Impactful pattern and candles pattern AlertThe Alertion indicator!
impactful pattern:
pattern that happen near the zone or in the zone at lower timeframe and give us entry and stop limit price.
It is helpful for price action traders and those who want to decrease their risk.
There are 3 IP patterns:
Quasimodo
Head and shoulder
whipsaw engulfing
These patterns may occur near the zone or may not occur but by them, you can decrease your trading risk for example you can
trade with half lot before IP pattern and enter with other half after pattern.
how to use?
for example:
you find zone at 1h timeframe for short position
when price enter to your zone
you run this indicator and choose your lower timeframe, for example 15m and click on short position.
Then make the alert by right-click on your chart and choose the add alert and at condition box choose the impactful pattern and then click on create
now wait for message :)
Candles pattern:
like reversal bar, key reversal bar, exhaustion bar, pin bar, two-bar reversal, tree-bar reversal, inside bar, outside bar
these occur when the trend turn, so it is usable when the price enter to your zone or near your zone.
This pattern can decrease your risk.
Inside bar and outside bar:
if this pattern engulf up, it is bullish pattern and if engulf down, it is bearish pattern.
what does this indicator do?
this indicator is for making alert
it helps you to decrease your risk and failure.
You optimize it to alert you when IP pattern happen or candle pattern happen or inside bar or outside bar engulfing or all of them.
For IP pattern, it will message you entry and stop limit price.
It works at 2 different timeframes, so you can make alert for example in 1h TF for candles pattern and 15m TF for IP pattern.
Indicator will alert you for candles pattern at your chart timeframe and for IP pattern at timeframe you've chosen when you run the indicator, and it is changeable
in setting.
setting options
TIMEFRAME
IP: select the timeframe for IP patterns it means when IP pattern happen at that timeframe the indicator will alert you
example = your TF is 1h, you found the supply zone and want to trade, note that IP pattern happen in lower TF, so you select 15m TF or TF lower than 1h.
Short position: select it if you want to make short position.
BUFFERING
indicator send you entry and stop limit price
you can change it by amount of percent
it is your strategy to change your entry and stop loss or not
example= in head and shoulder pattern at short position, the stop limit is high price of head in pattern
so the indicator will message you the exact price but if you want to put
your stop limit 5 percent upper than exact price you can enter 5 in front of stop loss
or you want to enter 5 percent lower than exact high price of shoulder, you can optimize it.
ALERTION
you choose what alert you want
IP alert or candle alert or inside and outside bar alert
type your text for alert
you can write additional text for your message
ADVANCE
IP alert frequency option:
1. Once per bar : indicator will alert you for IP pattern once at your chat timeframe bar, and you should wait til next bar for next alert.
2. Once per bar close : alert you when your chart timeframe bar closed and next alert will happen when next bar is closed.
3. All: alert you all the times IP pattern happen
pivot left and right bars: lower will find smaller pattern
at the END:
this indicator is not strategy
it is part of your strategy that help you to increase your winning rate.
It is helpful for scalping and candle patterns finding.
After you make an alert, you can delete the indicator or change your timeframe or make another alert, your previous alert won’t change.
Thank you all.
在腳本中搜尋"bar"
How to avoid repainting when NOT using security()Even when your code does not use security() calls, repainting dynamics still come into play in the realtime bar. Script coders and users must understand them and, if they choose to avoid repainting, need to know how to do so. This script demonstrates three methods to avoid repainting when NOT using the security() function.
Note that repainting dynamics when not using security() usually only come into play in the realtime bar, as historical data is fixed and thus cannot cause repainting, except in situations related to stock splits or dividend adjustments.
For those who don’t want to read
Configure your alerts to trigger “Once Per Bar Close” and you’re done.
For those who want to understand
Put this indicator on a 1 minute or seconds chart with a live symbol. As price changes you will see four of this script’s MAs (all except the two orange ones) move in the realtime bar. You are seeing repainting in action. When the current realtime bar closes and becomes a historical bar, the lines on the historical bars will no longer move, as the bar’s OHLC values are fixed. Note that you may need to refresh your chart to see the correct historical OHLC values, as exchange feeds sometimes produce very slight variations between the end values of the realtime bar and those of the same bar once it becomes a historical bar.
Some traders do not use signals generated by a script but simply want to avoid seeing the lines plotted by their scripts move during the realtime bar. They are concerned with repainting of the lines .
Other traders use their scripts to evaluate conditions, which they use to either plot markers on the chart, trigger alerts, or both. They may not care about the script’s plotted lines repainting, but do not want their markers to appear/disappear on the chart, nor their alerts to trigger for a condition that becomes true during the realtime bar but is no longer true once it closes. Those traders are more concerned with repainting of signals .
For each of the three methods shown in this script’s code, comments explain if its lines, markers and alerts will repaint or not. Through the Settings/Inputs you will be able to control plotting of lines and markers corresponding to each method, as well as experiment with the option, for method 2, of disabling only the lines plotting in the realtime bar while still allowing the markers and alerts to be generated.
An unavoidable fact is that non-repainting lines, markers or alerts are always late compared to repainting ones. The good news is that how late they are will in many cases be insignificant, so that the added reliability of the information they provide will largely offset the disadvantages of waiting.
Method 1 illustrates the usual way of going about things in a script. Its gray lines and markers will always repaint but repainting of the alerts the marker conditions generate can be avoided by configuring alerts to trigger “Once Per Bar Close”. Because this gray marker repaints, you will occasionally see it appear/disappear during the realtime bar when the gray MAs cross/un-cross.
Method 2 plots the same MAs as method 1, but in green. The difference is that it delays its marker condition by one bar to ensure it does not repaint. Its lines will normally repaint but its markers will not, as they pop up after the condition has been confirmed on the bar preceding the realtime bar. Its markers appear at the beginning of the realtime bar and will never disappear. When using this method alerts can be configured to trigger “Once Per Bar” so they fire the moment the marker appears on the chart at the beginning of the realtime bar. Note that the delay incurred between methods 1 and 2 is merely the instant between the close of a realtime bar and the beginning of the next one—a delay measured in milliseconds. Method 2 also allows its lines to be hidden in the realtime bar with the corresponding option in the script’s Settings/Inputs . This will be useful to those wishing to eliminate unreliable lines from the realtime bar. Commented lines in method 2 provide for a 2b option, which is to delay the calculation of the MAs rather than the cross condition. It has the obvious inconvenient of plotting delayed MAs, but may come in handy in some situations.
Method 3 is not the best solution when using MAs because it uses the open of bars rather than their close to calculate the MAs. While this provides a way of avoiding repainting, it is not ideal in the case of MA calcs but may come in handy in other cases. The orange lines and markers of method 3 will not repaint because the value of open cannot change in the realtime bar. Because its markers do not repaint, alerts may be configured using “Once Per Bar”.
Spend some time playing with the different options and looking at how this indicator’s lines plot and behave when you refresh you chart. We hope everything you need to understand and prevent repainting when not using security() is there.
Look first. Then leap.
Delta Volume Columns [LucF]Displays delta volume columns using intrabar volume information. Each volume column is divided into three sections: buying, selling and neutral volume. Volume for each section is determined from the volume and price movement of each intrabar at a user-selected lower resolution.
Features include:
- Choice of color themes for either dark or light chart backgrounds
- Delta volume columns
- Volume Balance displayed as the difference between the MAs of buying and selling volume
- Display of divergences between a bar’s volume balance and the bar’s price movement (example: buying volume > selling volume but close < open). Divergences can be shown in 2 different color schemes (including green/red showing a tentative direction), on volume columns and/or on chart bars
- Display of bar by bar volume balance with highlighting of above average volume
- Display of the usual total volume MA
- Choice of the lower resolution used to retrieve intrabar information
- Alerts configurable on any combination of the markers, with control over long/short direction
- Choice of 3 different markers:
1. Double bumps: two consecutive bars where buying or selling volume is in the same direction and where volume > volume MA
2. Divergence confirmations: direction of the price bar following a price/volume balance divergence
3. Volume balance shifts: zero level crossings of the volume balance MA delta
The chart shows the two main modes of display:
- Top pane : shows the stacked volume columns with divergences in orange and the flattened volume balance MAs delta at the bottom of the volume columns. This volume balance is the same shown in the bottom pane. The top pane also shows the instant volume balance strip above the volume columns. The strip’s colors show which of the buying or selling volume was greater, and colors are brighter if the total volume was above the total volume MA.
- Bottom pane : shows the volume balance MAs delta with markers 1 and 2. Given that this graphic has no price momentum component, I find quite eerie how it often looks like a momentum-based signal.
The default 5 minute intrabar resolution is used in combination with the weekly chart, which is excessive.
This script uses a special characteristic of the security() function’s behavior when it is sent to a resolution lower than the chart’s resolution. Details are given in the script’s comments. This method has the advantage of working under more circumstances than some of the other loop-based methods, but it also has its limits.
IMPORTANT
This is what you need to know:
- The method used does not work on the realtime bar—only on historical bars. Consequently, the volume column shown on the realtime bar is a normal volume column plotted in green or red, following price movement. The column will only show delta volume information after it closes and becomes a historical bar.
- The indicator only works on some chart resolutions: 5, 10, 15 and 30 minutes, 1, 2, 4, 6, and 12 hours, 1 day, 1 week and 1 month. The script’s code can be modified to run on other resolutions, but chart resolutions must be divisible by the lower resolution used for intrabars.
- Intrabar resolutions can be selected from 1, 5, 15, 30, 45 minutes, 1, 2, 3, 4 hours, 1 day, 1 week and 1 month. The intrabar resolution must of course be smaller than the chart’s resolution.
- Contrary to my other indicators where alerts must be configured to trigger “Once Per Bar Close” in order to avoid false triggers (or repainting), all this indicator’s alerts are designed to trigger using previous bar information since the indicator’s calculations in the realtime bar are not exact. Markers are not plotted with a negative offset; they appear at the beginning of the realtime bar following confirmation of the marker’s condition on the previous bar. Alerts for this indicator should thus be configured to trigger “Once Per Bar” so they trigger at the beginning of the realtime bar. Note that the penalty is not that great, as it is simply the instant between the close of the previous realtime bar and the opening of the next. The advantage of using this technique is that the indicator does not repaint; a marker that appears at the beginning of the realtime bar will never disappear.
- The script only plots information that is reliable in the realtime bar, i.e., total volume and markers. All other plots are set to n/a to prevent misleading traders.
- When the difference between the chart’s resolution and the lower resolution is too important, volume columns will not calculate for all bars in the dataset.
On Delta Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by 2 different traders. There is no such thing as “buy only” or “sell only” volume, but trader lingo is riddled with original fabulations.
Without access to order book information, traders work with the assumption that when price moves up during a bar, there was more buying pressure than selling pressure. The built-in volume indicator available on TradingView uses this logic to color the volume columns green or red. While this script’s numbers are more precise because it analyses a number of intrabars to calculate its information, it uses the exact same imperfect logic to calculate its buying/selling/neutral sections.
Until Pine scripts can have access to how much volume was transacted at the bid/ask prices, our so-called buying/selling volume information will always be a mere proxy.
Divergences
You may wonder how there can be divergences between buying/selling volume information and price movement. This will sometimes be due to the methodology’s shortcomings we have just discussed, but divergences may also occur in instances where because of order book structure, it takes less volume to increase the price of an asset than it takes to decrease it.
