markets. Slowest market can be any market with unusually small average true range values or just simply a market that does have a personality of a "sleeper". Tight Mode can be also used for aggresive entries in the most ridiculous trends. Sometimes price will barely pullback to the Trend Line not even the Stop Line.
2. Normal
Normal Mode is the golden mean between the modes. "Normal" provides the ideal ATR lengths for the most used markets such as S&P Futures (ES) or SPY, AAPL and plenty of other highly popular stocks. More often than not, the length of this mode is respected considering there is no breaking news or high impact market event scheduled.
3. Loose
The "Loose" mode is basically a normal mode but a little bit more loose. This mode is useful whenever the ATRs jump higher than usual or during the days of highly anticipated news events. This mode is also better suited for more active markets such as NQ futures.
4. FOMC
The FOMC mode is called FOMC for a reason. This mode provides the maximum amount of wiggle room between the price and the Stop Line. This mode was designed for the extreme volatility, breaking news events or post-FOMC trading. If the market quiets down, this mode will not get the Stop Line touch as frequently as othete modes, thus it is not very useful to run this on markets with the average volatlity. Although never properly tested, perhaps the FOMC mode can find its value in the crypto market?
5. The Net
The net mode is basically a combination of all modes into one stop line system which creates "the net" effect. The Net provides the widest Stop Line zone which can be mainly appreciated by traders that like to use scale-in scale-out methods for their trading. Not to mention the visual side of the indicator which looks pretty great with the net mode on.
HTF (Higher Time Frame) Trend System:
The system also includes additional higher time frame (HTF) trend system. This can be set to any time frame by manual HTF mode. HTF mode set to "auto" will automatically choose the best suitable higher time frame trend system based on how appropriate the aggregation is. For everything below 5min the HTF Trend System will stay on 5min. Anything between 5-15min = 30min. 30min - 120min will turn on the 240min. 180min and higher will result in Daily time frame. Anything above the Daily will result in Weekly HTF aggregation, above W = Monthly, above M = Quarterly.
Background Clouds:
In terms of visualization, each trend system is fully customizable through the inputs settings. There is also an option to turn on/off the background clouds behind the stop lines. These clouds can make the charts more clean & visible.
Tips & Tricks:
1. Different Trend Modes
Try out different modes in different markets. There is no one single mode that will fit to everyone on the same type of market. I myself actually prefer more Loose than the Normal.
2. Stop Line Mirroring
Whenever the Stop Lines start to mirror each other (there is one above the price and one below) this means the price is entering a ranging sideways market. It does not matter which Stop Line will the price touch first. They can both be faded until one of them flips.
3. Signs of the Ranging Market
Watch out for signs of ranging market. Whenever the Trend System looses its colors whether on trend line or trend bars, if everything turns neutral (gray) that is usually a solid indication of a range type action for the following moments. Also as already stated before, the Stop Line mirroring is a good sign of the range market.
4. Trailing Tool, Trend System as an Additional Study?
In case you are not a fan of the colorful green / red charts & candles. You can switch all of them off and just leave the Stop Line on. This way you can use the benefits of the trend system and still use other studies on top of that. Similarly as the Parabolic SAR is often used.
5. The Flip Setup
One of my favorite trades is the Flip Setup on the 5min charts. Whenever the Stop Line is broken , the very first opposing touch after the Trend System flips is a usually a highly participated touch. If there is a strong reaction, this means this is likely a beginning of a new trend. Once I am in the position i like to trail the Stop Line on the 1min charts.
Hope it helps.
Buying Selling Volume StrategyFirst I would like to give the original credit and thanks to @ceyhun for his amazing volume script.
The way I decided to convert it into a strategy is divided into multiple types.
First, I decided in order to smooth out the values and make it more accurate to adapt the values to multiple timeframes.
After that I took the initial values from the buyers and sellers , and made a rest operation between them to have a flat difference between the power of both sides.
WIth that later on I decided to to apply a volatility filter,in this case bollinger bands, in order to find out potential leading trends.
At the same time in order to filter even more, I decided to make use as well for weekly VWAP values of the asset used.
Lastly I added a dynamic risk management into it , based on the ATR Daily values of the asset values.
