Volume Based S/R with EMA Crossover SignalsThis Pine Script indicator, titled "Volume Based S/R with EMA Crossover Signals," is designed for use on the TradingView platform and overlays on price charts to help traders identify potential buy and sell opportunities based on volume changes and EMA (Exponential Moving Average) crossovers. Let's break down its components for a detailed understanding:
Inputs
length: The number of bars used to calculate the standard deviation of the volume change. This parameter helps in identifying significant changes in volume over a specified period.
threshold: A multiplier applied to the standard deviation of volume change to determine significant spikes in volume, which are then used to identify support and resistance levels.
smoothLength: The length of the EMA used to smooth the price data, providing a clearer view of the overall price trend and helping to confirm trade signals.
fastEMALength and slowEMALength: The lengths of the fast and slow EMAs, respectively. These are used to generate crossover signals, where the crossing of the fast EMA over the slow EMA may indicate a potential entry or exit point.
Calculations
Volume Change and Standard Deviation: The script calculates the percentage change in volume from one bar to the next and then computes the standard deviation of these changes over the specified length. This process helps identify unusual volume activity, which can precede significant price movements.
Signal Generation Based on Volume: When the absolute value of the volume change divided by its standard deviation exceeds the threshold, it signals significant volume activity, potentially indicating strong support or resistance levels at previous highs or lows.
Smoothed Price: An EMA applied to the closing prices over smoothLength bars helps to confirm the trend direction and filter out noise.
EMA Crossover Signals: The script calculates two EMAs based on the fastEMALength and slowEMALength inputs. A crossover of these two averages generates potential buy or sell signals.
Logic for Buy/Sell Signals
Buy Signal: Generated when the price is above the identified support level (determined by significant volume activity), the fast EMA crosses above the slow EMA, and the price is also above the smoothed price. This confluence of conditions suggests upward momentum and potential buying opportunity.
Sell Signal: The opposite conditions generate a sell signal — when the price is below the identified resistance level, the fast EMA crosses below the slow EMA, and the price is below the smoothed price, indicating downward momentum and a potential selling opportunity.
Plotting
Support and Resistance Levels: Plotted as circles on the chart, with resistance levels in red and support levels in green, based on significant volume activity.
Smoothed Price and EMAs: The smoothed price line and both EMAs are plotted on the chart to help visually assess the trend and the crossover signals.
Buy and Sell Signals: Represented by shapes plotted on the chart, indicating the recommended trading action (buy or sell) based on the combined indicator logic.
Filling Between Support and Resistance: For visual clarity, the area between the identified support and resistance levels is filled, highlighting the range within which the price is expected to fluctuate.
This indicator offers a multi-faceted approach to trading, combining volume analysis with trend following via EMA crossovers. By identifying significant volume-based support and resistance levels and confirming trend direction with EMA crossovers and smoothed price trends, traders can make more informed decisions regarding entry and exit points. However, it's important to use this indicator as part of a comprehensive trading strategy, considering other factors such as market conditions, news, and technical analysis from other indicators.
Cerca negli script per "moving average crossover"
Sniper Entry using RSI confirmationThis is a sniper entry indicator that provides Buy and Sell signals using other Indicators to give the best possible Entries (note: Entries will not be 100 percent accurate and analysis should be done to support an entry)
Moving Average Crossovers:
The indicator uses two moving averages: a short-term SMA (Simple Moving Average) and a long-term SMA.
When the short-term SMA crosses above the long-term SMA, it generates a buy signal (indicating potential upward momentum).
When the short-term SMA crosses below the long-term SMA, it generates a sell signal (indicating potential downward momentum).
RSI Confirmation:
The indicator incorporates RSI (Relative Strength Index) to confirm the buy and sell signals generated by the moving average crossovers.
RSI is used to gauge the overbought and oversold conditions of the market.
A buy signal is confirmed if RSI is below a specified overbought level, indicating potential buying opportunity.
A sell signal is confirmed if RSI is above a specified oversold level, indicating potential selling opportunity.
Dynamic Take Profit and Stop Loss:
The indicator calculates dynamic take profit and stop loss levels based on the Average True Range (ATR).
ATR is used to gauge market volatility, and the take profit and stop loss levels are adjusted accordingly.
This feature helps traders to manage their risk effectively by setting appropriate profit targets and stop loss levels.
Combining the information provided by these, the indicator will provide an entry point with a provided take profit and stop loss. The indicator can be applied to different asset classes. Risk management must be applied when using this indicator as it is not 100% guaranteed to be profitable.
Goodluck!
[CP]Pivot Boss Multi Timeframe CPR Inception with MACD and EMAINTRODUCTION:
This indicator combines multi-timeframe CPR bands with MACD Momentum and EMA trend, all projected on the candlestick chart through a novel visualization.
If you have seen my other indicators on TradingView, you would know that I use floor pivots a lot and “Secrets of a Pivot Boss” is my favorite book. While using floor pivots, time and again I have noticed an interesting price behavior,
Trending moves in price typically start from around the Central Pivot Range (CPR). The CPR could be from ANY timeframe. These moves can easily be caught using simple momentum and trend indicators like MACD and EMA crossovers.
Yes, it is that simple. Follow along to understand how to use this indicator.
INDICATOR SETTINGS:
RANGEBOUND MACD AND EMA MARKINGS:
TradingView limits the max number of labels that can be shown on a chart to 500. Therefore, if you go far back enough, you won't see any markings for the MACD or EMA setups. If you are looking to test the efficacy of this indicator in the past, change the start and end dates to your desired timeframe and then select the ‘Mark MACD and EMA Setups in Range?’ option.
MULTI TIMEFRAME CENTRAL PIVOT RANGE:
Here you can select CPRs and their bands from which timeframes are shown on the chart. I will share my favorite settings later in this description.
CPR CONFIGURATION:
Show CPR Labels: CPRs markings can carry labels, so that you don’t confuse between which line is what. Use this setting to toggle them On/Off.
Show Next Time Period Pivots: Check this option if you want to see the CPR of the next time period. This is typically done to figure out the ’Two Day CPR Relationship’ . Read the book, “Secrets of a Pivot Boss”, to understand more.
EMA TREND:
Show EMA on the Chart: EMAs will be plotted on the chart. Standard stuff.
Mark EMA Crossovers on Chart: EMA crossovers will be marked on the chart in diamond shapes. If you are using EMA crossovers, I recommend setting this option to True.
Rest of the EMA settings are fairly obvious.
MACD MOMENTUM:
Projecting MACD parameters directly on the candlesticks is surely going to give you a new perspective about price action and MACD.
Also, in order to better understand the MACD projections on the chart, you can add a standard MACD indicator on the chart with default settings to figure out what my indicator is actually showing you.
Marking MACD Crossovers on Chart: Marks the MACD signal crossovers on the chart. This visualization was a game changer for me.
Show MACD Histogram on Chart: Projects the complete MACD Histogram in a novel fashion (Try it!). You will be able to visually see the ebbs and flow of momentum in the charts.
Mark MACD Histogram Peaks on Chart: Marks only the MACD peaks instead of the complete histogram. Peaks are a great way to enter an ongoing trend and to play an intraday rangebound market.
Rest of the settings are just the standard settings that you will find in a typical MACD indicator.
ALERTS:
Not shown in the settings panel, but I have added alerts for EMA and MACD Crossovers so that you don’t have to sit in front of the charts or constantly check the price all day long.
If you don’t know how to set alerts in TradingView, then please Google it.
INDICATOR USAGE EXAMPLES:
This indicator can be used in intraday as well as in higher timeframes.
There are quite a few variations possible, I personally prefer to use the EMA crossovers in intraday (5m) and MACD on Daily timeframes.
This is just a matter of personal preference, some people might prefer using EMAs only or MACD only in all timeframes.
Here are my personal settings for the intraday 5-minute timeframe:
Turn on all the CPR pivots starting from Yearly all the way to Daily. You can turn on 6 hourly and 4 hourly as well if you want.
Hourly CPR is mostly used when the price is in a strong trend and you missed the entry and don’t know when to enter. Price will typically experience pullbacks towards the Hourly CPR, before resuming in the direction of the trend. That is your chance to hop onto the bandwagon.
For Intraday, I keep the Bands off. Just a personal preference here.
You can turn ON the Show CPR Labels , if you want.
Turn ON both the options in the EMA TREND section. You would want to see the EMA crossovers marked on the chart as well as the EMAs themselves, as the distance between the two EMAs will give you an idea about the strength of the trend.
Keep rest of the settings in the EMA section as default (you can change the colors if you wish). I keep the same EMAs as the ones kept in the MACD indicator. I like to keep things simple.
In the MACD MOMENTUM section, turn ON Mark MACD Histogram Peaks on Chart and all the other options turned OFF. Leave the other settings as default. By the way, these are the default settings of the standard MACD Indicator.
You can set up EMA Bullcross and Bearcross alarms if you like.
Before checking out the examples, remember one super simple rule:
SOME OF THE BEST TRENDING MOVES IN THE MARKET, BE IT INTRADAY OR OTHERWISE, ORIGINATE IN THE VICINITY OF A LARGER TIMEFRAME PIVOT/CPR.
Look for price settling above/below a pivot, and then a move away from the pivot in any direction is typically a trending move.
You can use hourly pivots or MACD Histogram peaks marked on the chart to enter an existing trend, or add to your positions.
Let’s have a look at a few recent intraday examples from the Crypto, Indian, and US equity markets.
I have added my comments in the charts to make you easily understand what is going on.
Understand that both, moving average crossover and MACD, will give out a lot of signals (chop) every day. But almost 70% of them are going to be fake signals. It is the signals that you get when the price is near a Pivot, that tend to convert into gorgeous trending moves that last.
BTC 5m Charts
NIFTY Futures 5m Charts (good intraday trends are hard to find here, as the market is very efficient)
TSLA 5m Charts
Some important points for using this indicator in higher timeframes:
For higher timeframes, my personal preference is to go with the MACD indicator. I personally find MACD to be lethal on daily and weekly timeframes, if you know how to use it well.
The default settings of the indicator are the settings I use for both, Daily and Weekly, timeframes. Additionally, I turn off the CPR labels.
In theory large trending moves still have a big probability to start near an important pivot level, however, in larger timeframes, trending moves can start from anywhere. They need not start in the vicinity of any important pivot (but they often do!).
Weekly pivots can act as great pullback levels when the price is in strong momentum, when trading on the daily timeframe.