As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. I do not share the overwhelming enthusiasm traders have for divergences. To your pattern-hungry brain, the orange bars this indicator shows on chart will—as divergences on other indicators do–appear to often indicate turnarounds. My opinion is that reality is generally quite sobering, as many who have tried building automated rules based on divergences will tell you. I do not have hard numbers on the lack of performance of divergences—only many failed attempts to make them perform, which a few experienced strategy modelers I know share with me. Please don’t try to read too much into them. While they look great on past data, I find they are often difficult to use in realtime to make bets with good odds.
Thanks to:
- A guy called Kuan who commented on a Backtest Rookies presentation of an intrabar delta volume indicator using a for loop. The heart of “my” indicator is code borrowed from Kuan; I just built a hopefully useful wrapper around it.
- @theheirophant, my partner in the exploration of the sometimes weird abysses of security() ’s behavior at lower resolutions.
How to avoid repainting when using security() - PineCoders FAQNOTE
The non-repainting technique in this publication that relies on bar states is now deprecated, as we have identified inconsistencies that undermine its credibility as a universal solution. The outputs that use the technique are still available for reference in this publication. However, we do not endorse its usage. See this publication for more information about the current best practices for requesting HTF data and why they work.
This indicator shows how to avoid repainting when using the security() function to retrieve information from higher timeframes.
What do we mean by repainting?
Repainting is used to describe three different things, in what we’ve seen in TV members comments on indicators:
1. An indicator showing results that change during the realtime bar, whether the script is using the security() function or not, e.g., a Buy signal that goes on and then off, or a plot that changes values.
2. An indicator that uses future data not yet available on historical bars.
3. An indicator that uses a negative offset= parameter when plotting in order to plot information on past bars.
The repainting types we will be discussing here are the first two types, as the third one is intentional—sometimes even intentionally misleading when unscrupulous script writers want their strategy to look better than it is.
Let’s be clear about one thing: repainting is not caused by a bug ; it is caused by the different context between historical bars and the realtime bar, and script coders or users not taking the necessary precautions to prevent it.
Why should repainting be avoided?
Repainting matters because it affects the behavior of Pine scripts in the realtime bar, where the action happens and counts, because that is when traders (or our systems) take decisions where odds must be in our favor.
Repainting also matters because if you test a strategy on historical bars using only OHLC values, and then run that same code on the realtime bar with more than OHLC information, scripts not properly written or misconfigured alerts will alter the strategy’s behavior. At that point, you will not be running the same strategy you tested, and this invalidates your test results , which were run while not having the additional price information that is available in the realtime bar.
The realtime bar on your charts is only one bar, but it is a very important bar. Coding proper strategies and indicators on TV requires that you understand the variations in script behavior and how information available to the script varies between when the script is running on historical and realtime bars.
How does repainting occur?
Repainting happens because of something all traders instinctively crave: more information. Contrary to trader lure, more information is not always better. In the realtime bar, all TV indicators (a.k.a. studies ) execute every time price changes (i.e. every tick ). TV strategies will also behave the same way if they use the calc_on_every_tick = true parameter in their strategy() declaration statement (the parameter’s default value is false ). Pine coders must decide if they want their code to use the realtime price information as it comes in, or wait for the realtime bar to close before using the same OHLC values for that bar that would be used on historical bars.
Strategy modelers often assume that using realtime price information as it comes in the realtime bar will always improve their results. This is incorrect. More information does not necessarily improve performance because it almost always entails more noise. The extra information may or may not improve results; one cannot know until the code is run in realtime for enough time to provide data that can be analyzed and from which somewhat reliable conclusions can be derived. In any case, as was stated before, it is critical to understand that if your strategy is taking decisions on realtime tick data, you are NOT running the same strategy you tested on historical bars with OHLC values only.
How do we avoid repainting?
It comes down to using reliable information and properly configuring alerts, if you use them. Here are the main considerations:
1. If your code is using security() calls, use the syntax we propose to obtain reliable data from higher timeframes.
2. If your script is a strategy, do not use the calc_on_every_tick = true parameter unless your strategy uses previous bar information to calculate.
3. If your script is a study and is using current timeframe information that is compared to values obtained from a higher timeframe, even if you can rely on reliable higher timeframe information because you are correctly using the security() function, you still need to ensure the realtime bar’s information you use (a cross of current close over a higher timeframe MA, for example) is consistent with your backtest methodology, i.e. that your script calculates on the close of the realtime bar. If your system is using alerts, the simplest solution is to configure alerts to trigger Once Per Bar Close . If you are not using alerts, the best solution is to use information from the preceding bar. When using previous bar information, alerts can be configured to trigger Once Per Bar safely.
What does this indicator do?
It shows results for 9 different ways of using the security() function and illustrates the simplest and most effective way to avoid repainting, i.e. using security() as in the example above. To show the indicator’s lines the most clearly, price on the chart is shown with a black line rather than candlesticks. This indicator also shows how misusing security() produces repainting. All combinations of using a 0 or 1 offset to reference the series used in the security() , as well as all combinations of values for the gaps= and lookahead= parameters are shown.
The close in the call labeled “BEST” means that once security has reached the upper timeframe (1 day in our case), it will fetch the previous day’s value.
The gaps= parameter is not specified as it is off by default and that is what we need. This ensures that the value returned by security() will not contain na values on any of our chart’s bars.
The lookahead security() to use the last available value for the higher timeframe bar we are using (the previous day, in our case). This ensures that security() will return the value at the end of the higher timeframe, even if it has not occurred yet. In our case, this has no negative impact since we are requesting the previous day’s value, with has already closed.
The indicator’s Settings/Inputs allow you to set:
- The higher timeframe security() calls will use
- The source security() calls will use
- If you want identifying labels printed on the lines that have no gaps (the lines containing gaps are plotted using very thick lines that appear as horizontal blocks of one bar in length)
For the lines to be plotted, you need to be on a smaller timeframe than the one used for the security() calls.
Comments in the code explain what’s going on.
Look first. Then leap.
BACAP PRICE STRUCTURE 21 EMA TREND21dma-STRUCTURE
Overview
The 21dma-STRUCTURE indicator is a sophisticated overlay indicator that visualizes price action relative to a triple 21-period exponential moving average structure. Originally developed by BalarezoCapital and enhanced by PrimeTrading, this indicator provides clear visual cues for trend direction and momentum through dynamic bar coloring and EMA structure analysis.
Key Features
Triple EMA Structure
- 21 EMA High: Tracks the exponential moving average of high prices
- 21 EMA Close: Tracks the exponential moving average of closing prices
- 21 EMA Low: Tracks the exponential moving average of low prices
- Dynamic Cloud: Gray fill between high and low EMAs for visual structure reference
Smart Bar Coloring System
- Blue Bars: Price closes above all three EMAs (strong bullish momentum)
- Pink Bars: Daily high falls below the lowest EMA (strong bearish signal)
- Gray Bars: Neutral conditions or transitional phases
- Color Memory: Maintains previous color until new condition is met
Dynamic Center Line
- Trend-Following Color: Green when all EMAs are rising, red when all are falling
- Color Persistence: Maintains trend color during sideways movement
- Visual Clarity: Thicker center line for easy trend identification
Customizable Visual Elements
- Adjustable line thickness for all EMA plots
- Customizable colors for bullish and bearish conditions
- Configurable trend colors for uptrend and downtrend phases
- Optional bar color changes with toggle control
How to Use
Trend Identification
- Rising Green Center Line: All EMAs trending upward (bullish structure)
- Falling Red Center Line: All EMAs trending downward (bearish structure)
- Flat Center Line: Maintains last trend color during consolidation
Momentum Analysis
- Blue Bars: Strong bullish momentum with price above entire EMA structure
- Pink Bars: Strong bearish momentum with high below lowest EMA
- Gray Bars: Neutral or transitional momentum phases
Entry and Exit Signals
- Bullish Setup: Look for blue bars during green center line periods
- Bearish Setup: Look for pink bars during red center line periods
- Exit Consideration: Watch for color changes as potential momentum shifts
Structure Trading
- Support/Resistance: Use EMA cloud as dynamic support and resistance zones
- Breakout Confirmation: Bar color changes can confirm structure breakouts
- Trend Continuation: Color persistence suggests ongoing momentum
Settings
Visual Customization
- Change Bar Color: Toggle to enable/disable bar coloring
- Line Size: Adjust thickness of EMA lines (default: 3)
- Bullish Candle Color: Customize blue bar color
- Bearish Candle Color: Customize pink bar color
Trend Colors
- Uptrend Color: Color for rising EMA center line (default: green)
- Downtrend Color: Color for falling EMA center line (default: red)
- Cloud Color: Fill color between high and low EMAs (default: gray)
Advanced Features
Modified Bar Logic
Unlike traditional EMA systems, this indicator uses refined conditions:
- Bullish signals require close above ALL three EMAs
- Bearish signals require high below the LOWEST EMA
- Enhanced precision reduces false signals compared to single EMA systems
Trend Memory System
- Intelligent color persistence during sideways movement
- Reduces noise from minor EMA fluctuations
- Maintains trend context during consolidation periods
Performance Optimization
- Efficient calculation methods for real-time performance
- Clean visual design that doesn't clutter charts
- Compatible with all timeframes and instruments
Best Practices
Multi-Timeframe Analysis
- Use higher timeframes to identify overall trend direction
- Apply on multiple timeframes for confluence
- Combine with weekly/monthly charts for position trading
Risk Management
- Use bar color changes as early warning signals
- Consider position sizing based on EMA structure strength
- Set stops relative to EMA support/resistance levels
Combination Strategies
- Pair with volume indicators for confirmation
- Use alongside RSI or MACD for momentum confirmation
- Combine with key support/resistance levels
Market Context
- More effective in trending markets than choppy conditions
- Consider overall market environment and sector strength
- Adjust expectations during high volatility periods
Technical Specifications
- Based on 21-period exponential moving averages
- Uses Pine Script v6 for optimal performance
- Overlay indicator that works with any chart type
- Maximum 500 lines for clean performance
Ideal Applications
- Swing trading on daily charts
- Position trading on weekly charts
- Intraday momentum trading (adjust timeframe accordingly)
- Trend following strategies
- Structure-based trading approaches
Disclaimer
This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis, proper risk management, and consider your individual trading plan and risk tolerance.
Compatible with Pine Script v6 | Works on all timeframes | Optimized for trending markets
Pullback Candle (Bullish & Bearish, No EMA)🔍 Purpose
This indicator detects simple pullback reversal patterns based on price action and swing highs/lows — without any moving average or trend filters.
It highlights:
Bullish pullbacks (potential bounce/long setups)
Bearish pullbacks (potential rejection/short setups)
📈 Bullish Pullback Criteria
Three-bar pattern:
Bar 3: Highest close
Bar 2: Lower close
Bar 1: Even lower close
Current bar closes above previous bar (bullish reversal)
One of the last two candles is the lowest low of the past 6 bars (swing low)
📍 Result: A small green cross is plotted below the bar, and the bar is colored green.
📉 Bearish Pullback Criteria
Three-bar pattern:
Bar 3: Lowest close
Bar 2: Higher close
Bar 1: Even higher close
Current bar closes below previous bar (bearish reversal)
One of the last two candles is the highest high of the past 10 bars (swing high)
📍 Result: A small red cross is plotted above the bar, and the bar is colored red.
🔔 Alerts
One alert condition each for bullish and bearish pullback detection.
Can be used to trigger TradingView alerts.