As for the rules used, for example for long, I am looking that the price of the asset is above the weekly VWAP, after that I am checking that the MTF volume rest operation is both bullish and above the upper side of the bollinger.
For short we would want the asset to be below the weekly VWAP, and the volume to be bearish and above the upper side of bollinger.
The exit is either based on daily ATR values multipliers, or if we have a reverse condition.
If you have any questions, please let me know !
Magic Trend By Market Mindset - Zero To EndlessMagic Trend indicator is an indicator combining the Commodity Channel Index (CCI) and the Average True Range (ATR) indicators.
The indicator is represented by a line that turns red when CCI readings are below 0 and converts to blue when CCI reaches above 0.
Color of the line can be treated as a trend indicator.
When CCI > 0 (Blue Color), price is assumed to be in uptrend and a buying momentum could be seen.
When CCI < 0 (Red Color), price is assumed to be in downtrend and a selling pressure could be seen.
Two Multipliers of ATR have been used. Default values for multiploier are : 1.5 and 3.0
It tells about the volatality in the price and also helps in deciding Entry poits, Stop loss points and sometimes Exit points.
If trend magic lines are not straight and moving upward/downward, continuition of the trend is expected and so Holding the position is adviced.
If the farther line (line with multiplier 3.0) is broken, a trend reversal can be seen soon.
In this case, squaring off and making reverse position is adviced near the other (1.5 mult) line.
If price is revolving in between these two lines... a sideways movement is expected.
Happy Trading
Market Mindset
Auto-Length Adaptive ChannelsIntroduction
The key innovation of the ALAC is the implementation of dynamic length identification, which allows the indicator to adjust to the "market beat" or dominant cycle in real-time.
The Auto-Length Adaptive Channels (ALAC) is a flexible technical analysis tool that combines the benefits of five different approaches to market band and price deviation calculations.
Traders often tend to overthink of what length their indicators should use, and this is the main idea behind this script. It automatically calculates length based on pivot points, averaging the distance that is in between of current market highs and lows.
This approach is very helpful to identify market deviations, because deviations are always calculated and compared to previous market behavior.
How it works
The indicator uses a Detrended Rhythm Oscillator (DRO) to identify the dominant cycle in the market. This length information is then used to calculate different market bands and price deviations. The ALAC combines five different methodologies to compute these bands:
1 - Bollinger Bands
2 - Keltner Channels
3 - Envelope
4 - Average True Range Channels
5 - Donchian Channels
By averaging these calculations, the ALAC produces an overall market band that generalizes the approaches of these five methods into a single, adaptive channel.
How to Use
When the price is at the upper band, this might suggest that the asset is overbought and may be due for a price correction. Conversely, when the price is at the lower band, the asset may be oversold and due for a price increase.
The space between the bands represents the market's volatility. Wider bands indicate higher volatility, while narrower bands suggest lower volatility.
Indicator Settings
The settings of the ALAC allow for customization to suit different trading strategies:
Use Autolength?: This allows the indicator to automatically adjust the length of the dominant cycle.
Usual Length: If "Use Autolength?" is disabled, this setting allows the user to manually specify the length of the cycle.
Moving Average Type: This selects the type of moving average to be used in the calculations. Options include SMA, EMA, ALMA, DEMA, JMA, KAMA, SMMA, TMA, TSF, VMA, VAMA, VWMA, WMA, and ZLEMA.
Channel Multiplier: This adjusts the distance between the bands.
Channel Multiplier Step: This changes the step size of the channel multiplier. Each next market band will be multiplied by a previous one. You can potentially use values below 1, which will plot bands inside the first, main channel.
Use DPO instead of source data?: This setting uses the DPO for calculations instead of the source data. Basically, this is how you can add or eliminate trend from calculation of an average leg-up / leg-down move.
Fast: This adjusts the fast length of the DPO.
Slow: This adjusts the slow length of the DPO.
Zig-zag Period: This adjusts the period of the zig-zag pattern used in the DPO.
(!) For more information about DPO visit official TradingView description here: link
Also, I want to say thanks to @StockMarketCycles for initial idea of Detrended Rhythm Oscillator (DRO) that I use in this script.