Quarterly Pivots act as great pullback levels when the price is in strong momentum, when trading on the weekly timeframe.
BTC Weekly Chart
BTC Daily Chart
Nifty Weekly Chart
Nifty Daily Chart
NASDAQ Weekly Chart
NASDAQ Daily Chart
FINAL WORDS:
Please understand that I have Cherry Picked the examples to showcase the capability of the indicator and its usage.
DO NOT conflate the accuracy of examples with the accuracy of this indicator.
Biggest catch is the fact that this indicator, like every other indicator out there, will have whipsaws. Some I have also marked in the example charts.
You need to come up with your own technique to avoid whipsaws, one technique I have shared here…… big moves typically start near pivots.
Work on avoiding whipsaws and finding you own edge in the markets.
If you really want to learn how to use Pivots, read the book ’Secrets of a Pivot Boss’ . This book can change your life.
hector mena Breakout Trading with ATR, RSI and MA CrossTitle: Breakout Trading Strategy with ATR, RSI, and Moving Average Cross
Description (English):
This script combines key technical indicators—ATR (Average True Range), RSI (Relative Strength Index), and Moving Averages—to provide a comprehensive breakout trading strategy. It is designed to help traders identify significant breakout levels and confirm signals with momentum and trend analysis.
How It Works:
ATR for Breakout Levels:
The ATR is used to calculate dynamic breakout levels by adjusting the highest resistance and lowest support levels with a customizable multiplier. This ensures that breakout levels adapt to market volatility.
RSI for Momentum Confirmation:
The RSI identifies overbought and oversold conditions, providing an additional layer of confirmation for breakouts. A breakout accompanied by an RSI signal can indicate stronger momentum.
Moving Average Cross for Trend Validation:
Two simple moving averages (short-term and long-term) are included to validate the trend. A crossover suggests a potential change in trend, aligning with breakout signals.
Why Combine These Indicators?
The ATR ensures breakout levels are realistic and volatility-adjusted.
The RSI avoids false signals by confirming if the price has momentum during a breakout.
Moving Average crossovers add trend-following confirmation, helping traders align with market direction.
The combination provides a robust framework to filter out false signals and improve the reliability of trading decisions.
Key Features:
Breakout Levels: Upper and lower breakout levels dynamically calculated using ATR.
RSI Confirmation: Visual overbought (70) and oversold (30) levels and RSI plot.
Trend Validation: Short and long-term moving averages plotted on the chart with crossover signals.
Visual Alerts: Clear "BUY" and "SELL" labels for actionable signals.
Custom Alerts: Configurable alerts for breakouts and moving average crossovers.
How to Use It:
Adjust the parameters (ATR length, multiplier, RSI length, and moving averages) based on your trading strategy.
Look for "BUY" signals when:
Price breaks above the resistance level, and RSI indicates oversold conditions.
Moving averages cross bullishly.
Look for "SELL" signals when:
Price breaks below the support level, and RSI indicates overbought conditions.
Moving averages cross bearishly.
Use alerts for automated notifications about potential trades.
Notes:
This script is intended for educational purposes. Use it alongside proper risk management techniques and backtesting.
Always test in demo mode before applying it to live trading.
Waldo RSI :oWaldo RSI :o Indicator Guide
The Waldo RSI :o indicator is designed to complement the "Waldo RSI Overlay :o" by providing an RSI-based analysis on TradingView, focusing on macro shifts in market trends. Here's a comprehensive guide on how to use this indicator:
Key Features:
RSI Settings:
RSI Source: Choose from ON RSI, ON HIGH, ON LOW, ON CLOSE, or ON OPEN to determine how RSI calculates pivots.
RSI Settings:
Source: Default is (H+L)/2, but you can select any price for RSI calculation.
Length: Default RSI length is 7, which can be adjusted for sensitivity.
Trend Lines:
Show Trend Lines: Option to display trend lines based on RSI pivot points.
Zigzag Length: Determines pivot point sensitivity.
Confirm Length: Validates pivot points (default is 3).
Colors: Customize colors for Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), and Lower Lows (LL) on the RSI.
Label Size and Line Width: Adjust the appearance of labels and lines.
Divergences:
Classic Divergences:
Show Classic Div: Toggle to reveal divergences where RSI and price move in opposite directions.
Colors: Set different colors for bullish and bearish divergence indicators.
Transparency and Line Width: Control the visual impact of divergence signals.
Hidden Divergences:
Similar settings for identifying hidden divergences, suggest trend continuation.
Breakout/Breakdown:
Show Breakout/Breakdown: Generates signals for RSI breakouts or breakdowns, used by "Waldo RSI Overlay :o" for visual chart signals.
Overbought/Oversold Zones:
Show Overbought and OverSold Zones: Highlights when RSI goes above 70 (overbought) or below 30 (oversold).
Moving Averages on RSI:
The default Moving Average (MA) settings are tailored to capture macro shifts in market trends:
Show Moving Averages: Option to overlay two MAs on the RSI for trend confirmation:
Fast RSI MA:
RSI Period: 50 (this is the period over which the RSI is calculated).
MA Length: 50 (the number of periods used for the moving average of the RSI).
Slow RSI MA:
RSI Period: 50 (same as fast for consistency in RSI calculation).
MA Length: 200 (longer term for capturing broader trends).
Crossover Signals: The RSI changes color from red to green based on these moving average crossovers:
When the Fast MA (50 period) crosses above the Slow MA (200 period), the RSI turns green, indicating potential bullish conditions or momentum shift.
Conversely, when the Fast MA crosses below the Slow MA, the RSI turns red, suggesting bearish conditions or a shift back towards a downtrend.
This 50-period RSI crossover setting is used to identify overall macro shifts in the market, providing a clear visual cue for traders looking at longer-term trends.
Ghost Lines (Optional):
Ghost Lines: Option to limit how far RSI trend lines extend, helping to keep the chart less cluttered.
How to Use the Indicator:
Setup:
Configure RSI by choosing the source and setting the length to match your trading style.
Set the zigzag and confirm lengths for appropriate pivot detection.
Trend Analysis:
Monitor the RSI for trend changes using the colored trend lines and labels.
Divergence Detection:
Look for RSI and price divergences to anticipate potential reversals or continuations.
Breakout/Breakdown:
Use these signals in conjunction with "Waldo RSI Overlay :o" for price action confirmation.
Overbought/Oversold:
Identify when the market might be due for a correction or continued momentum.
Moving Averages:
Focus on the color changes in RSI to understand macro trend shifts with the default 50/200 period setup.
Ghost Lines:
Enable for a cleaner chart if you don't need trend lines extending indefinitely.
Usage Tips:
Combine with other indicators for confirmation, as no single tool is foolproof.
Adjust settings to suit different market conditions or trading timeframes.
Use in tandem with "Waldo RSI Overlay :o" for a full trading signal system.
Remember, trading involves significant risk, and historical data does not guarantee future performance. Use this indicator as part of a broader trading strategy.
UM EMA SMA WMA HMA with Directional Color ChangeUM EMA SMA WMA HMA with Directional Color Change
Description:
This is a Swiss Army knife type of Moving Average tool. Select your favorite Moving Average type, EMA - Exponential Moving Average, SMA - Simple Moving Average, WMA - Weighted Moving Average, or HMA - Hull Moving Average. Then selection your number of periods. The MA line is green when trending higher and red when trending lower. The fill between price and the MA line matches the red/green of the direction.
Defaults and Configuration:
The default setting is 65 period and EMA. Line colors and optional fill colors are user-configurable.
Alerts:
An alert can be set on the MA for directional color changes (red to green, or green to red) Right click the indicator and select Add Alert. Then select Bullish or Bearish color change.
Suggested Uses:
Add this to any timeframe chart with your favorite Moving averages. A strategy I use frequently is to "stretch" the Moving average. For example if you like the 8 day moving average on the daily chart, try the 52 period Moving average on the hourly chart. (6.5 market hours per day * 8) By looking at smaller time frames with longer MAs you get smoother color transitions on the Moving average. Add multiple instances of the MA. I prefer to use a smaller quick MA with a longer MA that represents a longer time frame.
Another use case I also like is the color transition over a Moving Average crossover. While I do like the daily 2/6 and 8/3 moving average crossovers, red-to-green and green-to-red color transitions seem to work with less lag than the crossovers.
Suggested Settings:
Daily charts: 8 EMA
Hourly charts: 55 EMA
30 minute charts: 65 WMA. (I like this one for inverse ETFs)
3 minutes charts: 178 EMA and 233 EMA
I also like to round MA settings up or down to the nearest fibonacci number: 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, etc.
Envelope and Moving Average**Description:**
- This script creates an indicator that combines an envelope and a simple moving average (MA).
- The envelope is constructed using a specified length, percentage deviation, and source price (close by default).
- The moving average is calculated based on a specified length and source price.
**Inputs:**
1. Envelope:
- Length: Number of periods used for the envelope calculation (default is 20).
- Percentage Deviation: Percentage above and below the envelope basis (default is 10%).
- Source: The price used for the envelope calculation (default is close).
- Exponential MA: Option to use exponential moving average for the envelope basis (default is false).
2. Moving Average:
- Length: Number of periods used for the moving average calculation (default is 20).
- Source: The price used for the moving average calculation (default is close).
**Plotting:**
- The script plots the envelope basis, upper envelope line, and lower envelope line.
- The area between the upper and lower envelope lines is filled with a semi-transparent color for better visualization.
- The moving average is plotted on the chart with a specified color and line width.
**How to Use in a Strategy:**
1. **Envelope Crossovers:**
- Go Long (Buy): When the close price crosses above the upper envelope line.
- Go Short (Sell): When the close price crosses below the lower envelope line.
2. **Moving Average Crossovers:**
- Go Long (Buy): When the close price crosses above the moving average.
- Go Short (Sell): When the close price crosses below the moving average.
3. **Confirmation:**
- Consider additional confirmation signals or filters to improve the robustness of your strategy.
- For example, you might require a certain amount of price momentum or use other technical indicators in conjunction with envelope and moving average signals.
4. **Optimization:**
- Experiment with different parameter values (e.g., envelope length, percentage deviation, moving average length) to optimize the strategy for specific market conditions.
5. **Risk Management:**
- Implement proper risk management techniques, such as setting stop-loss orders and position sizing, to control risk.
Remember to thoroughly backtest any strategy before deploying it in a live trading environment. Additionally, consider the current market conditions and adapt your strategy accordingly.