🛠️ Customization
No inputs — fully automated logic
Clean, minimal, and fast
Can be extended with labels, alert sounds, or signals
EXODUS EXODUS by (DAFE) Trading Systems
EXODUS is a sophisticated trading algorithm built by Dskyz (DAFE) Trading Systems for competitive and competition purposes, designed to identify high-probability trades with robust risk management. this strategy leverages a multi-signal voting system, combining three core components—SPR, VWMO, and VEI—alongside ADX, choppiness filters, and ATR-based volatility gates to ensure trades are taken only in favorable market conditions. the algo uses a take-profit to stop-loss ratio, dynamic position sizing, and a strict voting mechanism requiring all signals to align before entering a trade.
EXODUS was not overfitted for any specific symbol. instead, it uses a generic tuned setting, making it versatile across various markets. while it can trade futures, it’s not currently set up for it but has the potential to do more with further development. visuals are intentionally minimal due to its competition focus, prioritizing performance over aesthetics. a more visually stunning version may be released in the future with enhanced graphics.
The Unique Core Components Developed for EXODUS
SPR (Session Price Recalibration)
SPR measures momentum during regular trading hours (RTH, 0930-1600, America/New_York) to catch session-specific trends.
spr_lookback = input.int(15, "SPR Lookback") this sets how many bars back SPR looks to calculate momentum (default 15 bars). it compares the current session’s price-volume score to the score 15 bars ago to gauge momentum strength.
how it works: a longer lookback smooths out the signal, focusing on bigger trends. a shorter one makes SPR more sensitive to recent moves.
how to adjust: on a 1-hour chart, 15 bars is 15 hours (about 2 trading days). if you’re on a shorter timeframe like 5 minutes, 15 bars is just 75 minutes, so you might want to increase it to 50 or 100 to capture more meaningful trends. if you’re trading a choppy stock, a shorter lookback (like 5) can help catch quick moves, but it might give more false signals.
spr_threshold = input.float (0.7, "SPR Threshold")
this is the cutoff for SPR to vote for a trade (default 0.7). if SPR’s normalized value is above 0.7, it votes for a long; below -0.7, it votes for a short.
how it works: SPR normalizes its momentum score by ATR, so this threshold ensures only strong moves count. a higher threshold means fewer trades but higher conviction.
how to adjust: if you’re getting too few trades, lower it to 0.5 to let more signals through. if you’re seeing too many false entries, raise it to 1.0 for stricter filtering. test on your chart to find a balance.
spr_atr_length = input.int(21, "SPR ATR Length") this sets the ATR period (default 21 bars) used to normalize SPR’s momentum score. ATR measures volatility, so this makes SPR’s signal relative to market conditions.
how it works: a longer ATR period (like 21) smooths out volatility, making SPR less jumpy. a shorter one makes it more reactive.
how to adjust: if you’re trading a volatile stock like TSLA, a longer period (30 or 50) can help avoid noise. for a calmer stock, try 10 to make SPR more responsive. match this to your timeframe—shorter timeframes might need a shorter ATR.
rth_session = input.session("0930-1600","SPR: RTH Sess.") rth_timezone = "America/New_York" this defines the session SPR uses (0930-1600, New York time). SPR only calculates momentum during these hours to focus on RTH activity.
how it works: it ignores pre-market or after-hours noise, ensuring SPR captures the main market action.
how to adjust: if you trade a different session (like London hours, 0300-1200 EST), change the session to match. you can also adjust the timezone if you’re in a different region, like "Europe/London". just make sure your chart’s timezone aligns with this setting.
VWMO (Volume-Weighted Momentum Oscillator)
VWMO measures momentum weighted by volume to spot sustained, high-conviction moves.
vwmo_momlen = input.int(21, "VWMO Momentum Length") this sets how many bars back VWMO looks to calculate price momentum (default 21 bars). it takes the price change (close minus close 21 bars ago).
how it works: a longer period captures bigger trends, while a shorter one reacts to recent swings.
how to adjust: on a daily chart, 21 bars is about a month—good for trend trading. on a 5-minute chart, it’s just 105 minutes, so you might bump it to 50 or 100 for more meaningful moves. if you want faster signals, drop it to 10, but expect more noise.
vwmo_volback = input.int(30, "VWMO Volume Lookback") this sets the period for calculating average volume (default 30 bars). VWMO weights momentum by volume divided by this average.
how it works: it compares current volume to the average to see if a move has strong participation. a longer lookback smooths the average, while a shorter one makes it more sensitive.
how to adjust: for stocks with spiky volume (like NVDA on earnings), a longer lookback (50 or 100) avoids overreacting to one-off spikes. for steady volume stocks, try 20. match this to your timeframe—shorter timeframes might need a shorter lookback.
vwmo_smooth = input.int(9, "VWMO Smoothing")
this sets the SMA period to smooth VWMO’s raw momentum (default 9 bars).
how it works: smoothing reduces noise in the signal, making VWMO more reliable for voting. a longer smoothing period cuts more noise but adds lag.
how to adjust: if VWMO is too jumpy (lots of false votes), increase to 15. if it’s too slow and missing trades, drop to 5. test on your chart to see what keeps the signal clean but responsive.
vwmo_threshold = input.float(10, "VWMO Threshold") this is the cutoff for VWMO to vote for a trade (default 10). above 10, it votes for a long; below -10, a short.
how it works: it ensures only strong momentum signals count. a higher threshold means fewer but stronger trades.
how to adjust: if you want more trades, lower it to 5. if you’re getting too many weak signals, raise it to 15. this depends on your market—volatile stocks might need a higher threshold to filter noise.
VEI (Velocity Efficiency Index)
VEI measures market efficiency and velocity to filter out choppy moves and focus on strong trends.
vei_eflen = input.int(14, "VEI Efficiency Smoothing") this sets the EMA period for smoothing VEI’s efficiency calc (bar range / volume, default 14 bars).
how it works: efficiency is how much price moves per unit of volume. smoothing it with an EMA reduces noise, focusing on consistent efficiency. a longer period smooths more but adds lag.
how to adjust: for choppy markets, increase to 20 to filter out noise. for faster markets, drop to 10 for quicker signals. this should match your timeframe—shorter timeframes might need a shorter period.
vei_momlen = input.int(8, "VEI Momentum Length") this sets how many bars back VEI looks to calculate momentum in efficiency (default 8 bars).
how it works: it measures the change in smoothed efficiency over 8 bars, then adjusts for inertia (volume-to-range). a longer period captures bigger shifts, while a shorter one reacts faster.
how to adjust: if VEI is missing quick reversals, drop to 5. if it’s too noisy, raise to 12. test on your chart to see what catches the right moves without too many false signals.
vei_threshold = input.float(4.5, "VEI Threshold") this is the cutoff for VEI to vote for a trade (default 4.5). above 4.5, it votes for a long; below -4.5, a short.
how it works: it ensures only strong, efficient moves count. a higher threshold means fewer trades but higher quality.
how to adjust: if you’re not getting enough trades, lower to 3. if you’re seeing too many false entries, raise to 6. this depends on your market—fast stocks like NQ1 might need a lower threshold.
Features
Multi-Signal Voting: requires all three signals (SPR, VWMO, VEI) to align for a trade, ensuring high-probability setups.
Risk Management: uses ATR-based stops (2.1x) and take-profits (4.1x), with dynamic position sizing based on a risk percentage (default 0.4%).
Market Filters: ADX (default 27) ensures trending conditions, choppiness index (default 54.5) avoids sideways markets, and ATR expansion (default 1.12) confirms volatility.
Dashboard: provides real-time stats like SPR, VWMO, VEI values, net P/L, win rate, and streak, with a clean, functional design.
Visuals
EXODUS prioritizes performance over visuals, as it was built for competitive and competition purposes. entry/exit signals are marked with simple labels and shapes, and a basic heatmap highlights market regimes. a more visually stunning update may be released later, with enhanced graphics and overlays.
Usage
EXODUS is designed for stocks and ETFs but can be adapted for futures with adjustments. it performs best in trending markets with sufficient volatility, as confirmed by its generic tuning across symbols like TSLA, AMD, NVDA, and NQ1. adjust inputs like SPR threshold, VWMO smoothing, or VEI momentum length to suit specific assets or timeframes.
Setting I used: (Again, these are a generic setting, each security needs to be fine tuned)
SPR LB = 19 SPR TH = 0.5 SPR ATR L= 21 SPR RTH Sess: 9:30 – 16:00
VWMO L = 21 VWMO LB = 18 VWMO S = 6 VWMO T = 8
VEI ES = 14 VEI ML = 21 VEI T = 4
R % = 0.4
ATR L = 21 ATR M (S) =1.1 TP Multi = 2.1 ATR min mult = 0.8 ATR Expansion = 1.02
ADX L = 21 Min ADX = 25
Choppiness Index = 14 Chop. Max T = 55.5
Backtesting: TSLA
Frame: Jan 02, 2018, 08:00 — May 01, 2025, 09:00
Slippage: 3
Commission .01
Disclaimer
this strategy is for educational purposes. past performance is not indicative of future results. trading involves significant risk, and you should only trade with capital you can afford to lose. always backtest and validate any strategy before using it in live markets.
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
About the Author
Dskyz (DAFE) Trading Systems is dedicated to building high-performance trading algorithms. EXODUS is a product of rigorous research and development, aimed at delivering consistent, and data-driven trading solutions.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
WhispererRealtimeVolumeLibrary "WhispererRealtimeVolume"
▮ Overview
The Whisperer Realtime Volume Library is a lightweight and reusable Pine Script® library designed for real-time volume analysis.
It calculates up, down, and neutral volumes dynamically, making it an essential tool for traders who want to gain deeper insights into market activity.
This library is a simplified and modular version of the original "Realtime Volume Bars w Market Buy/Sell/Neutral split & Mkt Delta" indicator by the_MarketWhisperer , tailored for integration into custom scripts.
How bars are classified
- Up Bars
If the current bar’s closing price is higher than the previous bar’s closing price, it is classified as an up bar.
Volume handling:
The increase in volume for this bar is added to the up volume.
This represents buying pressure.
- Down Bars
If the current bar’s closing price is lower than the previous bar’s closing price, it is classified as a down bar.
Volume handling:
The increase in volume for this bar is added to the down volume.
This represents selling pressure.
- Neutral Bars
If the current bar’s closing price is the same as the previous bar’s closing price, it is classified as a neutral bar.
Volume handling:
If neutral volume is enabled, the volume is added to the neutral volume.
If neutral volume is not enabled, the volume is assigned to the same direction as the previous bar (up or down). If the previous direction is unknown, it is added to the neutral volume.
▮ What to look for
Real-Time Volume Calculation : Analyze up, down, and neutral volumes in real-time based on price movements and bar volume.
Customizable Start Line : Add a visual reference line to your chart for better context by viewing the starting point of real-time bars.
Ease of Integration : Designed as a library for seamless use in other Pine Script® indicators or strategies.
▮ How to use
Example code:
//@version=6
indicator("Volume Realtime from Whisperer")
import andre_007/WhispererRealtimeVolume/4 as MW
MW.displayStartLine(startLineColor = color.gray, startLineWidth = 1, startLineStyle = line.style_dashed,
displayStartLine = true, y1=volume, y2=volume + 10)
= MW.mw_upDownVolumeRealtime(true)
plot(volume, style=plot.style_columns, color=color.gray)
plot(volumeUp, style=plot.style_columns, color=color.green)
plot(volumeDown, style=plot.style_columns, color=color.red)
plot(volumeNeutral, style=plot.style_columns, color=color.purple)
▮ Credits
This library is inspired by the original work of the_MarketWhisperer , whose "Realtime Volume Bars" indicator served as the foundation.