The Adaptive Average Channel is a powerful and versatile indicator that combines the strengths of multiple technical analysis methods.
In summary, with the ALAC, you can:
1 - Dynamically adapt to any asset and price action with automatic calculation of dominant cycle lengths.
2 - Identify potential overbought and oversold conditions with the adaptive market bands.
3 - Customize your analysis with various settings, including moving average type and channel multiplier.
4 - Enhance your trading strategy by using the indicator in conjunction with other forms of analysis.
TrendGuard Flag Finder - Strategy [presentTrading]
Introduction and How It Is Different
In the vast world of trading strategies, the TrendGuard Flag Finder stands out as a unique blend of traditional flag pattern detection and the renowned SuperTrend indicator.
- A significant portion of the Flag Pattern detection is inspired by the "Flag Finder" code by @Amphibiantrading, which serves as one of foundational element of this strategy.
- While many strategies focus on either trend-following or pattern recognition, this strategy harmoniously combines both, offering traders a more holistic view of the market.
- The integration of the SuperTrend indicator not only provides a clear direction of the prevailing trend but also offers potential stop-loss levels, enhancing the strategy's risk management capabilities.
AAPL 1D chart
ETHBTC 6hr chart
Strategy: How It Works
The TrendGuard Flag Finder is primarily built on two pillars:
1. Flag Pattern Detection : At its core, the strategy identifies flag patterns, which are continuation patterns suggesting that the prevailing trend will resume after a brief consolidation. The strategy meticulously detects both bullish and bearish flags, ensuring traders can capitalize on opportunities in both rising and falling markets.
What is a Flag Pattern? A flag pattern consists of two main components:
1.1 The Pole : This is the initial strong price move, which can be either upwards (for bullish flags) or downwards (for bearish flags). The pole represents a strong surge in price in a particular direction, driven by significant buying or selling momentum.
1.2 The Flag : Following the pole, the price starts consolidating, moving against the initial trend. This consolidation forms a rectangular shape and is characterized by parallel trendlines. In a bullish flag, the consolidation will have a slight downward tilt, while in a bearish flag, it will have a slight upward tilt.
How the Strategy Detects Flags:
Identifying the Pole: The strategy first identifies a strong price movement over a user-defined number of bars. This movement should meet a certain percentage change to qualify as a pole.
Spotting the Flag: After the pole is identified, the strategy looks for a consolidation phase. The consolidation should be counter to the prevailing trend and should be contained within parallel lines. The depth (for bullish flags) or rally (for bearish flags) of this consolidation is calculated to ensure it meets user-defined criteria.
2. SuperTrend Integration : The SuperTrend indicator, known for its simplicity and effectiveness, is integrated into the strategy. It provides a dynamic line on the chart, signaling the prevailing trend. When prices are above the SuperTrend line, it's an indication of an uptrend, and vice versa. This not only confirms the flag pattern's direction but also offers a potential stop-loss level for trades.
When combined, these components allow traders to identify potential breakout (for bullish flags) or breakdown (for bearish flags) scenarios, backed by the momentum indicated by the SuperTrend.
Usage
To use the SuperTrend Enhanced Flag Finder:
- Inputs : Begin by setting the desired parameters. The strategy offers a range of user-controlled settings, allowing for customization based on individual trading preferences and risk tolerance.
- Visualization : Once the parameters are set, the strategy will identify and visually represent flag patterns on the chart. Bullish flags are represented in green, while bearish flags are in red.
- Trade Execution : When a breakout or breakdown is identified, the strategy provides entry signals. It also offers exit signals based on the SuperTrend, ensuring that traders can capitalize on the momentum while managing risk.
Default Settings
The strategy comes with a set of default settings optimized for general use:
- SuperTrend Parameters: Length set to 10 and Factor set to 5.0.
- Bull Flag Criteria: Max Flag Depth at 7, Max Flag Length at 10 bars, Min Flag Length at 3 bars, Prior Uptrend Minimum at 9%, and Flag Pole Length between 7 to 13 bars.
- Bear Flag Criteria: Similar settings adjusted for bearish patterns.
- Display Options: By default, both bullish and bearish flags are displayed, with breakout and breakdown points highlighted.