Dynamic RSI Bollinger Bands with Waldo Cloud
TradingView Indicator Description: Dynamic RSI Bollinger Bands with Waldo Cloud
Title: Dynamic RSI Bollinger Bands with Waldo Cloud
Short Title: Dynamic RSI BB Waldo
Overview:
Introducing an experimental indicator, the Dynamic RSI Bollinger Bands with Waldo Cloud, designed for adventurous traders looking to explore new dimensions in technical analysis. This indicator overlays on your chart, providing a unique perspective by integrating the Relative Strength Index (RSI) with Bollinger Bands, creating a dynamic trading tool that adapts to market conditions through the lens of momentum and volatility.
What is it?
This innovative indicator combines the traditional Bollinger Bands with the RSI in a way that hasn't been commonly explored. Here's a breakdown:
RSI Integration: The RSI is calculated with customizable length settings, and its values are used not just for momentum analysis but as the basis for the Bollinger Bands. This means the position and width of the bands are directly influenced by the RSI, offering a visual representation of momentum within the context of price volatility.
Dynamic Bollinger Bands: Instead of using price directly, the Bollinger Bands are calculated using a scaled version of the RSI. This scaling is done to fit the RSI values into the price range, ensuring the bands are relevant to the actual price movement. The standard deviation for these bands is also scaled accordingly, providing a unique volatility measure that's momentum-driven.
Waldo Cloud: Named after a visual representation concept, the 'Waldo Cloud' refers to the colored area between the Bollinger Bands, which changes based on various conditions:
Purple when RSI is overbought.
Blue when RSI is oversold.
Green for bullish conditions, defined by the fast-moving average crossing above the slow one, RSI is bullish, and the price is above the slow MA.
Red for bearish conditions, when the fast MA crosses below the slow MA, the RSI is bearish, and the price is below the slow MA.
Gray for neutral market conditions.
Moving Averages: Two simple moving averages (Fast MA and Slow MA) are included, which can be toggled on or off, offering additional trend analysis through crossovers.
How to Use It:
Given its experimental nature, this indicator should be used with caution and in conjunction with other analysis methods:
Identifying Market Conditions: Use the color of the Waldo Cloud to gauge market sentiment. A green cloud might suggest a good time to consider long positions, while a red cloud could indicate potential shorting opportunities. Purple and blue clouds highlight extreme conditions that might precede reversals.
Volatility and Momentum: The dynamic nature of the Bollinger Bands based on RSI provides insight into how momentum is affecting price volatility. When the bands are wide, it might indicate high momentum and potential trend continuation or reversal, depending on the RSI's position relative to its overbought/oversold levels.
Trend Confirmation: The moving average crossovers can act as confirmation signals. For instance, a bullish crossover (fast MA over slow MA) within a green cloud might strengthen a buy signal, whereas a bearish crossover in a red cloud might reinforce a sell decision.
Customization: Adjust the RSI length, overbought/oversold levels, and moving average lengths to suit different trading styles or market conditions. Experiment with these settings to find what works best for your strategy.
Combining with Other Indicators: Since this is an experimental tool, it's advisable to use it alongside established indicators like traditional Bollinger Bands, MACD, or trend lines to validate signals.
Conclusion:
The Dynamic RSI Bollinger Bands with Waldo Cloud is an experimental venture into combining momentum with volatility visually and interactively. It's designed for traders who are open to exploring new methods of market analysis.
Remember, due to its experimental status, this indicator should be part of a broader trading strategy, and backtesting or paper trading is recommended before applying it in live trading scenarios. Keep an eye on how the market reacts to the signals provided by this indicator and always consider risk management practices.
Wyckoff Range StrategyThe Wyckoff Range Strategy is a trading strategy that aims to identify potential accumulation and distribution phases in the market using the principles of Wyckoff analysis. It also incorporates the detection of spring and upthrust patterns.
Here's a step-by-step explanation of how to use this strategy:
Understanding Accumulation and Distribution Phases:
Accumulation Phase: This is a period where smart money (large institutional traders) accumulates a particular asset at lower prices. It is characterized by a sideways or consolidating price action.
Distribution Phase: This is a period where smart money distributes or sells a particular asset at higher prices. It is also characterized by a sideways or consolidating price action.
Input Variables:
crossOverLength: This variable determines the length of the moving average crossover used to identify accumulation and distribution phases. You can adjust this value based on the market you are trading and the time frame you are analyzing.
stopPercentage: This variable determines the percentage used to calculate the stop loss level. It helps you define a predefined level at which you would exit a trade if the price moves against your position.
Strategy Conditions:
Enter Long: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength and a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the start of an accumulation phase and a potential buying opportunity.
Exit Long: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength or a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the end of an accumulation phase and a potential exit signal for long positions.
Enter Short: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength and a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the start of a distribution phase and a potential selling opportunity.
Exit Short: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength or a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the end of a distribution phase and a potential exit signal for short positions.
Stop Loss:
The strategy sets a stop loss level for both long and short positions. The stop loss level is calculated based on the stopPercentage variable, which represents the percentage of the current close price. If the price reaches the stop loss level, the strategy will automatically exit the position.
Plotting Wyckoff Schematics:
The strategy plots different shapes on the chart to indicate the identified phases and patterns. Green and red labels indicate the accumulation and distribution phases, respectively. Blue triangles indicate spring patterns, and orange triangles indicate upthrust patterns.
To use this strategy, you can follow these steps:
Jim Forte — Anatomy of a Trading Range
robertbrain.com/Bull...+a+Trading+Range.pdf
9:22 5 MIN 15 MIN BANKNIFTY9:22 5 MIN 15 MIN BANKNIFTY Strategy with Additional Filters
The 9:22 5 MIN 15 MIN BANKNIFTY Strategy with Additional Filters is a trend-following strategy designed for trading the BANKNIFTY instrument on a 5-minute chart. It aims to capture potential price movements by generating buy and sell signals based on moving average crossovers, breakout confirmations, and additional filters.
Key Features:
Fast MA Length: 9
Slow MA Length: 22
ATR Length: 14
ATR Filter: 0.5
Trailing Stop Percentage: 1.5%
Pullback Threshold: 0.5
Minimum Candle Body Percentage: 0.5
Use Breakout Confirmation: Enabled
Additional Filters:
Volume Threshold: Set a minimum volume requirement for trades.
Trend Filter: Optionally enable a trend filter based on a higher timeframe moving average.
Momentum Filter: Optionally enable a momentum filter using the RSI indicator.
Support/Resistance Filter: Optionally enable a filter based on predefined support and resistance levels.
Buy and Sell Signals:
Buy Signal: A buy signal is generated when the fast moving average crosses above the slow moving average, with additional confirmation from breakout and volume criteria, along with optional trend, momentum, and support/resistance filters.
Sell Signal: A sell signal is generated when the fast moving average crosses below the slow moving average, with similar confirmation and filtering criteria as the buy signal.
Exit Strategy:
The strategy employs a trailing stop-loss mechanism based on a percentage of the average entry price. The stop-loss is dynamically adjusted to protect profits while allowing for potential upside.
Please note that this strategy should be thoroughly backtested and evaluated in different market conditions before applying it to live trading. It is also recommended to adjust the parameters and filters according to individual preferences and risk tolerance.
Feel free to customise and adapt the description as needed to suit your preferences and the specific details of your strategy.
Webhook Starter Kit [HullBuster]
Introduction
This is an open source strategy which provides a framework for webhook enabled projects. It is designed to work out-of-the-box on any instrument triggering on an intraday bar interval. This is a full featured script with an emphasis on actual trading at a brokerage through the TradingView alert mechanism and without requiring browser plugins.
The source code is written in a self documenting style with clearly defined sections. The sections “communicate” with each other through state variables making it easy for the strategy to evolve and improve. This is an excellent place for Pine Language beginners to start their strategy building journey. The script exhibits many Pine Language features which will certainly ad power to your script building abilities.
This script employs a basic trend follow strategy utilizing a forward pyramiding technique. Trend detection is implemented through the use of two higher time frame series. The market entry setup is a Simple Moving Average crossover. Positions exit by passing through conditional take profit logic. The script creates ten indicators including a Zscore oscillator to measure support and resistance levels. The indicator parameters are exposed through 47 strategy inputs segregated into seven sections. All of the inputs are equipped with detailed tool tips to help you get started.
To improve the transition from simulation to execution, strategy.entry and strategy.exit calls show enhanced message text with embedded keywords that are combined with the TradingView placeholders at alert time. Thereby, enabling a single JSON message to generate multiple execution events. This is genius stuff from the Pine Language development team. Really excellent work!
This document provides a sample alert message that can be applied to this script with relatively little modification. Without altering the code, the strategy inputs can alter the behavior to generate thousands of orders or simply a few dozen. It can be applied to crypto, stocks or forex instruments. A good way to look at this script is as a webhook lab that can aid in the development of your own endpoint processor, impress your co-workers and have hours of fun.
By no means is a webhook required or even necessary to benefit from this script. The setups, exits, trend detection, pyramids and DCA algorithms can be easily replaced with more sophisticated versions. The modular design of the script logic allows you to incrementally learn and advance this script into a functional trading system that you can be proud of.
Design
This is a trend following strategy that enters long above the trend line and short below. There are five trend lines that are visible by default but can be turned off in Section 7. Identified, in frequency order, as follows:
1. - EMA in the chart time frame. Intended to track price pressure. Configured in Section 3.
2. - ALMA in the higher time frame specified in Section 2 Signal Line Period.
3. - Linear Regression in the higher time frame specified in Section 2 Signal Line Period.
4. - Linear Regression in the higher time frame specified in Section 2 Signal Line Period.
5. - DEMA in the higher time frame specified in Section 2 Trend Line Period.
The Blue, Green and Orange lines are signal lines are on the same time frame. The time frame selected should be at least five times greater than the chart time frame. The Purple line represents the trend line for which prices above the line suggest a rising market and prices below a falling market. The time frame selected for the trend should be at least five times greater than the signal lines.
Three oscillators are created as follows:
1. Stochastic - In the chart time frame. Used to enter forward pyramids.
2. Stochastic - In the Trend period. Used to detect exit conditions.
3. Zscore - In the Signal period. Used to detect exit conditions.
The Stochastics are configured identically other than the time frame. The period is set in Section 2.
Two Simple Moving Averages provide the trade entry conditions in the form of a crossover. Crossing up is a long entry and down is a short. This is in fact the same setup you get when you select a basic strategy from the Pine editor. The crossovers are configured in Section 3. You can see where the crosses are occurring by enabling Show Entry Regions in Section 7.