Link to original indicator :
Anchored Darvas Box## ANCHORED DARVAS BOX
---
### OVERVIEW
**Anchored Darvas Box** lets you drop a single timestamp on your chart and build a Darvas-style consolidation zone forward from that exact candle. The indicator freezes the first user-defined number of bars to establish the range, verifies that price respects that range for another user-defined number of bars, then waits for the first decisive breakout. The resulting rectangle captures every tick of the accumulation phase and the exact moment of expansion—no manual drawing, complete timestamp precision.
---
### HISTORICAL BACKGROUND
Nicolas Darvas’s 1950s box theory tracked institutional accumulation by hand-drawing rectangles around tight price ranges. A trade was triggered only when price escaped the rectangle.
The anchored version preserves Darvas’s logic but pins the entire sequence to a user-chosen candle: perfect for analysing a market open, an earnings release, FOMC minute, or any other catalytic bar.
---
### ALGORITHM DETAIL
1. **ANCHOR BAR**
*You provide a timestamp via the settings panel.* The script waits until the chart reaches that bar and records its index as **startBar**.
2. **RANGE DEFINITION — BARS 1-7**
• `rangeHigh` = highest high of bars 1-7 plus optional tolerance.
• `rangeLow` = lowest low of bars 1-7 minus optional tolerance.
3. **RANGE VALIDATION — BARS 8-14**
• Price must stay inside ` `.
• Any violation aborts the test; no box is created.
4. **ARMED STATE**
• If bars 8-14 hold the range, two live guide-lines appear:
– **Green** at `rangeHigh`
– **Red** at `rangeLow`
• The script is now “armed,” waiting indefinitely for the first true breakout.
5. **BREAKOUT & BOX CREATION**
• **Up breakout** =`high > rangeHigh` → rectangle drawn in **green**.
• **Down breakout**=`low < rangeLow` → rectangle drawn in **red**.
• Box extends from **startBar** to the breakout bar and never updates again.
• Optional labels print the dollar and percentage height of the box at its left edge.
6. **OPTIONAL COOLDOWN**
• After the box is painted the script can stay silent for a user-defined number of bars, letting you study the fallout without another range immediately arming on top of it.
---
### INPUT PARAMETERS
• **ANCHOR TIME** – Precise yyyy-mm-dd HH:MM:SS that seeds the sequence.
• **BARS TO DEFINE RANGE** – Default 7; affects both definition and validation windows.
• **OPTIONAL TOLERANCE** – Absolute price buffer to ignore micro-wicks.
• **COOLDOWN BARS AFTER BREAKOUT** – Pause length before the indicator is allowed to re-anchor (set to zero to disable).
• **SHOW BOX DISTANCE LABELS** – Toggle to print Δ\$ and Δ% on every completed box.
---
### USER WORKFLOW
1. Add the indicator, open settings, and set **ANCHOR TIME** to the candle you care about (e.g., “2025-04-23 09:30:00” for NYSE open).
2. Watch live as the script:
– Paints the seven-bar range.
– Draws validation lines.
– Locks in the box on breakout.
3. Use the box boundaries as structural stops, targets, or context for further trades.
---
### PRACTICAL APPLICATIONS
• **OPENING RANGE BREAKOUTS** – Anchor at the first second of the session; capture the initial 7-bar range and trade the first clean break.
• **EVENT STUDIES** – Anchor at a news candle to measure immediate post-event volatility.
• **VOLUME PROFILE FUSION** – Combine the anchored box with VPVR to see if the breakout occurs at a high-volume node or a low-liquidity pocket.
• **RISK DISCIPLINE** – Stop-loss can sit just inside the opposite edge of the anchored range, enforcing objective risk.
---
### ADVANCED CUSTOMISATION IDEAS
• **MULTIPLE ANCHORS** – Clone the indicator and anchor several boxes (e.g., London open, New York open).
• **DYNAMIC WINDOW** – Switch the 7-bar fixed length to a volatility-scaled length (ATR percentile).
• **STRATEGY WRAPPER** – Turn the indicator into a `strategy{}` script and back-test anchored boxes on decades of data.
---
### FINAL THOUGHTS
Anchored Darvas Boxes give you Darvas’s timeless range-break methodology anchored to any candle of interest—perfect for dissecting openings, economic releases, or your own bespoke “important” bars with laboratory precision.
Uptrick: Fisher Eclipse1. Name and Purpose
Uptrick: Fisher Eclipse is a Pine version 6 extension of the basic Fisher Transform indicator that focuses on highlighting potential turning points in price data. Its purpose is to allow traders to spot shifts in momentum, detect divergence, and adapt signals to different market environments. By combining a core Fisher Transform with additional signal processing, divergence detection, and customizable aggressiveness settings, this script aims to help users see when a price move might be losing momentum or gaining strength.
2. Overview
This script uses a Fisher Transform calculation on the average of each bar’s high and low (hl2). The Fisher Transform is designed to amplify price extremes by mapping data into a different scale, making potential reversals more visible than they might be with standard oscillators. Uptrick: Fisher Eclipse takes this concept further by integrating a signal line, divergence detection, bar coloring for momentum intensity, and optional thresholds to reduce unwanted noise.
3. Why Use the Fisher Transform
The Fisher Transform is known for converting relatively smoothed price data into a more pronounced scale. This transformation highlights where markets may be overextended. In many cases, standard oscillators move gently, and traders can miss subtle hints that a reversal might be approaching. The Fisher Transform’s mathematical approach tightens the range of values and sharpens the highs and lows. This behavior can allow traders to see clearer peaks and troughs in momentum. Because it is often quite responsive, it can help anticipate areas where price might change direction, especially when compared to simpler moving averages or traditional oscillators. The result is a more evident signal of possible overbought or oversold conditions.
4. How This Extension Improves on the Basic Fisher Transform
Uptrick: Fisher Eclipse adds multiple features to the classic Fisher framework in order to address different trading styles and market behaviors:
a) Divergence Detection
The script can detect bullish or bearish divergences between price and the oscillator over a chosen lookback period, helping traders anticipate shifts in market direction.
b) Bar Coloring
When momentum exceeds a certain threshold (default 3), bars can be colored to highlight surges of buying or selling pressure. This quick visual reference can assist in spotting periods of heightened activity. After a bar color like this, usually, there is a quick correction as seen in the image below.
c) Signal Aggressiveness Levels
Users can choose between conservative, moderate, or aggressive signal thresholds. This allows them to tune how quickly the indicator flags potential entries or exits. Aggressive settings might suit scalpers who need rapid signals, while conservative settings may benefit swing traders preferring fewer, more robust indications.
d) Minimum Movement Filter
A configurable filter can be set to ensure that the Fisher line and its signal have a sufficient gap before triggering a buy or sell signal. This step is useful for traders seeking to minimize signals during choppy or sideways markets. This can be used to eliminate noise as well.
By combining all these elements into one package, the indicator attempts to offer a comprehensive toolkit for those who appreciate the Fisher Transform’s clarity but also desire more versatility.
5. Core Components
a) Fisher Transform
The script calculates a Fisher value using normalized price over a configurable length, highlighting potential peaks and troughs.
b) Signal Line
The Fisher line is smoothed using a short Simple Moving Average. Crossovers and crossunders are one of the key ways this indicator attempts to confirm momentum shifts.
c) Divergence Logic
The script looks back over a set number of bars to compare current highs and lows of both price and the Fisher oscillator. When price and the oscillator move in opposing directions, a divergence may occur, suggesting a possible upcoming reversal or weakening trend.
d) Thresholds for Overbought and Oversold
Horizontal lines are drawn at user-chosen overbought and oversold levels. These lines help traders see when momentum readings reach particular extremes, which can be especially relevant when combined with crossovers in that region.
e) Intensity Filter and Bar Coloring
If the magnitude of the change in the Fisher Transform meets or exceeds a specified threshold, bars are recolored. This provides a visual cue for significant momentum changes.
6. User Inputs
a) length
Defines how many bars the script looks back to compute the highest high and lowest low for the Fisher Transform. A smaller length reacts more quickly but can be noisier, while a larger length smooths out the indicator at the cost of responsiveness.
b) signal aggressiveness
Adjusts the buy and sell thresholds for conservative, moderate, and aggressive trading styles. This can be key in matching the indicator to personal risk preferences or varying market conditions. Conservative will give you less signals and aggressive will give you more signals.
c) minimum movement filter
Specifies how far apart the Fisher line and its signal line must be before generating a valid crossover signal.
d) divergence lookback
Controls how many bars are examined when determining if price and the oscillator are diverging. A larger setting might generate fewer signals, while a smaller one can provide more frequent alerts.
e) intensity threshold
Determines how large a change in the Fisher value must be for the indicator to recolor bars. Strong momentum surges become more noticeable.
f) overbought level and oversold level
Lets users define where they consider market conditions to be stretched on the upside or downside.
7. Calculation Process
a) Price Input
The script uses the midpoint of each bar’s high and low, sometimes referred to as hl2.
hl2 = (high + low) / 2
b) Range Normalization
Determine the maximum (maxHigh) and minimum (minLow) values over a user-defined lookback period (length).
Scale the hl2 value so it roughly fits between -1 and +1:
value = 2 * ((hl2 - minLow) / (maxHigh - minLow) - 0.5)
This step highlights the bar’s current position relative to its recent highs and lows.
c) Fisher Calculation
Convert the normalized value into the Fisher Transform:
fisher = 0.5 * ln( (1 + value) / (1 - value) ) + 0.5 * fisher_previous
fisher_previous is simply the Fisher value from the previous bar. Averaging half of the new transform with half of the old value smooths the result slightly and can prevent erratic jumps.
ln is the natural logarithm function, which compresses or expands values so that market turns often become more obvious.
d) Signal Smoothing
Once the Fisher value is computed, a short Simple Moving Average (SMA) is applied to produce a signal line. In code form, this often looks like:
signal = sma(fisher, 3)
Crossovers of the fisher line versus the signal line can be used to hint at changes in momentum:
• A crossover occurs when fisher moves from below to above the signal.
• A crossunder occurs when fisher moves from above to below the signal.
e) Threshold Checking
Users typically define oversold and overbought levels (often -1 and +1).
Depending on aggressiveness settings (conservative, moderate, aggressive), these thresholds are slightly shifted to filter out or include more signals.
For example, an oversold threshold of -1 might be used in a moderate setting, whereas -1.5 could be used in a conservative setting to require a deeper dip before triggering.
f) Divergence Checks
The script looks back a specified number of bars (divergenceLookback). For both price and the fisher line, it identifies:
• priceHigh = the highest hl2 within the lookback
• priceLow = the lowest hl2 within the lookback
• fisherHigh = the highest fisher value within the lookback
• fisherLow = the lowest fisher value within the lookback
If price forms a lower low while fisher forms a higher low, it can signal a bullish divergence. Conversely, if price forms a higher high while fisher forms a lower high, a bearish divergence might be indicated.
g) Bar Coloring
The script monitors the absolute change in Fisher values from one bar to the next (sometimes called fisherChange):
fisherChange = abs(fisher - fisher )
If fisherChange exceeds a user-defined intensityThreshold, bars are recolored to highlight a surge of momentum. Aqua might indicate a strong bullish surge, while purple might indicate a strong bearish surge.