DTR & ATR
Description
This ATR and DTR label is update of Existing Label provided by © ssksubam
Please See Notes on original Script Here :
Original Code is not mine but I have done few code changes which I believe will help everyone who are looking to add more labels together and save space on the chart
ATR & DTR Script is very helpful for Day Traders as I will explain in detail bellow
Following are changes I have incorporated
Previous Label took more space on the charts with Header and Footer.
I removed the Header and moved both DTR vs ATR descriptions on the same line, saving space on the chart.
I updated the code to remove => signs, which are self-explanatory as I will explain below.
I made the label in 1 single compact line for maximum space efficiency and aesthetics.
These changes improve the content's clarity and conciseness while optimizing space on the charts. If you have any further requests or need additional assistance, feel free to let me know!
What Does DTR Signify?
Stock ATR stands for Average True Range, which is a technical indicator used in trading and investment analysis. The Average True Range measures the volatility of a stock over a given period of time. It provides insights into the price movement and potential price ranges of the stock.
The ATR is calculated as the average of the true ranges over a specific number of periods. The true range is the greatest of the following three values:
The difference between the current high and the current low.
The absolute value of the difference between the current high and the previous close.
The absolute value of the difference between the current low and the previous close.
Traders and investors use ATR to assess the potential risk and reward of a stock. A higher ATR value indicates higher volatility and larger price swings, while a lower ATR value suggests lower volatility and smaller price movements. By understanding the ATR, traders can set appropriate stop-loss levels and make informed decisions about position sizing and risk management.
It's important to note that the ATR is not a directional indicator like moving averages or oscillators. Instead, it provides a measure of volatility, helping traders adapt their strategies to suit the current market conditions.
What Does ATR Signify?
The Average True Range (ATR) signifies the level of volatility or price variability in a particular financial asset, such as a stock, currency pair, or commodity, over a specific period of time. It provides valuable information to traders and investors regarding the potential risk and reward associated with the asset.
Here are the key significances of ATR:
Volatility Measurement: ATR measures the average price range between high and low prices over a specified timeframe. Higher ATR values indicate greater volatility, while lower values suggest lower volatility. Traders use this information to gauge the potential price movements and adjust their strategies accordingly.
Risk Assessment: A higher ATR value implies larger price swings, indicating increased market uncertainty and risk. Traders can use ATR to set appropriate stop-loss levels and manage risk by adjusting position sizes based on the current volatility.
Trend Strength: ATR can also be used to assess the strength of a trend. In an uptrend or downtrend, ATR tends to increase, indicating a more powerful price movement. Conversely, a declining ATR might signify a weakening trend or a consolidation period.
Range-Bound Market Identification: In a range-bound or sideways market, the ATR value tends to be relatively low, reflecting the lack of significant price movements. This information can be helpful for range-trading strategies.
Volatility Breakouts: Traders often use ATR to identify potential breakouts from consolidation patterns. When the ATR value expands significantly, it may indicate the beginning of a new trend or a breakout move.
Comparison between Assets: ATR allows traders to compare the volatility of different
How to use DTR & ATR for Trading
Using Average True Range (ATR) and Daily Trading Range (DTR) can be beneficial for day trading to assess potential price movements, manage risk, and identify trading opportunities. Here's how you can use both indicators effectively:
Calculate ATR and DTR: First, calculate the ATR and DTR values for the asset you are interested in trading. ATR is the average of true ranges over a specified period (e.g., 14 days), while DTR is the difference between the high and low prices of a single trading day.
Assess Volatility: Compare the ATR and DTR values to understand the current volatility of the asset. Higher values indicate increased volatility, while lower values suggest reduced volatility.
Setting Stop-Loss: Use ATR to set appropriate stop-loss levels. For example, you might decide to set your stop-loss a certain number of ATR points away from your entry point. This approach allows you to factor in market volatility when determining your risk tolerance.
Identify Trading Range: Analyze DTR to determine the typical daily price range of the asset. This information can help you identify potential support and resistance levels, which are essential for day trading strategies such as breakout or range trading.