The script has the capacity for pyramids and DCA. Forward pyramids are enabled by setting the Pyramid properties tab with a non zero value. In this case add on trades will enter the market on dips above the position open price. This process will continue until the trade exits. Downward pyramids are available in Crypto and Range mode only. In this case add on trades are placed below the entry price in the drawdown space until the stop is hit. To enable downward pyramids set the Pyramid Minimum Span In Section 1 to a non zero value.
This implementation of Dollar Cost Averaging (DCA) triggers off consecutive losses. Each loss in a run increments a sequence number. The position size is increased as a multiple of this sequence. When the position eventually closes at a profit the sequence is reset. DCA is enabled by setting the Maximum DCA Increments In Section 1 to a non zero value.
It should be noted that the pyramid and DCA features are implemented using a rudimentary design and as such do not perform with the precision of my invite only scripts. They are intended as a feature to stress test your webhook endpoint. As is, you will need to buttress the logic for it to be part of an automated trading system. It is for this reason that I did not apply a Martingale algorithm to this pyramid implementation. But, hey, it’s an open source script so there is plenty of room for learning and your own experimentation.
How does it work
The overall behavior of the script is governed by the Trading Mode selection in Section 1. It is the very first input so you should think about what behavior you intend for this strategy at the onset of the configuration. As previously discussed, this script is designed to be a trend follower. The trend being defined as where the purple line is predominately heading. In BiDir mode, SMA crossovers above the purple line will open long positions and crosses below the line will open short. If pyramiding is enabled add on trades will accumulate on dips above the entry price. The value applied to the Minimum Profit input in Section 1 establishes the threshold for a profitable exit. This is not a hard number exit. The conditional exit logic must be satisfied in order to permit the trade to close. This is where the effort put into the indicator calibration is realized. There are four ways the trade can exit at a profit:
1. Natural exit. When the blue line crosses the green line the trade will close. For a long position the blue line must cross under the green line (downward). For a short the blue must cross over the green (upward).
2. Alma / Linear Regression event. The distance the blue line is from the green and the relative speed the cross is experiencing determines this event. The activation thresholds are set in Section 6 and relies on the period and length set in Section 2. A long position will exit on an upward thrust which exceeds the activation threshold. A short will exit on a downward thrust.
3. Exponential event. The distance the yellow line is from the blue and the relative speed the cross is experiencing determines this event. The activation thresholds are set in Section 3 and relies on the period and length set in the same section.
4. Stochastic event. The purple line stochastic is used to measure overbought and over sold levels with regard to position exits. Signal line positions combined with a reading over 80 signals a long profit exit. Similarly, readings below 20 signal a short profit exit.
Another, optional, way to exit a position is by Bale Out. You can enable this feature in Section 1. This is a handy way to reduce the risk when carrying a large pyramid stack. Instead of waiting for the entire position to recover we exit early (bale out) as soon as the profit value has doubled.
There are lots of ways to implement a bale out but the method I used here provides a succinct example. Feel free to improve on it if you like. To see where the Bale Outs occur, enable Show Bale Outs in Section 7. Red labels are rendered below each exit point on the chart.
There are seven selectable Trading Modes available from the drop down in Section 1:
1. Long - Uses the strategy.risk.allow_entry_in to execute long only trades. You will still see shorts on the chart.
2. Short - Uses the strategy.risk.allow_entry_in to execute short only trades. You will still see long trades on the chart.
3. BiDir - This mode is for margin trading with a stop. If a long position was initiated above the trend line and the price has now fallen below the trend, the position will be reversed after the stop is hit. Forward pyramiding is available in this mode if you set the Pyramiding value in the Properties tab. DCA can also be activated.
4. Flip Flop - This is a bidirectional trading mode that automatically reverses on a trend line crossover. This is distinctively different from BiDir since you will get a reversal even without a stop which is advantageous in non-margin trading.
5. Crypto - This mode is for crypto trading where you are buying the coins outright. In this case you likely want to accumulate coins on a crash. Especially, when all the news outlets are talking about the end of Bitcoin and you see nice deep valleys on the chart. Certainly, under these conditions, the market will be well below the purple line. No margin so you can’t go short. Downward pyramids are enabled for Crypto mode when two conditions are met. First the Pyramiding value in the Properties tab must be non zero. Second the Pyramid Minimum Span in Section 1 must be non zero.
6. Range - This is a counter trend trading mode. Longs are entered below the purple trend line and shorts above. Useful when you want to test your webhook in a market where the trend line is bisecting the signal line series. Remember that this strategy is a trend follower. It’s going to get chopped out in a range bound market. By turning on the Range mode you will at least see profitable trades while stuck in the range. However, when the market eventually picks a direction, this mode will sustain losses. This range trading mode is a rudimentary implementation that will need a lot of improvement if you want to create a reliable switch hitter (trend/range combo).
7. No Trade. Useful when setting up the trend lines and the entry and exit is not important.
Once in the trade, long or short, the script tests the exit condition on every bar. If not a profitable exit then it checks if a pyramid is required. As mentioned earlier, the entry setups are quite primitive. Although they can easily be replaced by more sophisticated algorithms, what I really wanted to show is the diminished role of the position entry in the overall life of the trade. Professional traders spend much more time on the management of the trade beyond the market entry. While your trade entry is important, you can get in almost anywhere and still land a profitable exit.
If DCA is enabled, the size of the position will increase in response to consecutive losses. The number of times the position can increase is limited by the number set in Maximum DCA Increments of Section 1. Once the position breaks the losing streak the trade size will return the default quantity set in the Properties tab. It should be noted that the Initial Capital amount set in the Properties tab does not affect the simulation in the same way as a real account. In reality, running out of money will certainly halt trading. In fact, your account would be frozen long before the last penny was committed to a trade. On the other hand, TradingView will keep running the simulation until the current bar even if your funds have been technically depleted.
Entry and exit use the strategy.entry and strategy.exit calls respectfully. The alert_message parameter has special keywords that the endpoint expects to properly calculate position size and message sequence. The alert message will embed these keywords in the JSON object through the {{strategy.order.alert_message}} placeholder. You should use whatever keywords are expected from the endpoint you intend to webhook in to.
Webhook Integration
The TradingView alerts dialog provides a way to connect your script to an external system which could actually execute your trade. This is a fantastic feature that enables you to separate the data feed and technical analysis from the execution and reporting systems. Using this feature it is possible to create a fully automated trading system entirely on the cloud. Of course, there is some work to get it all going in a reliable fashion. Being a strategy type script place holders such as {{strategy.position_size}} can be embedded in the alert message text. There are more than 10 variables which can write internal script values into the message for delivery to the specified endpoint.
Entry and exit use the strategy.entry and strategy.exit calls respectfully. The alert_message parameter has special keywords that my endpoint expects to properly calculate position size and message sequence. The alert message will embed these keywords in the JSON object through the {{strategy.order.alert_message}} placeholder. You should use whatever keywords are expected from the endpoint you intend to webhook in to.
Here is an excerpt of the fields I use in my webhook signal:
"broker_id": "kraken",
"account_id": "XXX XXXX XXXX XXXX",
"symbol_id": "XMRUSD",
"action": "{{strategy.order.action}}",
"strategy": "{{strategy.order.id}}",
"lots": "{{strategy.order.contracts}}",
"price": "{{strategy.order.price}}",
"comment": "{{strategy.order.alert_message}}",
"timestamp": "{{time}}"
Though TradingView does a great job in dispatching your alert this feature does come with a few idiosyncrasies. Namely, a single transaction call in your script may cause multiple transmissions to the endpoint. If you are using placeholders each message describes part of the transaction sequence. A good example is closing a pyramid stack. Although the script makes a single strategy.close() call, the endpoint actually receives a close message for each pyramid trade. The broker, on the other hand, only requires a single close. The incongruity of this situation is exacerbated by the possibility of messages being received out of sequence. Depending on the type of order designated in the message, a close or a reversal. This could have a disastrous effect on your live account. This broker simulator has no idea what is actually going on at your real account. Its just doing the job of running the simulation and sending out the computed results. If your TradingView simulation falls out of alignment with the actual trading account lots of really bad things could happen. Like your script thinks your are currently long but the account is actually short. Reversals from this point forward will always be wrong with no one the wiser. Human intervention will be required to restore congruence. But how does anyone find out this is occurring? In closed systems engineering this is known as entropy. In practice your webhook logic should be robust enough to detect these conditions. Be generous with the placeholder usage and give the webhook code plenty of information to compare states. Both issuer and receiver. Don’t blindly commit incoming signals without verifying system integrity.
Setup
The following steps provide a very brief set of instructions that will get you started on your first configuration. After you’ve gone through the process a couple of times, you won’t need these anymore. It’s really a simple script after all. I have several example configurations that I used to create the performance charts shown. I can share them with you if you like. Of course, if you’ve modified the code then these steps are probably obsolete.
There are 47 inputs divided into seven sections. For the most part, the configuration process is designed to flow from top to bottom. Handy, tool tips are available on every field to help get you through the initial setup.
Step 1. Input the Base Currency and Order Size in the Properties tab. Set the Pyramiding value to zero.
Step 2. Select the Trading Mode you intend to test with from the drop down in Section 1. I usually select No Trade until I’ve setup all of the trend lines, profit and stop levels.
Step 3. Put in your Minimum Profit and Stop Loss in the first section. This is in pips or currency basis points (chart right side scale). Remember that the profit is taken as a conditional exit not a fixed limit. The actual profit taken will almost always be greater than the amount specified. The stop loss, on the other hand, is indeed a hard number which is executed by the TradingView broker simulator when the threshold is breached.
Step 4. Apply the appropriate value to the Tick Scalar field in Section 1. This value is used to remove the pipette from the price. You can enable the Summary Report in Section 7 to see the TradingView minimum tick size of the current chart.
Step 5. Apply the appropriate Price Normalizer value in Section 1. This value is used to normalize the instrument price for differential calculations. Basically, we want to increase the magnitude to significant digits to make the numbers more meaningful in comparisons. Though I have used many normalization techniques, I have always found this method to provide a simple and lightweight solution for less demanding applications. Most of the time the default value will be sufficient. The Tick Scalar and Price Normalizer value work together within a single calculation so changing either will affect all delta result values.