This color-coding provides a quick visual cue for traders looking to spot large momentum swings without constantly monitoring indicator values.
8. Signal Generation and Filtering
Buy and sell signals occur when the Fisher line crosses the signal line in regions defined as oversold or overbought. The optional minimum movement filter prevents triggering if Fisher and its signal line are too close, reducing the chance of small, inconsequential price fluctuations creating frequent signals. Divergences that appear in oversold or overbought regions can serve as additional evidence that momentum might soon shift.
9. Visualization on the Chart
Uptrick: Fisher Eclipse plots two lines: the Fisher line in one color and the signal line in a contrasting shade. The chart displays horizontal dashed lines where the overbought and oversold levels lie. When the Fisher Transform experiences a sharp jump or drop above the intensity threshold, the corresponding price bars may change color, signaling that momentum has undergone a noticeable shift. If the indicator detects bullish or bearish divergence, dotted lines are drawn on the oscillator portion to connect the relevant points.
10. Market Adaptability
Because of the different aggressiveness levels and the optional minimum movement filter, Uptrick: Fisher Eclipse can be tailored to multiple trading styles. For instance, a short-term scalper might select a smaller length and more aggressive thresholds, while a swing trader might choose a longer length for smoother readings, along with conservative thresholds to ensure fewer but potentially stronger signals. During strongly trending markets, users might rely more on divergences or large intensity changes, whereas in a range-bound market, oversold or overbought conditions may be more frequent.
11. Risk Management Considerations
Indicators alone do not ensure favorable outcomes, and relying solely on any one signal can be risky. Using a stop-loss or other protections is often suggested, especially in fast-moving or unpredictable markets. Divergence can appear before a market reversal actually starts. Similarly, a Fisher Transform can remain in an overbought or oversold region for extended periods, especially if the trend is strong. Cautious interpretation and confirmation with additional methods or chart analysis can help refine entry and exit decisions.
12. Combining with Other Tools
Traders can potentially strengthen signals from Uptrick: Fisher Eclipse by checking them against other methods. If a moving average cross or a price pattern aligns with a Fisher crossover, the combined evidence might provide more certainty. Volume analysis may confirm whether a shift in market direction has participation from a broad set of traders. Support and resistance zones could reinforce overbought or oversold signals, particularly if price reaches a historical boundary at the same time the oscillator indicates a possible reversal.
13. Parameter Customization and Examples
Some short-term traders run a 15-minute chart, with a shorter length setting, aggressively tight oversold and overbought thresholds, and a smaller divergence lookback. This approach produces more frequent signals, which may appeal to those who enjoy fast-paced trading. More conservative traders might apply the indicator to a daily chart, using a larger length, moderate threshold levels, and a bigger divergence lookback to focus on broader market swings. Results can differ, so it may be helpful to conduct thorough historical testing to see which combination of parameters aligns best with specific goals.
14. Realistic Expectations
While the Fisher Transform can reveal potential turning points, no mathematical tool can predict future price behavior with full certainty. Markets can behave erratically, and a period of strong trending may see the oscillator pinned in an extreme zone without a significant reversal. Divergence signals sometimes appear well before an actual trend change occurs. Recognizing these limitations helps traders manage risk and avoids overreliance on any one aspect of the script’s output.
15. Theoretical Background
The Fisher Transform uses a logarithmic formula to map a normalized input, typically ranging between -1 and +1, into a scale that can fluctuate around values like -3 to +3. Because the transformation exaggerates higher and lower readings, it becomes easier to spot when the market might have stretched too far, too fast. Uptrick: Fisher Eclipse builds on that foundation by adding a series of practical tools that help confirm or refine those signals.
16. Originality and Uniqueness
Uptrick: Fisher Eclipse is not simply a duplicate of the basic Fisher Transform. It enhances the original design in several ways, including built-in divergence detection, bar-color triggers for momentum surges, thresholds for overbought and oversold levels, and customizable signal aggressiveness. By unifying these concepts, the script seeks to reduce noise and highlight meaningful shifts in market direction. It also places greater emphasis on helping traders adapt the indicator to their specific style—whether that involves frequent intraday signals or fewer, more robust alerts over longer timeframes.
17. Summary
Uptrick: Fisher Eclipse is an expanded take on the original Fisher Transform oscillator, including divergence detection, bar coloring based on momentum strength, and flexible signal thresholds. By adjusting parameters like length, aggressiveness, and intensity thresholds, traders can configure the script for day-trading, swing trading, or position trading. The indicator endeavors to highlight where price might be shifting direction, but it should still be combined with robust risk management and other analytical methods. Doing so can lead to a more comprehensive view of market conditions.
18. Disclaimer
No indicator or script can guarantee profitable outcomes in trading. Past performance does not necessarily suggest future results. Uptrick: Fisher Eclipse is provided for educational and informational purposes. Users should apply their own judgment and may want to confirm signals with other tools and methods. Deciding to open or close a position remains a personal choice based on each individual’s circumstances and risk tolerance.
PIP Algorithm
# **Script Overview (For Non-Coders)**
1. **Purpose**
- The script tries to capture the essential “shape” of price movement by selecting a limited number of “key points” (anchors) from the latest bars.
- After selecting these anchors, it draws straight lines between them, effectively simplifying the price chart into a smaller set of points without losing major swings.
2. **How It Works, Step by Step**
1. We look back a certain number of bars (e.g., 50).
2. We start by drawing a straight line from the **oldest** bar in that range to the **newest** bar—just two points.
3. Next, we find the bar whose price is *farthest away* from that straight line. That becomes a new anchor point.
4. We “snap” (pin) the line to go exactly through that new anchor. Then we re-draw (re-interpolate) the entire line from the first anchor to the last, in segments.
5. We repeat the process (adding more anchors) until we reach the desired number of points. Each time, we choose the biggest gap between our line and the actual price, then re-draw the entire shape.
6. Finally, we connect these anchors on the chart with red lines, visually simplifying the price curve.
3. **Why It’s Useful**
- It highlights the most *important* bends or swings in the price over the chosen window.
- Instead of plotting every single bar, it condenses the information down to the “key turning points.”
4. **Key Takeaway**
- You’ll see a small number of red line segments connecting the **most significant** points in the price data.
- This is especially helpful if you want a simplified view of recent price action without minor fluctuations.
## **Detailed Logic Explanation**
# **Script Breakdown (For Coders)**
//@version=5
indicator(title="PIP Algorithm", overlay=true)
// 1. Inputs
length = input.int(50, title="Lookback Length")
num_points = input.int(5, title="Number of PIP Points (≥ 3)")
// 2. Helper Functions
// ---------------------------------------------------------------------
// reInterpSubrange(...):
// Given two “anchor” indices in `linesArr`, linearly interpolate
// the array values in between so that the subrange forms a straight line
// from linesArr to linesArr .
reInterpSubrange(linesArr, segmentLeft, segmentRight) =>
float leftVal = array.get(linesArr, segmentLeft)
float rightVal = array.get(linesArr, segmentRight)
int segmentLen = segmentRight - segmentLeft
if segmentLen > 1
for i = segmentLeft + 1 to segmentRight - 1
float ratio = (i - segmentLeft) / segmentLen
float interpVal = leftVal + (rightVal - leftVal) * ratio
array.set(linesArr, i, interpVal)
// reInterpolateAllSegments(...):
// For the entire “linesArr,” re-interpolate each subrange between
// consecutive breakpoints in `lineBreaksArr`.
// This ensures the line is globally correct after each new anchor insertion.
reInterpolateAllSegments(linesArr, lineBreaksArr) =>
array.sort(lineBreaksArr, order.asc)
for i = 0 to array.size(lineBreaksArr) - 2
int leftEdge = array.get(lineBreaksArr, i)
int rightEdge = array.get(lineBreaksArr, i + 1)
reInterpSubrange(linesArr, leftEdge, rightEdge)
// getMaxDistanceIndex(...):
// Return the index (bar) that is farthest from the current “linesArr.”
// We skip any indices already in `lineBreaksArr`.
getMaxDistanceIndex(linesArr, closeArr, lineBreaksArr) =>
float maxDist = -1.0
int maxIdx = -1
int sizeData = array.size(linesArr)
for i = 1 to sizeData - 2
bool isBreak = false
for b = 0 to array.size(lineBreaksArr) - 1
if i == array.get(lineBreaksArr, b)
isBreak := true
break
if not isBreak
float dist = math.abs(array.get(linesArr, i) - array.get(closeArr, i))
if dist > maxDist
maxDist := dist
maxIdx := i
maxIdx
// snapAndReinterpolate(...):
// "Snap" a chosen index to its actual close price, then re-interpolate the entire line again.
snapAndReinterpolate(linesArr, closeArr, lineBreaksArr, idxToSnap) =>
if idxToSnap >= 0
float snapVal = array.get(closeArr, idxToSnap)
array.set(linesArr, idxToSnap, snapVal)
reInterpolateAllSegments(linesArr, lineBreaksArr)
// 3. Global Arrays and Flags
// ---------------------------------------------------------------------
// We store final data globally, then use them outside the barstate.islast scope to draw lines.
var float finalCloseData = array.new_float()
var float finalLines = array.new_float()
var int finalLineBreaks = array.new_int()
var bool didCompute = false
var line pipLines = array.new_line()
// 4. Main Logic (Runs Once at the End of the Current Bar)
// ---------------------------------------------------------------------
if barstate.islast
// A) Prepare closeData in forward order (index 0 = oldest bar, index length-1 = newest)
float closeData = array.new_float()
for i = 0 to length - 1
array.push(closeData, close )
// B) Initialize linesArr with a simple linear interpolation from the first to the last point
float linesArr = array.new_float()
float firstClose = array.get(closeData, 0)
float lastClose = array.get(closeData, length - 1)
for i = 0 to length - 1
float ratio = (length > 1) ? (i / float(length - 1)) : 0.0
float val = firstClose + (lastClose - firstClose) * ratio
array.push(linesArr, val)
// C) Initialize lineBreaks with two anchors: 0 (oldest) and length-1 (newest)
int lineBreaks = array.new_int()
array.push(lineBreaks, 0)
array.push(lineBreaks, length - 1)
// D) Iteratively insert new breakpoints, always re-interpolating globally
int iterationsNeeded = math.max(num_points - 2, 0)
for _iteration = 1 to iterationsNeeded
// 1) Re-interpolate entire shape, so it's globally up to date
reInterpolateAllSegments(linesArr, lineBreaks)
// 2) Find the bar with the largest vertical distance to this line
int maxDistIdx = getMaxDistanceIndex(linesArr, closeData, lineBreaks)
if maxDistIdx == -1
break
// 3) Insert that bar index into lineBreaks and snap it
array.push(lineBreaks, maxDistIdx)
array.sort(lineBreaks, order.asc)
snapAndReinterpolate(linesArr, closeData, lineBreaks, maxDistIdx)
// E) Save results into global arrays for line drawing outside barstate.islast
array.clear(finalCloseData)
array.clear(finalLines)
array.clear(finalLineBreaks)
for i = 0 to array.size(closeData) - 1
array.push(finalCloseData, array.get(closeData, i))
array.push(finalLines, array.get(linesArr, i))
for b = 0 to array.size(lineBreaks) - 1
array.push(finalLineBreaks, array.get(lineBreaks, b))
didCompute := true
// 5. Drawing the Lines in Global Scope
// ---------------------------------------------------------------------
// We cannot create lines inside barstate.islast, so we do it outside.
array.clear(pipLines)
if didCompute
// Connect each pair of anchors with red lines
if array.size(finalLineBreaks) > 1
for i = 0 to array.size(finalLineBreaks) - 2
int idxLeft = array.get(finalLineBreaks, i)
int idxRight = array.get(finalLineBreaks, i + 1)
float x1 = bar_index - (length - 1) + idxLeft
float x2 = bar_index - (length - 1) + idxRight
float y1 = array.get(finalCloseData, idxLeft)
float y2 = array.get(finalCloseData, idxRight)
line ln = line.new(x1, y1, x2, y2, extend=extend.none)
line.set_color(ln, color.red)
line.set_width(ln, 2)
array.push(pipLines, ln)
1. **Data Collection**
- We collect the **most recent** `length` bars in `closeData`. Index 0 is the oldest bar in that window, index `length-1` is the newest bar.