Breakout Strategies: ATR can assist in identifying potential breakout opportunities. When ATR values increase significantly, it suggests an expansion in volatility, which may indicate an upcoming breakout from a trading range. Look for breakouts above resistance or below support levels with higher than usual ATR values.
Scalping Strategies: For scalping strategies, where traders aim to profit from small price movements within a single trading session, knowing the typical DTR can help set reasonable profit targets and stop-loss levels.
Confirming Trend Strength: In day trading, you may encounter short-term trends. Use ATR to assess the strength of these trends. If the ATR is rising, it suggests a strong trend, while a declining ATR may indicate a weakening trend or potential reversal.
Risk Management: Both ATR and DTR can aid in risk management. Determine your position size based on the current ATR value to align it with your risk tolerance. Additionally, understanding the DTR can help you avoid overtrading during periods of low volatility.
Combine with Other Indicators: ATR and DTR work well when used in conjunction with other technical indicators like moving averages, Bollinger Bands, or RSI. Combining multiple indicators can provide a mor
ATR Extension [QuantVue]The Moving Average ATR Extension Indicator offers a powerful blend of two key market elements: the Average True Range (ATR) and Moving Averages (MA), capturing the dynamics of market momentum and trend direction.
This indicator is used to measure market extension from a user-selected moving average based on multiples of the Average True Range (ATR). By doing this, it becomes remarkably straightforward to spot strength at breakout points or exhaustion near the end of a run.
As a market breaks out the extension indicates a surge in buying pressure, while an extension after a sizeable move can often be an indication of market exhaustion. This extended position essentially reflects over-enthusiastic buying and could be an early warning sign of a potential trend reversal.
Breakout Strength:
Exhaustion:
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers.
[tradinghook] - Renko Trend Reversal Strategy - Renko Trend Reversal Strategy
Short Title: - Renko TRS
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
CCI+EMA Strategy with Percentage or ATR TP/SL [Alifer]This is a momentum strategy based on the Commodity Channel Index (CCI), with the aim of entering long trades in oversold conditions and short trades in overbought conditions.
Optionally, you can enable an Exponential Moving Average (EMA) to only allow trading in the direction of the larger trend. Please note that the strategy will not plot the EMA. If you want, for visual confirmation, you can add to the chart an Exponential Moving Average as a second indicator, with the same settings used in the strategy’s built-in EMA.
The strategy also allows you to set internal Stop Loss and Take Profit levels, with the option to choose between Percentage-based TP/SL or ATR-based TP/SL.
The strategy can be adapted to multiple assets and timeframes:
Pick an asset and a timeframe
Zoom back as far as possible to identify meaningful positive and negative peaks of the CCI
Set Overbought and Oversold at a rough average of the peaks you identified
Adjust TP/SL according to your risk management strategy
Like the strategy? Give it a boost!
Have any questions? Leave a comment or drop me a message.
CAUTIONARY WARNING
Please note that this is a complex trading strategy that involves several inputs and conditions. Before using it in live trading, it is highly recommended to thoroughly test it on historical data and use risk management techniques to safeguard your capital. After backtesting, it's also highly recommended to perform a first live test with a small amount. Additionally, it's essential to have a good understanding of the strategy's behavior and potential risks. Only risk what you can afford to lose .
USED INDICATORS
1 — COMMODITY CHANNEL INDEX (CCI)
The Commodity Channel Index (CCI) is a technical analysis indicator used to measure the momentum of an asset. It was developed by Donald Lambert and first published in Commodities magazine (now Futures) in 1980. Despite its name, the CCI can be used in any market and is not just for commodities. The CCI compares current price to average price over a specific time period. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement.
The CCI was originally developed to spot long-term trend changes but has been adapted by traders for use on all markets or timeframes. Trading with multiple timeframes provides more buy or sell signals for active traders. Traders often use the CCI on the longer-term chart to establish the dominant trend and on the shorter-term chart to isolate pullbacks and generate trade signals.
CCI is calculated with the following formula:
(Typical Price - Simple Moving Average) / (0.015 x Mean Deviation)
Some trading strategies based on CCI can produce multiple false signals or losing trades when conditions turn choppy. Implementing a stop-loss strategy can help cap risk, and testing the CCI strategy for profitability on your market and timeframe is a worthy first step before initiating trades.