Step 6. Turn on the trend line plots in Section 7. Then configure Section 2. Try to get the plots to show you what’s really happening not what you want to happen. The most important is the purple trend line. Select an interval and length that seem to identify where prices tend to go during non-consolidation periods. Remember that a natural exit is when the blue crosses the green line.
Step 7. Enable Show Event Regions in Section 7. Then adjust Section 6. Blue background fills are spikes and red fills are plunging prices. These measurements should be hard to come by so you should see relatively few fills on the chart if you’ve set this up as intended. Section 6 includes the Zscore oscillator the state of which combines with the signal lines to detect statistically significant price movement. The Zscore is a zero based calculation with positive and negative magnitude readings. You want to input a reasonably large number slightly below the maximum amplitude seen on the chart. Both rise and fall inputs are entered as a positive real number. You can easily use my code to create a separate indicator if you want to see it in action. The default value is sufficient for most configurations.
Step 8. Turn off Show Event Regions and enable Show Entry Regions in Section 7. Then adjust Section 3. This section contains two parts. The entry setup crossovers and EMA events. Adjust the crossovers first. That is the Fast Cross Length and Slow Cross Length. The frequency of your trades will be shown as blue and red fills. There should be a lot. Then turn off Show Event Regions and enable Display EMA Peaks. Adjust all the fields that have the word EMA. This is actually the yellow line on the chart. The blue and red fills should show much less than the crossovers but more than event fills shown in Step 7.
Step 9. Change the Trading Mode to BiDir if you selected No Trades previously. Look on the chart and see where the trades are occurring. Make adjustments to the Minimum Profit and Stop Offset in Section 1 if necessary. Wider profits and stops reduce the trade frequency.
Step 10. Go to Section 4 and 5 and make fine tuning adjustments to the long and short side.
Example Settings
To reproduce the performance shown on the chart please use the following configuration: (Bitcoin on the Kraken exchange)
1. Select XBTUSD Kraken as the chart symbol.
2. On the properties tab set the Order Size to: 0.01 Bitcoin
3. On the properties tab set the Pyramiding to: 12
4. In Section 1: Select “Crypto” for the Trading Model
5. In Section 1: Input 2000 for the Minimum Profit
6. In Section 1: Input 0 for the Stop Offset (No Stop)
7. In Section 1: Input 10 for the Tick Scalar
8. In Section 1: Input 1000 for the Price Normalizer
9. In Section 1: Input 2000 for the Pyramid Minimum Span
10. In Section 1: Check mark the Position Bale Out
11. In Section 2: Input 60 for the Signal Line Period
12. In Section 2: Input 1440 for the Trend Line Period
13. In Section 2: Input 5 for the Fast Alma Length
14. In Section 2: Input 22 for the Fast LinReg Length
15. In Section 2: Input 100 for the Slow LinReg Length
16. In Section 2: Input 90 for the Trend Line Length
17. In Section 2: Input 14 Stochastic Length
18. In Section 3: Input 9 Fast Cross Length
19. In Section 3: Input 24 Slow Cross Length
20. In Section 3: Input 8 Fast EMA Length
21. In Section 3: Input 10 Fast EMA Rise NetChg
22. In Section 3: Input 1 Fast EMA Rise ROC
23. In Section 3: Input 10 Fast EMA Fall NetChg
24. In Section 3: Input 1 Fast EMA Fall ROC
25. In Section 4: Check mark the Long Natural Exit
26. In Section 4: Check mark the Long Signal Exit
27. In Section 4: Check mark the Long Price Event Exit
28. In Section 4: Check mark the Long Stochastic Exit
29. In Section 5: Check mark the Short Natural Exit
30. In Section 5: Check mark the Short Signal Exit
31. In Section 5: Check mark the Short Price Event Exit
32. In Section 5: Check mark the Short Stochastic Exit
33. In Section 6: Input 120 Rise Event NetChg
34. In Section 6: Input 1 Rise Event ROC
35. In Section 6: Input 5 Min Above Zero ZScore
36. In Section 6: Input 120 Fall Event NetChg
37. In Section 6: Input 1 Fall Event ROC
38. In Section 6: Input 5 Min Below Zero ZScore
In this configuration we are trading in long only mode and have enabled downward pyramiding. The purple trend line is based on the day (1440) period. The length is set at 90 days so it’s going to take a while for the trend line to alter course should this symbol decide to node dive for a prolonged amount of time. Your trades will still go long under those circumstances. Since downward accumulation is enabled, your position size will grow on the way down.
The performance example is Bitcoin so we assume the trader is buying coins outright. That being the case we don’t need a stop since we will never receive a margin call. New buy signals will be generated when the price exceeds the magnitude and speed defined by the Event Net Change and Rate of Change.
Feel free to PM me with any questions related to this script. Thank you and happy trading!
CFTC RULE 4.41
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
The Flash-Strategy with Minervini Stage Analysis QualifierThe Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) with Minervini Stage Analysis Qualifier
Introduction
Welcome to a comprehensive guide on a cutting-edge trading strategy I've developed, designed for the modern trader seeking an edge in today's dynamic markets. This strategy, which I've honed through my years of experience in the trading arena, stands out for its unique blend of technical analysis and market intuition, tailored specifically for use on the TradingView platform.
As a trader with a deep passion for the financial markets, my journey began several years ago, driven by a relentless pursuit of a trading methodology that is both effective and adaptable. My background in trading spans various market conditions and asset classes, providing me with a rich tapestry of experiences from which to draw. This strategy is the culmination of that journey, embodying the lessons learned and insights gained along the way.
The cornerstone of this strategy lies in its ability to generate precise long signals in a Stage 2 uptrend and equally accurate short signals in a Stage 4 downtrend. This approach is rooted in the principles of trend following and momentum trading, harnessing the power of key indicators such as the Momentum-RSI, EMA Crossover, and Average True Range (ATR). What sets this strategy apart is its meticulous design, which allows it to adapt to the ever-changing market conditions, providing traders with a robust tool for navigating both bullish and bearish scenarios.
This strategy was born out of a desire to create a trading system that is not only highly effective in identifying potential trade setups but also straightforward enough to be implemented by traders of varying skill levels. It's a reflection of my belief that successful trading hinges on clarity, precision, and disciplined execution. Whether you are a seasoned trader or just beginning your journey, this guide aims to provide you with a comprehensive understanding of how to harness the full potential of this strategy in your trading endeavors.
In the following sections, we will delve deeper into the mechanics of the strategy, its implementation, and how to make the most out of its features. Join me as we explore the nuances of a strategy that is designed to elevate your trading to the next level.
Stage-Specific Signal Generation
A distinctive feature of this trading strategy is its focus on generating long signals exclusively during Stage 2 uptrends and short signals during Stage 4 downtrends. This approach is based on the widely recognized market cycle theory, which divides the market into four stages: Stage 1 (accumulation), Stage 2 (uptrend), Stage 3 (distribution), and Stage 4 (downtrend). By aligning the signal generation with these specific stages, the strategy aims to capitalize on the most dynamic and clear-cut market movements, thereby enhancing the potential for profitable trades.
1. Long Signals in Stage 2 Uptrends
• Characteristics of Stage 2: Stage 2 is characterized by a strong uptrend, where prices are consistently rising. This stage typically follows a period of accumulation (Stage 1) and is marked by increased investor interest and bullish sentiment in the market.
• Criteria for Long Signal Generation: Long signals are generated during this stage when the technical indicators align with the characteristics of a Stage 2 uptrend.
• Rationale for Stage-Specific Signals: By focusing on Stage 2 for long trades, the strategy seeks to enter positions during the phase of strong upward momentum, thus riding the wave of rising prices and investor optimism. This stage-specific approach minimizes exposure to less predictable market phases, like the consolidation in Stage 1 or the indecision in Stage 3.
2. Short Signals in Stage 4 Downtrends
• Characteristics of Stage 4: Stage 4 is identified by a pronounced downtrend, with declining prices indicating prevailing bearish sentiment. This stage typically follows the distribution phase (Stage 3) and is characterized by increasing selling pressure.
• Criteria for Short Signal Generation: Short signals are generated in this stage when the indicators reflect a strong bearish trend.
• Rationale for Stage-Specific Signals: Targeting Stage 4 for shorting capitalizes on the market's downward momentum. This tactic aligns with the natural market cycle, allowing traders to exploit the downward price movements effectively. By doing so, the strategy avoids the potential pitfalls of shorting during the early or late stages of the market cycle, where trends are less defined and more susceptible to reversals.
In conclusion, the strategy’s emphasis on stage-specific signal generation is a testament to its sophisticated understanding of market dynamics. By tailoring the long and short signals to Stages 2 and 4, respectively, it leverages the most compelling phases of the market cycle, offering traders a clear and structured approach to aligning their trades with dominant market trends.
Strategy Overview
At the heart of this trading strategy is a philosophy centered around capturing market momentum and trend efficiency. The core objective is to identify and capitalize on clear uptrends and downtrends, thereby allowing traders to position themselves in sync with the market's prevailing direction. This approach is grounded in the belief that aligning trades with these dominant market forces can lead to more consistent and profitable outcomes.
The strategy is built on three foundational components, each playing a critical role in the decision-making process:
1. Momentum-RSI (Relative Strength Index): The Momentum-RSI is a pivotal element of this strategy. It's an enhanced version of the traditional RSI, fine-tuned to better capture the strength and velocity of market trends. By measuring the speed and change of price movements, the Momentum-RSI provides invaluable insights into whether a market is potentially overbought or oversold, suggesting possible entry and exit points. This indicator is especially effective in filtering out noise and focusing on substantial market moves.
2. EMA (Exponential Moving Average) Crossover: The EMA Crossover is a crucial component for trend identification. This strategy employs two EMAs with different timeframes to determine the market trend. When the shorter-term EMA crosses above the longer-term EMA, it signals an emerging uptrend, suggesting a potential long entry. Conversely, a crossover below indicates a possible downtrend, hinting at a short entry opportunity. This simple yet powerful tool is key in confirming trend directions and timing market entries.
3. ATR (Average True Range): The ATR is instrumental in assessing market volatility. This indicator helps in understanding the average range of price movements over a given period, thus providing a sense of how much a market might move on a typical day. In this strategy, the ATR is used to adjust stop-loss levels and to gauge the potential risk and reward of trades. It allows for more informed decisions by aligning trade management techniques with the current volatility conditions.