2. **Initial Straight Line**
- We create an array called `linesArr` that starts as a simple linear interpolation from `closeData ` (the oldest bar’s close) to `closeData ` (the newest bar’s close).
3. **Line Breaks**
- We store “anchor points” in `lineBreaks`, initially ` `. These are the start and end of our segment.
4. **Global Re-Interpolation**
- Each time we want to add a new anchor, we **re-draw** (linear interpolation) for *every* subrange ` [lineBreaks , lineBreaks ]`, ensuring we have a globally consistent line.
- This avoids the “local subrange only” approach, which can cause clustering near existing anchors.
5. **Finding the Largest Distance**
- After re-drawing, we compute the vertical distance for each bar `i` that isn’t already a line break. The bar with the biggest distance from the line is chosen as the next anchor (`maxDistIdx`).
6. **Snapping and Re-Interpolate**
- We “snap” that bar’s line value to the actual close, i.e. `linesArr = closeData `. Then we globally re-draw all segments again.
7. **Repeat**
- We repeat these insertions until we have the desired number of points (`num_points`).
8. **Drawing**
- Finally, we connect each consecutive pair of anchor points (`lineBreaks`) with a `line.new(...)` call, coloring them red.
- We offset the line’s `x` coordinate so that the anchor at index 0 lines up with `bar_index - (length - 1)`, and the anchor at index `length-1` lines up with `bar_index` (the current bar).
**Result**:
You get a simplified representation of the price with a small set of line segments capturing the largest “jumps” or swings. By re-drawing the entire line after each insertion, the anchors tend to distribute more *evenly* across the data, mitigating the issue where anchors bunch up near each other.
Enjoy experimenting with different `length` and `num_points` to see how the simplified lines change!
William Fractals + SignalsWilliams Fractals + Trading Signals
This indicator identifies Williams Fractals and generates trading signals based on price sweeps of these fractal levels.
Williams Fractals are specific candlestick patterns that identify potential market turning points. Each fractal requires a minimum of 5 bars (2 before, 1 center, 2 after), though this indicator allows you to customize the number of bars checked.
Up Fractal (High Point) forms when you have a center bar whose HIGH is higher than the highs of 'n' bars before and after it. For example, with n=2, you'd see a pattern where the center bar's high is higher than 2 bars before and 2 bars after it. The indicator also recognizes patterns where up to 4 bars after the center can have equal highs before requiring a lower high.
Down Fractal (Low Point) forms when you have a center bar whose LOW is lower than the lows of 'n' bars before and after it. For example, with n=2, you'd see a pattern where the center bar's low is lower than 2 bars before and 2 bars after it. The indicator also recognizes patterns where up to 4 bars after the center can have equal lows before requiring a higher low.
Trading Signals:
The indicator generates signals when price "sweeps" these fractal levels:
Buy Signal (Green Triangle) triggers when price sweeps a down fractal. This requires price to go BELOW the down fractal's low level and then CLOSE ABOVE it . This pattern often indicates a failed breakdown and potential reversal upward.
Sell Signal (Red Triangle) triggers when price sweeps an up fractal. This requires price to go ABOVE the up fractal's high level and then CLOSE BELOW it. This pattern often indicates a failed breakout and potential reversal downward.
Customizable Settings:
1. Periods (default: 10) - How many bars to check before and after the center bar (minimum value: 2)
2. Maximum Stored Fractals (default: 1) - How many fractal levels to keep in memory. Older levels are removed when this limit is reached to prevent excessive signals and maintain indicator performance.
Important Notes:
• The indicator checks the actual HIGH and LOW prices of each bar, not just closing prices
• Fractal levels are automatically removed after generating a signal to prevent repeated triggers
• Signals are only generated on bar close to avoid false triggers
• Alerts include the ticker symbol and the exact price level where the sweep occurred
Common Use Cases:
• Identifying potential reversal points
• Finding stop-hunt levels where price might reverse
• Setting stop-loss levels above up fractals or below down fractals
• Trading failed breakouts/breakdowns at fractal levels
Salman Indicator: Multi-Purpose Price ActionSalman Indicator: Multi-Purpose Price Action Tool for Pin Bars, Breakouts, and VWAP Anchoring
This indicator provides a comprehensive suite of price action insights, designed for active traders looking to identify key market structures and potential reversals. The script incorporates a Quarterly VWAP for trend bias, marks pin bars for possible reversal points, highlights outside bars for volatility signals, and indicates simple breakouts and pivot-level breaks. Customizable settings allow for flexibility in various trading styles, with default settings optimized for daily charts.
Outside Bars : Represented by an ⤬ symbol on the chart, these indicate bars where the current high is greater than the previous bar’s high, and the low is lower than the previous bar’s low, signaling high volatility and potential market reversals.
Pin Bars : Denoted by a small dot at the top or bottom of a candle’s wick, these are crucial signals of potential reversal areas. Pin bars are identified based on the percentage length of their shadows, with adjustable strictness in settings.
Quarterly VWAP : The light blue line on the chart represents the VWAP (Volume-Weighted Average Price), which is anchored to the Quarterly period by default. The VWAP acts as a directional bias filter, helping you to determine underlying market trends. This period, source, and offset are fully adjustable in the script’s settings.
Simple Breaks : Hollow candles on the chart indicate "simple breaks," defined when the current bar closes above the previous high or below the previous low. This is an effective way to highlight directional momentum in the market.
Bonus Pivot Breaks : The tilde symbol ~ appears when the price closes above or below prior pivot high/low levels, helping traders spot significant breakout or breakdown points relative to recent pivots.
Alerts
Simple Breaks : Alerts you when a breakout occurs beyond the previous bar’s high or low. Pin Bars : Notifies you of potential reversal points as indicated by bullish or bearish pin bars. Outside Bars : Triggers an alert whenever an outside bar is detected, indicating possible volatility changes.
How to Use
VWAP for Trend Bias : Use the Quarterly VWAP line to gauge overall market trend, with settings that allow adjustment to daily, weekly, monthly, or even larger time frames.
Pin Bars for Reversal Potential : Look for the dot markers on candle wicks, where the strictness of the pin bar detection can be adjusted via settings to match your trading preference.
Simple and Pivot Breaks for Momentum : Watch for hollow candles and the tilde symbol ~ as indicators of potential breakout momentum and pivot break levels, respectively.
This script can serve traders on multiple timeframes, from daily to weekly and beyond. The flexible configuration allows for adjustments in VWAP anchoring and pin bar criteria, providing a tailored fit for individual trading strategies.
[Defaust] Fractals Fractals Indicator
Overview
The Fractals Indicator is a technical analysis tool designed to help traders identify potential reversal points in the market by detecting fractal patterns. This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for enhanced visual clarity and usability.
What Are Fractals?
In trading, a fractal is a pattern consisting of five consecutive bars (candlesticks) that meet specific conditions:
Up Fractal (Potential Sell Signal): Occurs when a high point is surrounded by two lower highs on each side.
Down Fractal (Potential Buy Signal): Occurs when a low point is surrounded by two higher lows on each side.
Fractals help traders identify potential tops and bottoms in the market, signaling possible entry or exit points.
Features of the Indicator
Customizable Periods (n): Allows you to define the number of periods to consider when detecting fractals, offering flexibility to adapt to different trading strategies and timeframes.
Enhanced Plotting Adjustments: This fork introduces adjustments to the plotting of fractal signals for better visual representation on the chart.
Visual Signals: Plots up and down triangles on the chart to signify down fractals (potential bullish signals) and up fractals (potential bearish signals), respectively.
Overlay on Chart: The fractal signals are overlaid directly on the price chart for immediate visualization.
Adjustable Precision: You can set the precision of the plotted values according to your needs.
Pine Script Code Explanation
Below is the Pine Script code for the Fractals Indicator:
//@version=5 indicator(" Fractals", shorttitle=" Fractals", format=format.price, precision=0, overlay=true)
// User input for the number of periods to consider for fractal detection n = input.int(title="Periods", defval=2, minval=2)
// Initialize flags for up fractal detection bool upflagDownFrontier = true bool upflagUpFrontier0 = true bool upflagUpFrontier1 = true bool upflagUpFrontier2 = true bool upflagUpFrontier3 = true bool upflagUpFrontier4 = true
// Loop through previous and future bars to check conditions for up fractals for i = 1 to n // Check if the highs of previous bars are less than the current bar's high upflagDownFrontier := upflagDownFrontier and (high < high ) // Check various conditions for future bars upflagUpFrontier0 := upflagUpFrontier0 and (high < high ) upflagUpFrontier1 := upflagUpFrontier1 and (high <= high and high < high ) upflagUpFrontier2 := upflagUpFrontier2 and (high <= high and high <= high and high < high ) upflagUpFrontier3 := upflagUpFrontier3 and (high <= high and high <= high and high <= high and high < high ) upflagUpFrontier4 := upflagUpFrontier4 and (high <= high and high <= high and high <= high and high <= high and high < high )
// Combine the flags to determine if an up fractal exists flagUpFrontier = upflagUpFrontier0 or upflagUpFrontier1 or upflagUpFrontier2 or upflagUpFrontier3 or upflagUpFrontier4 upFractal = (upflagDownFrontier and flagUpFrontier)
// Initialize flags for down fractal detection bool downflagDownFrontier = true bool downflagUpFrontier0 = true bool downflagUpFrontier1 = true bool downflagUpFrontier2 = true bool downflagUpFrontier3 = true bool downflagUpFrontier4 = true
// Loop through previous and future bars to check conditions for down fractals for i = 1 to n // Check if the lows of previous bars are greater than the current bar's low downflagDownFrontier := downflagDownFrontier and (low > low ) // Check various conditions for future bars downflagUpFrontier0 := downflagUpFrontier0 and (low > low ) downflagUpFrontier1 := downflagUpFrontier1 and (low >= low and low > low ) downflagUpFrontier2 := downflagUpFrontier2 and (low >= low and low >= low and low > low ) downflagUpFrontier3 := downflagUpFrontier3 and (low >= low and low >= low and low >= low and low > low ) downflagUpFrontier4 := downflagUpFrontier4 and (low >= low and low >= low and low >= low and low >= low and low > low )
// Combine the flags to determine if a down fractal exists flagDownFrontier = downflagUpFrontier0 or downflagUpFrontier1 or downflagUpFrontier2 or downflagUpFrontier3 or downflagUpFrontier4 downFractal = (downflagDownFrontier and flagDownFrontier)
// Plot the fractal symbols on the chart with adjusted plotting plotshape(downFractal, style=shape.triangleup, location=location.belowbar, offset=-n, color=color.gray, size=size.auto) plotshape(upFractal, style=shape.triangledown, location=location.abovebar, offset=-n, color=color.gray, size=size.auto)
Explanation:
Input Parameter (n): Sets the number of periods for fractal detection. The default value is 2, and it must be at least 2 to ensure valid fractal patterns.