2 — AVERAGE TRUE RANGE (ATR)
The Average True Range (ATR) is a technical analysis indicator that measures market volatility by calculating the average range of price movements in a financial asset over a specific period of time. The ATR was developed by J. Welles Wilder Jr. and introduced in his book “New Concepts in Technical Trading Systems” in 1978.
The ATR is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The ATR can be used to set stop-loss orders. One way to use ATR for stop-loss orders is to multiply the ATR by a factor (such as 2 or 3) and subtract it from the entry price for long positions or add it to the entry price for short positions. This can help traders set stop-loss orders that are more adaptive to market volatility.
3 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
STRATEGY EXPLANATION
1 — INPUTS AND PARAMETERS
The strategy uses the Commodity Channel Index (CCI) with additional options for an Exponential Moving Average (EMA), Take Profit (TP) and Stop Loss (SL).
length : The period length for the CCI calculation.
overbought : The overbought level for the CCI. When CCI crosses above this level, it may signal a potential short entry.
oversold : The oversold level for the CCI. When CCI crosses below this level, it may signal a potential long entry.
useEMA : A boolean input to enable or disable the use of Exponential Moving Average (EMA) as a filter for long and short entries.
emaLength : The period length for the EMA if it is used.
2 — CCI CALCULATION
The CCI indicator is calculated using the following formula:
(src - ma) / (0.015 * ta.dev(src, length))
src is the typical price (average of high, low, and close) and ma is the Simple Moving Average (SMA) of src over the specified length.
3 — EMA CALCULATION
If the useEMA option is enabled, an EMA is calculated with the given emaLength .
4 — TAKE PROFIT AND STOP LOSS METHODS
The strategy offers two methods for TP and SL calculations: percentage-based and ATR-based.
tpSlMethod_percentage : A boolean input to choose the percentage-based method.
tpSlMethod_atr : A boolean input to choose the ATR-based method.
5 — PERCENTAGE-BASED TP AND SL
If tpSlMethod_percentage is chosen, the strategy calculates the TP and SL levels based on a percentage of the average entry price.
tp_percentage : The percentage value for Take Profit.
sl_percentage : The percentage value for Stop Loss.
6 — ATR-BASED TP AND SL
If tpSlMethod_atr is chosen, the strategy calculates the TP and SL levels based on Average True Range (ATR).
atrLength : The period length for the ATR calculation.
atrMultiplier : A multiplier applied to the ATR to set the SL level.
riskRewardRatio : The risk-reward ratio used to calculate the TP level.
7 — ENTRY CONDITIONS
The strategy defines two conditions for entering long and short positions based on CCI and, optionally, EMA.
Long Entry: CCI crosses below the oversold level, and if useEMA is enabled, the closing price should be above the EMA.
Short Entry: CCI crosses above the overbought level, and if useEMA is enabled, the closing price should be below the EMA.
8 — TP AND SL LEVELS
The strategy calculates the TP and SL levels based on the chosen method and updates them dynamically.
For the percentage-based method, the TP and SL levels are calculated as a percentage of the average entry price.
For the ATR-based method, the TP and SL levels are calculated using the ATR value and the specified multipliers.
9 — EXIT CONDITIONS
The strategy defines exit conditions for both long and short positions.
If there is a long position, it will be closed either at TP or SL levels based on the chosen method.
If there is a short position, it will be closed either at TP or SL levels based on the chosen method.
Additionally, positions will be closed if CCI crosses back above oversold in long positions or below overbought in short positions.
10 — PLOTTING
The script plots the CCI line along with overbought and oversold levels as horizontal lines.
The CCI line is colored red when above the overbought level, green when below the oversold level, and white otherwise.
The shaded region between the overbought and oversold levels is plotted as well.
Average True Range Trailing Mean [Alifer]Upgrade of the Average True Range default indicator by TradingView. It adds and plots a trailing mean to show periods of increased volatility more clearly.
ATR TRAILING MEAN
A trailing mean, also known as a moving average, is a statistical calculation used to smooth out data over time and identify trends or patterns in a time series.
In our indicator, it clearly shows when the ATR value spikes outside of it's average range, making it easier to identify periods of increased volatility.