The synergy of these three components – the Momentum-RSI, EMA Crossover, and ATR – creates a robust framework for this trading strategy. By combining momentum analysis, trend identification, and volatility assessment, the strategy offers a comprehensive approach to navigating the markets. Whether it's capturing a strong trend in its early stages or identifying a potential reversal, this strategy aims to provide traders with the tools and insights needed to make well-informed, strategically sound trading decisions.
Detailed Component Analysis
The efficacy of this trading strategy hinges on the synergistic functioning of its three key components: the Momentum-RSI, EMA Crossover, and Average True Range (ATR). Each component brings a unique perspective to the strategy, contributing to a well-rounded approach to market analysis.
1. Momentum-RSI (Relative Strength Index)
• Definition and Function: The Momentum-RSI is a modified version of the classic Relative Strength Index. While the traditional RSI measures the velocity and magnitude of directional price movements, the Momentum-RSI amplifies aspects that reflect trend strength and momentum.
• Significance in Identifying Trend Strength: This indicator excels in identifying the strength behind a market's move. A high Momentum-RSI value typically indicates strong bullish momentum, suggesting the potential continuation of an uptrend. Conversely, a low Momentum-RSI value signals strong bearish momentum, possibly indicative of an ongoing downtrend.
• Application in Strategy: In this strategy, the Momentum-RSI is used to gauge the underlying strength of market trends. It helps in filtering out minor fluctuations and focusing on significant movements, providing a clearer picture of the market's true momentum.
2. EMA (Exponential Moving Average) Crossover
• Definition and Function: The EMA Crossover component utilizes two exponential moving averages of different timeframes. Unlike simple moving averages, EMAs give more weight to recent prices, making them more responsive to new information.
• Contribution to Market Direction: The interaction between the short-term and long-term EMAs is key to determining market direction. A crossover of the shorter EMA above the longer EMA is an indicator of an emerging uptrend, while a crossover below signals a developing downtrend.
• Application in Strategy: The EMA Crossover serves as a trend confirmation tool. It provides a clear, visual representation of the market's direction, aiding in the decision-making process for entering long or short positions. This component ensures that trades are aligned with the prevailing market trend, a crucial factor for the success of the strategy.
3. ATR (Average True Range)
• Definition and Function: The ATR is an indicator that measures market volatility by calculating the average range between the high and low prices over a specified period.
• Role in Assessing Market Volatility: The ATR provides insights into the typical market movement within a given timeframe, offering a measure of the market's volatility. Higher ATR values indicate increased volatility, while lower values suggest a calmer market environment.
• Application in Strategy: Within this strategy, the ATR is instrumental in tailoring risk management techniques, particularly in setting stop-loss levels. By accounting for the market's volatility, the ATR ensures that stop-loss orders are placed at levels that are neither too tight (risking premature exits) nor too loose (exposing to excessive risk).
In summary, the combination of Momentum-RSI, EMA Crossover, and ATR in this trading strategy provides a comprehensive toolkit for market analysis. The Momentum-RSI identifies the strength of market trends, the EMA Crossover confirms the market direction, and the ATR guides in risk management by assessing volatility. Together, these components form the backbone of a strategy designed to navigate the complexities of the financial markets effectively.
1. Signal Generation Process
• Combining Indicators: The strategy operates by synthesizing signals from the Momentum-RSI, EMA Crossover, and ATR indicators. Each indicator serves a specific purpose: the Momentum-RSI gauges trend momentum, the EMA Crossover identifies the trend direction, and the ATR assesses the market’s volatility.
• Criteria for Signal Validation: For a signal to be considered valid, it must meet specific criteria set by each of the three indicators. This multi-layered approach ensures that signals are not only based on one aspect of market behavior but are a result of a comprehensive analysis.
2. Conditions for Long Positions
• Uptrend Confirmation: A long position signal is generated when the shorter-term EMA crosses above the longer-term EMA, indicating an uptrend.
• Momentum-RSI Alignment: Alongside the EMA crossover, the Momentum-RSI should indicate strong bullish momentum. This is typically represented by the Momentum-RSI being at a high level, confirming the strength of the uptrend.
• ATR Consideration: The ATR is used to fine-tune the entry point and set an appropriate stop-loss level. In a low volatility scenario, as indicated by the ATR, the stop-loss can be set tighter, closer to the entry point.
3. Conditions for Short Positions
• Downtrend Confirmation: Conversely, a short position signal is indicated when the shorter-term EMA crosses below the longer-term EMA, signaling a downtrend.
• Momentum-RSI Confirmation: The Momentum-RSI should reflect strong bearish momentum, usually seen when the Momentum-RSI is at a low level. This confirms the bearish strength of the market.
• ATR Application: The ATR again plays a role in determining the stop-loss level for the short position. Higher volatility, as indicated by a higher ATR, would warrant a wider stop-loss to accommodate larger market swings.
By adhering to these mechanics, the strategy aims to ensure that each trade is entered with a high probability of success, aligning with the market’s current momentum and trend. The integration of these indicators allows for a holistic market analysis, providing traders with clear and actionable signals for both entering and exiting trades.
Customizable Parameters in the Strategy
Flexibility and adaptability are key features of this trading strategy, achieved through a range of customizable parameters. These parameters allow traders to tailor the strategy to their individual trading style, risk tolerance, and specific market conditions. By adjusting these parameters, users can fine-tune the strategy to optimize its performance and align it with their unique trading objectives. Below are the primary parameters that can be customized within the strategy:
1. Momentum-RSI Settings
• Period: The lookback period for the Momentum-RSI can be adjusted. A shorter period makes the indicator more sensitive to recent price changes, while a longer period smoothens the RSI line, offering a broader view of the momentum.
• Overbought/Oversold Thresholds: Users can set their own overbought and oversold levels, which can help in identifying extreme market conditions more precisely according to their trading approach.
2. EMA Crossover Settings
• Timeframes for EMAs: The strategy uses two EMAs with different timeframes. Traders can modify these timeframes, choosing shorter periods for a more responsive approach or longer periods for a more conservative one.
• Source Data: The choice of price data (close, open, high, low) used in calculating the EMAs can be varied depending on the trader’s preference.
3. ATR Settings
• Lookback Period: Adjusting the lookback period for the ATR impacts how the indicator measures volatility. A longer period may provide a more stable but less responsive measure, while a shorter period offers quicker but potentially more erratic readings.
• Multiplier for Stop-Loss Calculation: This parameter allows traders to set how aggressively or conservatively they want their stop-loss to be in relation to the ATR value.
Here are the standard settings:
RDBRB Strategy with Filters + Cooldowns + LabelsRDBRB Strategy with Filters + Cooldowns
This script implements the RDBRB (Rally-Drop-Base-Retest-Breakout) strategy, a classic price action setup designed to identify structured trade opportunities using volume, volatility bands, and trend alignment. It’s ideal for traders looking for clean, rule-based entries across any timeframe.
🧠 Core Components
Rally & Drop Detection
Identifies short-term momentum shifts using moving average crossovers:
✅ Ra = Rally (bullish crossover)
🔻 Dr = Drop (bearish crossunder)
Base Formation
A statistical base is defined using a moving average with a standard deviation envelope (Upper/Lower BB). This forms the foundation for breakout or retest setups.
Retest Zone (RT)
When price returns to the lower band (but stays below the base), it suggests a potential re-accumulation or reaction zone before a breakout.
Breakout Confirmation (BO)
A breakout is validated when:
Price crosses above the upper band
Volume exceeds the 20-bar average by a threshold multiplier
RSI is above a bullish momentum level
Price is trending above the longer-term EMA
⏱️ Smart Cooldown Logic
Each signal (Rally, Drop, Retest, Breakout) has an independent cooldown timer to prevent multiple triggers within a short range, filtering out noise and duplicate signals:
Customizable cooldown periods via input settings
Ensures signals are meaningful and not clustered
💡 Visual Markers
All signals are shown as small, color-coded labels:
Ra : Green label below bar
Dr : Red label above bar
RT : Yellow label below bar
BO : Green breakout label below bar
Bands and base are plotted for structure reference.
🛠️ Customizable Settings
Cooldown periods for each signal type
MA lengths, volume and RSI thresholds
Trend filter and base calculation inputs
This script is ideal for price action traders who want a clean, structured method to trade consolidations and trend continuations while avoiding over-signaling. Use it on any timeframe and combine with higher-timeframe confirmation for best results.
Multi-Symbol Trend DashboardMulti-Symbol Trend Dashboard - MA Cross Trend Monitor
Short Description
A customizable dashboard that displays trend direction across multiple symbols and timeframes using moving average crossovers.
Full Description
Overview
This Multi-Symbol Trend Dashboard allows you to monitor trend direction across 7 different symbols and 5 timeframes simultaneously in a single view. The dashboard uses moving average crossovers to determine trend direction, displaying bullish trends in green and bearish trends in red.
Key Features
Multi-Symbol Monitoring : Track up to 7 different trading instruments at once
Multi-Timeframe Analysis: View 5 different timeframes simultaneously for each instrument
Customizable Moving Averages: Choose between SMA, EMA, or WMA with adjustable periods
Visual Clarity: Color-coded cells provide immediate trend identification
Flexible Positioning: Place the dashboard anywhere on your chart
Customizable Appearance: Adjust sizes, colors, and text formatting
How It Works
The dashboard calculates a fast MA and slow MA for each symbol-timeframe combination. When the fast MA is above the slow MA, the cell shows green (bullish). When the fast MA is below the slow MA, the cell shows red (bearish).
Use Cases
Get a bird's-eye view of market trends across multiple instruments
Identify potential trading opportunities where multiple timeframes align
Monitor your watchlist without switching between charts
Spot divergences between related instruments
Track market breadth across sectors or related instruments
Notes and Limitations
Limited to 7 symbols and 5 timeframes due to TradingView's security request limits
Uses simple MA crossover as trend determination method
Dashboard is most effective when displayed on a dedicated chart
Performance may vary on lower-end devices due to multiple security requests
Settings Explanation
MA Settings: Configure the periods and types of moving averages
Display Settings: Adjust dashboard positioning and visual elements
Trading Instruments: Select which symbols to monitor (defaults to major forex pairs)
Timeframes: Choose which timeframes to display (default: M15, H1, H4, D1, W1)
Colors: Customize the color scheme for bullish/bearish indications and headers
This dashboard provides a straightforward way to maintain situational awareness across multiple markets and timeframes, helping traders identify potential setups and market conditions at a glance.