Flag Initialization: Boolean variables are used to store intermediate conditions during fractal detection.
Loops: Iterate through the specified number of periods to evaluate the conditions for fractal formation.
Conditions:
Up Fractals: Checks if the current high is greater than previous highs and if future highs are lower or equal to the current high.
Down Fractals: Checks if the current low is lower than previous lows and if future lows are higher or equal to the current low.
Flag Combination: Logical and and or operations are used to combine the flags and determine if a fractal exists.
Adjusted Plotting:
The plotting of fractal symbols has been adjusted for better alignment and visual clarity.
The offset parameter is set to -n to align the plotted symbols with the correct bars.
The color and size have been fine-tuned for better visibility.
How to Use the Indicator
Adding the Indicator to Your Chart
Open TradingView:
Go to TradingView.
Access the Chart:
Click on "Chart" to open the main charting interface.
Add the Indicator:
Click on the "Indicators" button at the top.
Search for " Fractals".
Select the indicator from the list to add it to your chart.
Configuring the Indicator
Periods (n):
Default value is 2.
Adjust this parameter based on your preferred timeframe and sensitivity.
A higher value of n considers more bars for fractal detection, potentially reducing the number of signals but increasing their significance.
Interpreting the Signals
– Up Fractal (Downward Triangle): Indicates a potential price reversal to the downside. May be used as a signal to consider exiting long positions or tightening stop-loss orders.
– Down Fractal (Upward Triangle): Indicates a potential price reversal to the upside. May be used as a signal to consider entering long positions or setting stop-loss orders for short positions.
Trading Strategy Suggestions
Up Fractal Detection:
The high of the current bar (n) is higher than the highs of the previous two bars (n - 1, n - 2).
The highs of the next bars meet certain conditions to confirm the fractal pattern.
An up fractal symbol (downward triangle) is plotted above the bar at position n - n (due to the offset).
Down Fractal Detection:
The low of the current bar (n) is lower than the lows of the previous two bars (n - 1, n - 2).
The lows of the next bars meet certain conditions to confirm the fractal pattern.
A down fractal symbol (upward triangle) is plotted below the bar at position n - n.
Benefits of Using the Fractals Indicator
Early Signals: Helps in identifying potential reversal points in price movements.
Customizable Sensitivity: Adjusting the n parameter allows you to fine-tune the indicator based on different market conditions.
Enhanced Visuals: Adjustments to plotting improve the clarity and readability of fractal signals on the chart.
Limitations and Considerations
Lagging Indicator: Fractals require future bars to confirm the pattern, which may introduce a delay in the signals.
False Signals: In volatile or ranging markets, fractals may produce false signals. It's advisable to use them in conjunction with other analysis tools.
Not a Standalone Tool: Fractals should be part of a broader trading strategy that includes other indicators and fundamental analysis.
Best Practices for Using This Indicator
Combine with Other Indicators: Use in combination with trend indicators, oscillators, or volume analysis to confirm signals.
Backtesting: Before applying the indicator in live trading, backtest it on historical data to understand its performance.
Adjust Periods Accordingly: Experiment with different values of n to find the optimal setting for the specific asset and timeframe you are trading.
Disclaimer
The Fractals Indicator is intended for educational and informational purposes only. Trading involves significant risk, and you should be aware of the risks involved before proceeding. Past performance is not indicative of future results. Always conduct your own analysis and consult with a professional financial advisor before making any investment decisions.
Credits
This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for improved visual representation. It is based on standard fractal patterns commonly used in technical analysis and has been developed to provide traders with an effective tool for detecting potential reversal points in the market.
GL Gann Swing IndicatorIntroduction
The GL Gann Swing Indicator is a versatile tool designed to help traders identify market trends, support and resistance areas, and potential reversals. This indicator applies the principles of Gann Swing Charts, a technique developed by W.D. Gann, which focuses on market swings to determine the overall direction and turning points of price action. Gann Swing Charts are a time-tested method of technical analysis that simplifies price action by focusing on significant highs and lows, thereby eliminating market noise and providing a clearer view of the trend.
By analyzing price action and determining swing directions and turning points, the indicator filters out market noise using four distinct bar types:
Up Bar: Higher High, Higher Low
Down Bar: Lower High, Lower Low
Inside Bar: Lower High, Higher Low
Outside Bar: Higher High, Lower Low
This approach helps traders to:
Identify the primary trend direction.
Determine key support and resistance levels.
Recognize potential reversal points.
Filter out minor price fluctuations that do not affect the overall trend.
Features
Bar Types: Display bar types by checking the Show Bar Type box in the indicator's settings. Up bars appear as green upward-pointing triangles, down bars as red downward-pointing triangles, inside bars as grey circles, and outside bars as blue diamonds. These visual aids help traders quickly identify the type of bar and its significance.
Break Lines: These lines highlight when the price rises above a previous swing high or falls below a prior swing low. Green lines indicate breaks of swing highs, while red lines indicate breaks of swing lows. Break lines are enabled by default but can be turned off in the indicator's settings. Break lines provide visual confirmation of trend continuation or reversal.
Bar Count: Bar counts help determine if a swing is overextended and if a reversal is likely. This feature is off by default but can be enabled in the indicator's settings. Users can set a minimum bar count to focus on significant swings. Analyzing the number of bars in a swing can help traders gauge the strength and potential exhaustion of a trend.
Swing MA (Moving Averages): This feature plots the average of a user-defined number of previous swing highs and lows. Options are available to add two moving averages, allowing for both fast and slow averages. Swing MAs can be enabled in the indicator's settings. These moving averages smooth out the price data, making it easier to identify the underlying trend direction.
Why This Indicator is Useful
The GL Gann Swing Indicator is particularly useful for several reasons:
Trend Identification: By focusing on significant price swings, the indicator helps traders identify the primary trend direction, making it easier to align trades with the overall market movement.
Noise Reduction: The indicator filters out minor price fluctuations, allowing traders to focus on meaningful market movements and avoid being misled by short-term volatility.
Support and Resistance Levels: By highlighting key swing highs and lows, the indicator helps traders identify crucial support and resistance levels, which are essential for making informed trading decisions.
Potential Reversals: The indicator's ability to identify overextended swings and potential reversal points can help traders anticipate market turning points and adjust their strategies accordingly.
Customizability: With options to display bar types, break lines, bar counts, and swing moving averages, traders can customize the indicator to suit their specific trading style and preferences.
By incorporating Gann Swing principles, the GL Gann Swing Indicator offers traders a powerful tool to enhance their technical analysis, improve their trading decisions, and ultimately achieve better trading outcomes.
D9 IndicatorD9 Indicator
Category
Technical Indicators
Overview
The D9 Indicator is designed to identify potential trend reversals by counting the number of consecutive closes that are higher or lower than the close four bars earlier. This indicator highlights key moments in the price action where a trend might be exhausting and potentially reversing, providing valuable insights for traders.
Features
Up Signal: Plots a downward triangle or a cross above the bar when the count of consecutive closes higher than the close four bars earlier reaches 7, 8, or 9.
Down Signal: Plots an upward triangle or a checkmark below the bar when the count of consecutive closes lower than the close four bars earlier reaches 7, 8, or 9.
Visual Signals
Red Downward Triangle (7): Indicates the seventh consecutive bar with a higher close.
Red Downward Triangle (8): Indicates the eighth consecutive bar with a higher close.
Red Cross (❌): Indicates the ninth consecutive bar with a higher close, suggesting a potential bearish reversal.
Green Upward Triangle (7): Indicates the seventh consecutive bar with a lower close.
Green Upward Triangle (8): Indicates the eighth consecutive bar with a lower close.
Green Checkmark (✅): Indicates the ninth consecutive bar with a lower close, suggesting a potential bullish reversal.
Usage
The D9 Indicator is useful for traders looking for visual cues to identify potential trend exhaustion and reversals. It can be applied to any market and timeframe, providing flexibility in various trading strategies.
How to Read
When a red cross (❌) appears above a bar, it may signal an overextended uptrend and a potential bearish reversal.
When a green checkmark (✅) appears below a bar, it may signal an overextended downtrend and a potential bullish reversal.
Example
When the price has consecutively closed higher than four bars ago for nine bars, a red cross (❌) will appear above the ninth bar. This suggests that the uptrend might be exhausting, and traders could look for potential short opportunities. Conversely, when the price has consecutively closed lower than four bars ago for nine bars, a green checkmark (✅) will appear below the ninth bar, indicating a potential buying opportunity.
chrono_utilsLibrary "chrono_utils"
Collection of objects and common functions that are related to datetime windows session days and time
ranges. The main purpose of this library is to handle time-related functionality and make it easy to reason about a
future bar checking if it will be part of a predefined session and/or inside a datetime window. All existing session
functionality I found in the documentation e.g. "not na(time(timeframe, session, timezone))" are not suitable for
strategy scripts, since the execution of the orders is delayed by one bar, due to the script execution happening at
the bar close. Moreover, a history operator with a negative value that looks forward is not allowed in any pinescript
expression. So, a prediction for the next bar using the bars_back argument of "time()"" and "time_close()" was
necessary. Thus, I created this library to overcome this small but very important limitation. In the meantime, I
added useful functionality to handle session-based behavior. An interesting utility that emerged from this
development is the data anomaly detection where a comparison between the prediction and the actual value is happening.