Here's how the ATR Trailing Mean (atr_mean) is calculated:
atr_mean = ta.cum(atr) / (bar_index + 1) * atr_mult
The ta.cum() function calculates the cumulative sum of the ATR over all bars up to the current bar.
(bar_index + 1) represents the number of bars processed up to the current bar, including the current one.
By dividing the cumulative ATR ta.cum(atr) by (bar_index + 1) and then multiplying it by atr_mult (Multiplier), we obtain the ATR Trailing Mean value.
If atr_mult is set to 1.0, the ATR Trailing Mean will be equal to the simple average of the ATR values, and it will follow the ATR's general trend.
However, if atr_mult is increased, the ATR Trailing Mean will react more strongly to the ATR's recent changes, making it more sensitive to short-term fluctuations.
On the other hand, reducing atr_mult will make the ATR Trailing Mean less responsive to recent changes in ATR, making it smoother and less prone to reacting to short-term volatility.
In summary, adjusting the atr_mult input allows traders to fine-tune the ATR Trailing Mean's responsiveness based on their preferred level of sensitivity to recent changes in market volatility.
IMPLEMENTATION IN A STRATEGY
You can easily implement this indicator in an existing strategy, to only enter positions when the ATR is above the ATR Trailing Mean (with Multiplier-adjusted sensitivity). To do so, add the following lines of codes.
Under Inputs:
length = input.int(title="Length", defval=20, minval=1)
atr_mult = input.float(defval=1.0, step = 0.1, title = "Multiplier", tooltip = "Adjust the sensitivity of the ATR Trailing Mean line.")
smoothing = input.string(title="Smoothing", defval="RMA", options= )
ma_function(source, length) =>
switch smoothing
"RMA" => ta.rma(source, length)
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
=> ta.wma(source, length)
This will allow you to define the Length of the ATR (lookback length over which the ATR is calculated), the Multiplier to adjust the Trailing Mean's sensitivity and the type of Smoothing to be used for the ATR.
Under Calculations:
atr= ma_function(ta.tr(true), length)
atr_mean = ta.cum(atr) / (bar_index+1) * atr_mult
This will calculate the ATR based on Length and Smoothing, and the resulting ATR Trailing Mean.
Under Entry Conditions, add the following to your existing conditions:
and atr > atr_mean
This will make it so that entries are only triggered when the ATR is above the ATR Trailing Mean (adjusted by the Multiplier value you defined earlier).
ATR - DEFINITION AND HISTORY
The Average True Range (ATR) is a technical indicator used to measure market volatility, regardless of the direction of the price. It was developed by J. Welles Wilder and introduced in his book "New Concepts in Technical Trading Systems" in 1978. ATR provides valuable insights into the degree of price movement or volatility experienced by a financial asset, such as a stock, currency pair, commodity, or cryptocurrency, over a specific period.
ATR - CALCULATION AND USAGE
The ATR calculation involves three components:
1 — True Range (TR): The True Range is a measure of the asset's price movement for a given period. It takes into account the following factors:
The difference between the high and low prices of the current period.
The absolute value of the difference between the high price of the current period and the closing price of the previous period.
The absolute value of the difference between the low price of the current period and the closing price of the previous period.
Mathematically, the True Range (TR) for the current period is calculated as follows:
TR = max(high - low, abs(high - previous_close), abs(low - previous_close))
2 — ATR Calculation: The ATR is calculated as a Moving Average (MA) of the True Range over a specified period.
The ATR is calculated as follows:
ATR = MA(TR, length)
3 — ATR Interpretation: The ATR value represents the average volatility of the asset over the chosen period. Higher ATR values indicate higher volatility, while lower ATR values suggest lower volatility.
Traders and investors can use ATR in various ways:
Setting Stop Loss and Take Profit Levels: ATR can help determine appropriate stop-loss and take-profit levels in trading strategies. A larger ATR value might require wider stop-loss levels to allow for the asset's natural price fluctuations, while a smaller ATR value might allow for tighter stop-loss levels.
Identifying Market Volatility: A sharp increase in ATR might indicate heightened market uncertainty or the potential for significant price movements. Conversely, a decreasing ATR might suggest a period of low volatility and possible consolidation.