Dual Momentum OSCOverview:
Momentum OSC is a dual-layered momentum oscillator that blends multi-timeframe momentum readings with moving average crossovers for deeper insight into trend acceleration and exhaustion. Perfect for confirming trend strength or spotting early shifts in momentum.
Features:
✅ Two separate momentum streams with customizable timeframes
✅ Smoothing via moving averages for both momenta
✅ Cross-timeframe momentum structure for confirmation and divergence
✅ Color-coded areas for intuitive visual interpretation
✅ Optional crossover markers to signal bullish/bearish momentum shifts
How It Works:
The script calculates two momentum values by comparing current price sources against lagged values across separate timeframes. Each is smoothed with a moving average to filter noise. The difference between momentum and its moving average forms a core component of trend strength confirmation. Optional visual circles mark bullish or bearish crossovers.
Customizable Inputs:
Timeframes, sources, lengths, and MA periods for both momentum streams
Toggle to display momentum cross signals (circles)
Works on any asset or timeframe
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
Moving Average Multitool CrossoverAs per request, this is a moving average crossover version of my original moving average multitool script .
It allows you to easily access and switch between different types of moving averages, without having to continuously add and remove different moving averages from your chart. This should make backtesting moving average crossovers much, much more easier. It also has the option to show buy and sell signals for the crossovers of the chosen moving averages.
It contains the following moving averages:
Exponential Moving Average (EMA)
Simple Moving Average (SMA)
Weighted Moving Average (WMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Triangular Moving Average (TMA)
Volume-Weighted Moving Average (VWMA)
Smoothed Moving Average (SMMA)
Hull Moving Average (HMA)
Least Squares Moving Average (LSMA)
Kijun-Sen line from the Ichimoku Kinko-Hyo system (Kijun)
McGinley Dynamic (MD)
Rolling Moving Average (RMA)
Jurik Moving Average (JMA)
Arnaud Legoux Moving Average (ALMA)
Vector Autoregression Moving Average (VAR)
Welles Wilder Moving Average (WWMA)
Sine Weighted Moving Average (SWMA)
Leo Moving Average (LMA)
Variable Index Dynamic Average (VIDYA)
Fractal Adaptive Moving Average (FRAMA)
Variable Moving Average (VAR)
Geometric Mean Moving Average (GMMA)
Corrective Moving Average (CMA)
Moving Median (MM)
Quick Moving Average (QMA)
Kaufman's Adaptive Moving Average (KAMA)
Volatility-Adjusted Moving Average (VAMA)
Modular Filter (MF)
HMA-Crossover AlertsThis simple script plots bullish and bearish Hull Moving Average Crossovers and fires Alerts when long or short conditions are met.
Varanormal Mac N Cheez Strategy v1Mac N Cheez Strategy (Set a $200 Take profit Manually)
It's super cheesy. Strategy does the following:
Here's a detailed explanation of what the entire script does, including its key components, functionality, and purpose.
1. Strategy Setup and Input Parameters:
Strategy Name: The script is named "NQ Futures $200/day Strategy" and is set as an overlay, meaning all elements (like moving averages and signals) are plotted on the price chart.
Input Parameters:
fastLength: This sets the length of the fast moving average. The user can adjust this value, and it defaults to 9.
slowLength: This sets the length of the slow moving average. The user can adjust this value, and it defaults to 21.
dailyTarget: The daily profit target, which defaults to $200. If set to 0, this disables the daily profit target.
stopLossAmount: The fixed stop-loss amount per trade, defaulting to $100. This value is used to calculate how much you're willing to lose on a single trade.
trailOffset: This value sets the distance for a trailing stop. It helps protect profits by automatically adjusting the stop-loss as the price moves in your favor.
2. Calculating the Moving Averages:
fastMA: The fast moving average is calculated using the ta.sma() function on the close price with a period length of fastLength. The ta.sma() function calculates the simple moving average.
slowMA: The slow moving average is also calculated using ta.sma() but with the slowLength period.
These moving averages are used to determine trend direction and identify entry points.
3. Buy and Sell Signal Conditions:
longCondition: This is the buy condition. It occurs when the fast moving average crosses above the slow moving average. The script uses ta.crossover() to detect this crossover event.
shortCondition: This is the sell condition. It occurs when the fast moving average crosses below the slow moving average. The script uses ta.crossunder() to detect this crossunder event.
4. Executing Buy and Sell Orders:
Buy Orders: When the longCondition is true (i.e., fast MA crosses above slow MA), the script enters a long position using strategy.entry("Buy", strategy.long).
Sell Orders: When the shortCondition is true (i.e., fast MA crosses below slow MA), the script enters a short position using strategy.entry("Sell", strategy.short).
5. Setting Stop Loss and Trailing Stop:
Stop-Loss for Long Positions: The stop-loss is calculated as the entry price minus the stopLossAmount. If the price falls below this level, the trade is exited automatically.
Stop-Loss for Short Positions: The stop-loss is calculated as the entry price plus the stopLossAmount. If the price rises above this level, the short trade is exited.
Trailing Stop: The trail_offset dynamically adjusts the stop-loss as the price moves in favor of the trade, locking in profits while still allowing room for market fluctuations.
6. Conditional Daily Profit Target:
The script includes a daily profit target that automatically closes all trades once the total profit for the day reaches or exceeds the dailyTarget.
Conditional Logic:
If the dailyTarget is greater than 0, the strategy checks whether the strategy.netprofit (total profit for the day) has reached or exceeded the target.
If the strategy.netprofit >= dailyTarget, the script calls strategy.close_all(), closing all open trades for the day and stopping further trading.
If dailyTarget is set to 0, this logic is skipped, and the script continues trading without a daily profit target.
7. Plotting Moving Averages:
plot(fastMA): This plots the fast moving average as a blue line on the price chart.
plot(slowMA): This plots the slow moving average as a red line on the price chart. These help visualize the crossover points and the trend direction on the chart.
8. Plotting Buy and Sell Signals:
plotshape(): The script uses plotshape() to add visual markers when buy or sell conditions are met:
"Long Signal": When a buy condition (longCondition) is met, a green marker is plotted below the price bar with the label "Long".
"Short Signal": When a sell condition (shortCondition) is met, a red marker is plotted above the price bar with the label "Short".
These markers help traders quickly see when buy or sell signals occurred on the chart.
In addition, triangle markers are plotted:
Green Triangle: Indicates where a buy entry occurred.
Red Triangle: Indicates where a sell entry occurred.
Summary of What the Script Does:
Inputs: The script allows the user to adjust moving average lengths, daily profit targets, stop-loss amounts, and trailing stop offsets.
Signals: It generates buy and sell signals based on the crossovers of the fast and slow moving averages.
Order Execution: It executes long positions on buy signals and short positions on sell signals.
Stop-Loss and Trailing Stop: It sets dynamic stop-losses and uses a trailing stop to protect profits.
Daily Profit Target: The strategy stops trading for the day once the net profit reaches the daily target (unless the target is disabled by setting it to 0).
Visual Markers: It plots moving averages and buy/sell signals directly on the main price chart to aid in visual analysis.
This script is designed to trade based on moving average crossovers, with robust risk management features like stop-loss and trailing stops, along with an optional daily profit target to limit daily trading activity. Let me know if you need further clarification or want to adjust any specific part of the script!
Normalized Volume Rate of ChangeThis indicator is designed to help traders gauge changes in volume dynamics and identify potential shifts in buying or selling pressure. By normalizing the volume rate of change and comparing it to moving averages of itself, it offers valuable insights into market trends and can assist in making informed trading decisions.
Calculation:
The indicator calculates the Volume Rate of Change (VROC) by measuring the percentage change in volume over a specified length. This calculation provides a relative measure of how quickly the volume is increasing or decreasing. It then normalizes the VROC to a range of -1 to +1 by scaling it based on the highest and lowest values observed within the specified length. This normalization allows for easy comparison of the current VROC value with historical levels, enabling traders to assess the intensity of volume fluctuations.
Interpretation:
The main plot of the indicator displays the normalized VROC values as columns. The color of each column provides valuable information about the relationship between the VROC and the moving averages. Lime-colored columns indicate that the VROC is above both moving averages, suggesting increased buying pressure and potential bullish sentiment. Conversely, fuchsia-colored columns indicate that the VROC is below both moving averages, suggesting increased selling pressure and potential bearish sentiment. Yellow-colored columns indicate that the VROC is between the two moving averages, reflecting a period of consolidation or indecision in the market.
To further enhance interpretation, the indicator includes two moving averages. The Aqua line represents the faster moving average (MA1), and the Orange line represents the slower moving average (MA2). These moving averages provide additional context by smoothing out the VROC values and highlighting the overall trend. Traders can observe the interaction between the moving averages and the VROC to identify potential crossovers and assess the strength of trend reversals or continuations.
Colors:
-- Lime : The lime color is used to represent high volume rate of change above both moving averages. This color indicates a potentially bullish market sentiment, suggesting that buyers are dominant.
-- Fuchsia : The fuchsia color is used to represent low volume rate of change below both moving averages. This color indicates a potentially bearish market sentiment, suggesting that sellers are dominant.
-- Yellow : The yellow color is used to represent the volume rate of change between the two moving averages. This color reflects a transitional phase where neither buyers nor sellers have a clear advantage, signaling a period of consolidation or indecision in the market.
To provide additional visual cues for potential trade signals, the indicator includes lime-colored arrows below the price chart when there is a crossover upwards (MA1 crossing above MA2). This lime arrow indicates a potential bullish signal, suggesting a favorable time to consider long positions. Similarly, fuchsia-colored arrows are displayed above the price chart when there is a crossover downwards (MA1 crossing below MA2), signaling a potential bearish signal and suggesting a favorable time to consider short positions.
Applications:
This indicator offers various applications in trading strategies, including:
-- Trend Identification : By observing the relationship between the normalized VROC and the moving averages, traders can identify potential shifts in market trends. Lime-colored columns above both moving averages indicate a strong bullish trend, suggesting an opportunity to capitalize on upward price movements. Conversely, fuchsia-colored columns below both moving averages indicate a strong bearish trend, suggesting an opportunity to profit from downward price movements. Yellow-colored columns between the moving averages indicate a period of consolidation or uncertainty, signaling a potential trend reversal or continuation.
-- Confirmation of Price Moves : The indicator's ability to reflect volume dynamics in relation to the moving averages can help traders validate price moves. When significant price movements are accompanied by lime-colored columns (indicating high volume rate of change above both moving averages), it adds confirmation to the bullish sentiment. Similarly, fuchsia-colored columns accompanying downward price movements validate the bearish sentiment. This confirmation can enhance traders' confidence in the reliability of price moves.