Comparing Volatility Between Assets: Since ATR uses absolute values, it shouldn't be used to compare volatility between different assets, as assets with higher prices will consistently have higher ATR values, while assets with lower prices will consistently have lower ATR values. However, the addition of a trailing mean makes such a comparison possible. An asset whose ATR is consistently close to its ATR Trailing Mean will have a lower volatility than an asset whose ATR continuously moves far above and below its ATR Trailing Mean. This can help traders and investors decide which markets to trade based on their risk tolerance and trading strategies.
Determining Position Size: ATR can be used to adjust position sizes, taking into account the asset's volatility. Smaller position sizes might be appropriate for more volatile assets to manage risk effectively.
Buyers & Sellers / RangeBuyers & Sellers / Range
Volatility oscillator that measures the relationship of Buying & Selling Pressure to True Range.
In other words, how much % Buyers and Sellers separately occupy the Bar
BSP is a part of Bar Range. Entire bar metrics will always have bigger value than its composite elements (body and wicks).
Since there will be NO chance of BP or SP being more than ATR, their ratio would serve crucial Volatility details.
Hence, we can relate each of them to the overall range.
As a result we have simultaneous measurements of proportions buyers and sellers to the bar.
Default mode shows BP/ATR and SP/ATR mirrored. When one rises, the other falls to compensate.
Buying Pressure / True Range ⬆️🟢 ⬇️🔵
Selling Pressure / True Range ⬆️🔴 ⬇️🟠
They are being averaged in 2 different ways:
Pre-average first, then relate as ratio
Related first, then Averaged
Enable "Preaveraged" to use already averaged BSP and Ranges in ratio instead of averaging the ratio of BSP to individual bar. For example, we're looking BP/ATR, in calculation of buyers / Range it will use "MA(Buying Pressure) / MA(True Range)" instead of "MA(Buying Pressure / True Range)".
Due such calculation, it is going to be more lagging than in off mode. Nevertheless, it reduces noise from the impact of individual bar change.
Second way of noise reduction is enabling "Body / Range"
BSP Body / Range where Bullish & Bearish Body = Buying & Selling Pressure - Relevant Wick
Buying Body = Buying Pressure - Lower Wick
Selling Body = Selling Pressure - Upper Wick
And only then it is divided to ATR.
Note that Balance line differs because body is less than it used to be with wicks. So change in wicks won't play any role in computing the ratio anymore. Thus, signals of their crossings will be more reliable than in default mode.
ATR InfoWhat Is the Average True Range (ATR)?
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
Each instrument per unit of time passes its average value of the true range, but there are moments when the volatility explodes or abruptly decays, these phenomena introduce large distortions into the average value of the true range.
The ATR_WPB function calculates the average value of the true range for the specified number of bars, while excluding paranormally large and paranormally small bars from the calculation of the average.
For example, if the instrument has passed a small ATR value, then it has many chances to continue moving, but if the instrument has passed its ATR value, then the chances of continuing to move are extremely low.
ATR_InfoWhat Is the Average True Range (ATR)?
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
Each instrument per unit of time passes its average value of the true range, but there are moments when the volatility explodes or abruptly decays, these phenomena introduce large distortions into the average value of the true range.
The ATR_WPB function calculates the average value of the true range for the specified number of bars, while excluding paranormally large and paranormally small bars from the calculation of the average.
For example, if the instrument has passed a small ATR value, then it has many chances to continue moving, but if the instrument has passed its ATR value, then the chances of continuing to move are extremely low.
Library "ATR_Info"
ATR_Info: Calculates ATR without paranormal bars
ATR_WPB(source, period, psmall, pbig)
ATR_WPB: Calculates ATR without paranormal bars
Parameters:
source (float) : ATR_WPB: (series float) The sequence of data on the basis of which the ATP calculation will be made
period (int) : ATR_WPB: (int) Sequence size for ATR calculation
psmall (float) : ATR_WPB: (float) Coefficient for paranormally small bar
pbig (float) : ATR_WPB: (float) Coefficient for paranormally big bar
Returns: ATR_WPB: (float) ATR without paranormal bars