-- Trade Timing : The indicator's moving average crossovers and the presence of arrows provide timing signals for trade entries and exits. Lime arrows appearing below the price chart signal potential long entry opportunities, indicating a bullish market sentiment. Conversely, fuchsia arrows appearing above the price chart suggest potential short entry opportunities, indicating a bearish market sentiment. These signals can be used in conjunction with other technical analysis tools to improve trade timing and increase the probability of successful trades.
Parameter Adjustments:
Traders can adjust the length of the VROC and the moving averages according to their trading preferences and timeframes. Longer VROC lengths provide a broader view of volume dynamics over an extended period, making it suitable for assessing long-term trends. Shorter VROC lengths offer a more sensitive measure of recent volume changes, making it suitable for shorter-term analysis. Similarly, adjusting the lengths of the moving averages can help adapt the indicator to different market conditions and trading styles.
Limitations:
While the indicator provides valuable insights, it has some limitations that traders should be aware of:
-- False Signals : Like any technical indicator, false signals can occur. During periods of low liquidity or in choppy markets, the indicator may generate misleading signals. It is essential to consider other indicators, price action, and fundamental analysis to confirm the signals before taking any trading actions.
-- Lagging Nature : Moving averages inherently lag behind the price action and volume changes. As a result, there may be a delay in the generation of signals and capturing trend reversals. Traders should exercise patience and avoid solely relying on this indicator for immediate trade decisions. Combining it with other indicators and tools can provide a more comprehensive picture of market conditions.
In conclusion, this indicator offers valuable insights into volume dynamics and trend analysis. By comparing the normalized VROC with moving averages, traders can identify shifts in buying or selling pressure, validate price moves, and improve trade timing. However, it is important to consider its limitations and use it in conjunction with other technical analysis tools to form a well-rounded trading strategy. Additionally, thorough testing, experimentation, and customization of the indicator's parameters are recommended to align it with individual trading preferences and market conditions.
Win-Loss Streak PlotterWin-Loss Streak Plotter
This indicator tracks the win/loss streaks of moving average crossovers (using simple moving averages for illustration purposes). It calculates the price change after each crossover, marking each as a win (green) or loss (red). The win rate is shown separately.
Inputs:
Source: Price series (default: open)
Fast MA: Fast moving average (default: open)
Slow MA: Slow moving average (default: open)
Total Crosses to Analyze: Number of crossovers to track
Crosses per Row: Number of crossovers per row in the table
Output:
A table displays each crossover’s result (win/loss).
A separate win rate table shows the percentage of wins.
Suggestions are always welcomed!
Amplitude [Anan]The Amplitude indicator calculates and visualizes both the amplitude and cumulative amplitude of price movements, providing traders with insights into price volatility and trend strength. By distinguishing between positive and negative amplitude movements, this indicator aids in identifying bullish and bearish sentiments, potential reversal points, and confirming trend directions.
█ Main Formulas
‣ Amplitude = High - Low
‣ Cumulative Amplitude = sum of Amplitude over the specified lookback period
‣ Percentage Amplitude = (Amplitude / Open) × 100%
High: Candle high (or highest high when lookback > 1)
Low: Candle low (or lowest low when lookback > 1)
Open: Open price of the first candle in the lookback period
█ Key Features
✦Dual Amplitude Calculations:
Amplitude: Reflects price range and direction over a short-term period.
Cumulative Amplitude: Aggregates amplitude over a longer period for broader trend analysis.
✦Customizable Parameters: Adjust lookback periods, smoothing options, moving averages and Alerts.
✦Direction Separation: Distinguish between positive and negative amplitude movements to identify market sentiment.
✦Flexible Visualization: Customizable colors and plot styles for enhanced chart readability.
✦Alert System: Generate signals based on amplitude direction and moving average crossovers
█ How to Use and Interpret
✦Understanding Amplitude and Cumulative Amplitude:
‣Amplitude: Measures the price range (high - low) over a specified short-term period.
‣Cumulative Amplitude: Aggregates amplitude over a defined longer-term period.
‣Percentage Representation: shows amplitude relative to the open price from `amp_length` bars ago, providing a normalized view.
‣Interpretation:
Large Amplitude Values: Indicate high volatility.
Small Amplitude Values: Indicate low volatility.
✦Trend Identification:
‣Uptrend: Consistently positive amplitudes and upward-moving averages.
‣Downtrend: Consistently negative amplitudes and downward-moving averages.
✦Overbought/Oversold Conditions:
‣High Positive Amplitude: May indicate overbought conditions and potential reversals.
‣High Negative Amplitude: May indicate oversold conditions and potential reversals.
✦Volatility Analysis:
‣High Amplitude Values: Suggest increased market volatility.
‣Low Amplitude Values: Suggest reduced market volatility.
✦Signal Confirmation:
‣Moving Average Crossovers: Confirm the strength and direction of trends, aiding in informed trading decisions.
✦Trading Strategies:
‣ Breakout Trading: Large increases in amplitude can signal potential breakouts.
‣ Mean Reversion: Extreme amplitude values may indicate upcoming price corrections.
‣ Volatility-Based Strategies: Adjust position sizes or trading frequency based on amplitude magnitudes.
‣ Multi-Timeframe Analysis: Compare amplitudes across different timeframes for a comprehensive market view.
█ Customization Tips
‣ Lookback Periods: Experiment with different periods to suit your trading style and asset characteristics.
‣ Smoothing Settings: Adjust to balance responsiveness and noise reduction.
‣ Percentage Amplitude: Use for normalized comparisons across different price levels.
Major and Minor Trend Indicator by Nikhil34a V 2.2Title: Major and Minor Trend Indicator by Nikhil34a V 2.2
Description:
The Major and Minor Trend Indicator v2.2 is a comprehensive technical analysis script designed for use with the TradingView platform. This powerful tool is developed in Pine Script version 5 and helps traders identify potential buying and selling opportunities in the stock market.
Features:
SMA Trend Analysis: The script calculates two Simple Moving Averages (SMAs) with user-defined lengths for major and minor trends. It displays these SMAs on the chart, allowing traders to visualize the prevailing trends easily.
Surge Detection: The indicator can detect buying and selling surges based on specific conditions, such as volume, RSI, MACD, and stochastic indicators. Both Buying and Selling surges are marked in black on the chart.
Option Buy Zone Detection: The script identifies the option buy zone based on SMA crossovers, RSI, and MACD values. The buy zone is categorized as "CE Zone" or "PE Zone" and displayed in the table along with the trigger time.
Two-Day High and Low Range: The script calculates the highest high and lowest low of the previous two trading days and plots them on the chart. The area between these points is shaded in semi-transparent green and red colors.
Crossover Analysis: The script analyzes moving average crossovers on multiple timeframes (2-minute, 3-minute, and 5-minute) and displays buy and sell signals accordingly.
Trend Identification: The script identifies the major and minor trends as either bullish or bearish, providing valuable insights into the overall market sentiment.
Usage:
Customize Major and Minor SMA Periods: Adjust the lengths of major and minor SMAs through input parameters to suit your trading preferences.
Enable/Disable Moving Averages: Choose which SMAs to display on the chart by toggling the "showXMA" input options.
Set Surge and Option Buy Zone Thresholds: Modify the surgeThreshold, volumeThreshold, RSIThreshold, and StochThreshold inputs to refine the surge and buy zone detection.
Analyze Crossover Signals: Monitor the crossover signals in the table, categorized by timeframes (2-minute, 3-minute, and 5-minute).
Explore Market Bias and Distance to 2-Day High/Low: The table provides information on market bias, current price movement relative to the previous two-day high and low, and the option buy zone status.
Additional Use Cases:
Surge Indicator:
The script includes a Surge Indicator that detects sudden buying or selling surges in the market. When a buying surge is identified, the "BSurge" label will appear below the corresponding candle with black text on a white background. Similarly, a selling surge will display the "SSurge" label in white text on a black background. These indicators help traders quickly spot strong buying or selling activities that may influence their trading decisions. These surges can be used to identify sudden premium dump zones.
Option Buy Zone:
The Option Buy Zone is an essential feature that identifies potential zones for buying call options (CE Zone) or put options (PE Zone) based on specific technical conditions. The indicator evaluates SMA crossovers, RSI, and MACD values to determine the current market sentiment. When the option buy zone is triggered, the script will display the respective zone ("CE Zone" or "PE Zone") in the table, highlighted with a white background. Additionally, the time when the buy zone was triggered will be shown under the "Option Buy Zone Trigger Time" column.
Price Movement Relative to 2-Day High/Low:
The script calculates the highest high and lowest low of the previous two trading days (high2DaysAgo and low2DaysAgo) and plots these points on the chart. The area between these two points is shaded in semi-transparent green and red colors. The green region indicates the price range between the highpricetoconsider (highest high of the previous two days) and the lower value between highPreviousDay and high2DaysAgo. Similarly, the red region represents the price range between the lowpricetoconsider (lowest low of the previous two days) and the higher value between lowPreviousDay and low2DaysAgo.
Entry Time and Current Zone:
The script identifies potential entry times for trades within the option buy zone. When a valid buy zone trigger occurs, the script calculates the entryTime by adding the durationInMinutes (user-defined) to the startTime. The entryTime will be displayed in the "Entry Time" column of the table. Depending on the comparison between optionbuyzonetriggertime and entryTime, the background color of the entry time will change. If optionbuyzonetriggertime is greater than entryTime, the background color will be yellow, indicating that a new trigger has occurred before the specified duration. Otherwise, the background color will be green, suggesting that the entry time is still within the defined duration.
Current Zone Indicator:
The script further categorizes the current zone as either "CE Zone" (call option zone) or "PE Zone" (put option zone). When the market is trending upwards and the minor SMA is above the major SMA, the currentZone will be set to "CE Zone." Conversely, when the market is trending downwards and the minor SMA is below the major SMA, the currentZone will be "PE Zone." This information is displayed in the "Current Zone" column of the table.
These additional use cases empower traders with valuable insights into market trends, buying and selling surges, option buy zones, and potential entry times. Traders can combine this information with their analysis and risk management strategies to make informed and confident trading decisions.
Note:
The script is optimized for identifying trends and potential trade opportunities. It is crucial to perform additional analysis and risk management before executing any trades based on the provided signals.
Happy Trading!