If those two values are different then a data inconsistency happened between the prediction bar and the actual bar
(probably due to a holiday, half session day, a timezone change etc..)
exTimezone(timezone)
exTimezone - Convert extended timezone to timezone string
Parameters:
timezone (simple string) : - The timezone or a special string
Returns: string representing the timezone
nameOfDay(day)
nameOfDay - Convert the day id into a short nameOfDay
Parameters:
day (int) : - The day id to convert
Returns: - The short name of the day
today()
today - Get the day id of this day
Returns: - The day id
nthDayAfter(day, n)
nthDayAfter - Get the day id of n days after the given day
Parameters:
day (int) : - The day id of the reference day
n (int) : - The number of days to go forward
Returns: - The day id of the day that is n days after the reference day
nextDayAfter(day)
nextDayAfter - Get the day id of next day after the given day
Parameters:
day (int) : - The day id of the reference day
Returns: - The day id of the next day after the reference day
nthDayBefore(day, n)
nthDayBefore - Get the day id of n days before the given day
Parameters:
day (int) : - The day id of the reference day
n (int) : - The number of days to go forward
Returns: - The day id of the day that is n days before the reference day
prevDayBefore(day)
prevDayBefore - Get the day id of previous day before the given day
Parameters:
day (int) : - The day id of the reference day
Returns: - The day id of the previous day before the reference day
tomorrow()
tomorrow - Get the day id of the next day
Returns: - The next day day id
normalize(num, min, max)
normalizeHour - Check if number is inthe range of
Parameters:
num (int)
min (int)
max (int)
Returns: - The normalized number
normalizeHour(hourInDay)
normalizeHour - Check if hour is valid and return a noralized hour range from
Parameters:
hourInDay (int)
Returns: - The normalized hour
normalizeMinute(minuteInHour)
normalizeMinute - Check if minute is valid and return a noralized minute from
Parameters:
minuteInHour (int)
Returns: - The normalized minute
monthInMilliseconds(mon)
monthInMilliseconds - Calculate the miliseconds in one bar of the timeframe
Parameters:
mon (int) : - The month of reference to get the miliseconds
Returns: - The number of milliseconds of the month
barInMilliseconds()
barInMilliseconds - Calculate the miliseconds in one bar of the timeframe
Returns: - The number of milliseconds in one bar
method to_string(this)
to_string - Formats the time window into a human-readable string
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The string of the time window
method to_string(this)
to_string - Formats the session days into a human-readable string with short day names
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The string of the session day short names
method to_string(this)
to_string - Formats the session time into a human-readable string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The string of the session time
method to_string(this)
to_string - Formats the session time into a human-readable string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The string of the session time
method to_string(this)
to_string - Formats the session into a human-readable string
Namespace types: Session
Parameters:
this (Session) : - The session object with the day and the time range selection
Returns: - The string of the session
method init(this, fromDateTime, toDateTime)
init - Initialize the time window object from boolean values of each session day
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object that will hold the from and to datetimes
fromDateTime (int) : - The starting datetime of the time window
toDateTime (int) : - The ending datetime of the time window
Returns: - The time window object
method init(this, refTimezone, chTimezone, fromDateTime, toDateTime)
init - Initialize the time window object from boolean values of each session day
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object that will hold the from and to datetimes
refTimezone (simple string) : - The timezone of reference of the 'from' and 'to' dates
chTimezone (simple string) : - The target timezone to convert the 'from' and 'to' dates
fromDateTime (int) : - The starting datetime of the time window
toDateTime (int) : - The ending datetime of the time window
Returns: - The time window object
method init(this, sun, mon, tue, wed, thu, fri, sat)
init - Initialize the session days object from boolean values of each session day
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
sun (bool) : - Is Sunday a trading day?
mon (bool) : - Is Monday a trading day?
tue (bool) : - Is Tuesday a trading day?
wed (bool) : - Is Wednesday a trading day?
thu (bool) : - Is Thursday a trading day?
fri (bool) : - Is Friday a trading day?
sat (bool) : - Is Saturday a trading day?
Returns: - The session days object
method init(this, unixTime)
init - Initialize the object from the hour and minute of the session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
unixTime (int) : - The unix time
Returns: - The session time object
method init(this, hourInDay, minuteInHour)
init - Initialize the object from the hour and minute of the session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
hourInDay (int) : - The hour of the time
minuteInHour (int) : - The minute of the time
Returns: - The session time object
method init(this, hourInDay, minuteInHour, refTimezone)
init - Initialize the object from the hour and minute of the session time
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
hourInDay (int) : - The hour of the time
minuteInHour (int) : - The minute of the time
refTimezone (string) : - The timezone of reference of the 'hour' and 'minute'
Returns: - The session time object
method init(this, startTime, endTime)
init - Initialize the object from the start and end session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
startTime (SessionTime) : - The time the session begins
endTime (SessionTime) : - The time the session ends
Returns: - The session time range object
method init(this, startTimeHour, startTimeMinute, endTimeHour, endTimeMinute, refTimezone)
init - Initialize the object from the start and end session time
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
startTimeHour (int) : - The time hour the session begins
startTimeMinute (int) : - The time minute the session begins
endTimeHour (int) : - The time hour the session ends
endTimeMinute (int) : - The time minute the session ends
refTimezone (string)
Returns: - The session time range object
method init(this, days, timeRanges)
init - Initialize the session object from session days and time range
Namespace types: Session
Parameters:
this (Session) : - The session object that will hold the day and the time range selection
days (SessionDays) : - The session days object that defines the days the session is happening
timeRanges (array) : - The array of all the session time ranges during a session day
Returns: - The session object
method init(this, days, timeRanges, names, colors)
init - Initialize the session object from session days and time range
Namespace types: SessionView
Parameters:
this (SessionView) : - The session view object that will hold the session, the names and the color selections
days (SessionDays) : - The session days object that defines the days the session is happening
timeRanges (array) : - The array of all the session time ranges during a session day
names (array) : - The array of the names of the sessions
colors (array) : - The array of the colors of the sessions
Returns: - The session object
method get_size_in_secs(this)
get_size_in_secs - Count the seconds from start to end in the given timeframe
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The number of seconds inside the time widow for the given timeframe
method get_size_in_secs(this)
get_size_in_secs - Calculate the seconds inside the session
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The number of seconds inside the session
method get_size_in_bars(this)
get_size_in_bars - Count the bars from start to end in the given timeframe
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The number of bars inside the time widow for the given timeframe
method get_size_in_bars(this)
get_size_in_bars - Calculate the bars inside the session
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The number of bars inside the session for the given timeframe
method is_bar_included(this, offset_forward)
is_bar_included - Check if the given bar is between the start and end dates of the window
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
offset_forward (simple int) : - The number of bars forward. Default is 1
Returns: - Whether the current bar is inside the datetime window
method is_bar_included(this, offset_forward)
is_bar_included - Check if the given bar is inside the session as defined by the input params (what "not na(time(timeframe.period, this.to_sess_string()) )" should return if you could write it
Namespace types: Session
Parameters:
this (Session) : - The session with the day and the time range selection
offset_forward (simple int) : - The bar forward to check if it is between the from and to datetimes. Default is 1
Returns: - Whether the current time is inside the session
method to_sess_string(this)
to_sess_string - Formats the session days into a session string with day ids
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object
Returns: - The string of the session day ids
method to_sess_string(this)
to_sess_string - Formats the session time into a session string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The string of the session time
method to_sess_string(this)
to_sess_string - Formats the session time into a session string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The string of the session time
method to_sess_string(this)
to_sess_string - Formats the session into a session string
Namespace types: Session
Parameters:
this (Session) : - The session object with the day and the time range selection
Returns: - The string of the session
method from_sess_string(this, sess)
from_sess_string - Initialize the session days object from the session string
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
sess (string) : - The session string part that represents the days
Returns: - The session days object
method from_sess_string(this, sess)
from_sess_string - Initialize the session time object from the session string in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object that will hold the hour and minute of the time
sess (string) : - The session string part that represents the time HHmm
Returns: - The session time object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the session time object from the session string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object that will hold the hour and minute of the time
sess (string) : - The session string part that represents the time HHmm
refTimezone (simple string) : - The timezone of reference of the 'hour' and 'minute'
Returns: - The session time object
method from_sess_string(this, sess)
from_sess_string - Initialize the session time range object from the session string in exchange timezone (syminfo.timezone)
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
sess (string) : - The session string part that represents the time range HHmm-HHmm
Returns: - The session time range object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the session time range object from the session string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
sess (string) : - The session string part that represents the time range HHmm-HHmm
refTimezone (simple string) : - The timezone of reference of the time ranges
Returns: - The session time range object
method from_sess_string(this, sess)
from_sess_string - Initialize the session object from the session string in exchange timezone (syminfo.timezone)
Namespace types: Session
Parameters:
this (Session) : - The session object that will hold the day and the time range selection
sess (string) : - The session string that represents the session HHmm-HHmm,HHmm-HHmm:ddddddd
Returns: - The session time range object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the session object from the session string
Namespace types: Session
Parameters:
this (Session) : - The session object that will hold the day and the time range selection
sess (string) : - The session string that represents the session HHmm-HHmm,HHmm-HHmm:ddddddd
refTimezone (simple string) : - The timezone of reference of the time ranges
Returns: - The session time range object
method nth_day_after(this, day, n)
nth_day_after - The nth day after the given day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
day (int) : - The day id of the reference day
n (int) : - The number of days after
Returns: - The day id of the nth session day of the week after the given day
method nth_day_before(this, day, n)
nth_day_before - The nth day before the given day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
day (int) : - The day id of the reference day
n (int) : - The number of days after
Returns: - The day id of the nth session day of the week before the given day
method next_day(this)
next_day - The next day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The day id of the next session day of the week
method previous_day(this)
previous_day - The previous day that is session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The day id of the previous session day of the week
method get_sec_in_day(this)
get_sec_in_day - Count the seconds since the start of the day this session time represents
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The number of seconds passed from the start of the day until that session time
method get_ms_in_day(this)
get_ms_in_day - Count the milliseconds since the start of the day this session time represents
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The number of milliseconds passed from the start of the day until that session time
method is_day_included(this, day)
is_day_included - Check if the given day is inside the session days
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
day (int) : - The day to check if it is a trading day
Returns: - Whether the current day is included in the session days
DateTimeWindow
DateTimeWindow - Object that represents a datetime window with a beginning and an end
Fields:
fromDateTime (series int) : - The beginning of the datetime window
toDateTime (series int) : - The end of the datetime window
SessionDays
SessionDays - Object that represent the trading days of the week
Fields:
days (map) : - The map that contains all days of the week and their session flag
SessionTime
SessionTime - Object that represents the time (hour and minutes)
Fields:
hourInDay (series int) : - The hour of the day that ranges from 0 to 24
minuteInHour (series int) : - The minute of the hour that ranges from 0 to 59
minuteInDay (series int) : - The minute of the day that ranges from 0 to 1440. They will be calculated based on hourInDay and minuteInHour when method is called
SessionTimeRange
SessionTimeRange - Object that represents a range that extends from the start to the end time
Fields:
startTime (SessionTime) : - The beginning of the time range
endTime (SessionTime) : - The end of the time range
isOvernight (series bool) : - Whether or not this is an overnight time range
Session
Session - Object that represents a session
Fields:
days (SessionDays) : - The map of the trading days
timeRanges (array) : - The array with all time ranges of the session during the trading days
SessionView
SessionView - Object that visualize a session
Fields:
sess (Session) : - The Session object to be visualized
names (array) : - The names of the session time ranges
colors (array) : - The colors of the session time ranges
Bilson Gann CountGann counting is a method for identifying swing points,trends, and overall market structure. It simplifies price action by drawing short trend lines that summarize moves.
There's essentially 4 types of bar/candle.
Up bar - Higher high and higher low than previous bar
Down bar - Lower high and lower low than previous bar
Inside bar - Lower high and higher low than previous bar
Outside bar - Higher high and lower low than previous bar
We use these determinations to decide how the trendline moves through the candles.
Up bars we join to the high, down bars we join to the low, inside bars are ignored.
There are other indicators that already exist which do this, the difference here is how we handle outside bars.
Other gann counting methods skip outside bars, this method determines how to handle the outside bar after the outside bar is broken.
examples
UP -> OUTSIDE -> UP = Outside bar treated as swing low
UP -> OUTSIDE -> DOWN = Outside bar treated as swing high
DOWN -> OUTSIDE -> UP = Outside bar treated as swing low
DOWN -> OUTSIDE -> DOWN = Outside bar treated as swing high
[TTI] High Volume Close (HVC) Setup📜 ––––HISTORY & CREDITS––––
The High Volume Close (HVC) Setup is a specialised indicator designed for the TradingView platform used to identify specific bar. This tool was developed with the objective of identifying a technical pattern that trades have claimed is significant trading opportunities through a unique blend of volume analysis and price action strategies. It is based on the premise that high-volume bars, when combined with specific price action criteria, can signal key market movements.
The HVC is applicable both for swing and longer term trading and as a technical tool it can be used by traders of any asset type (stocks, ETF, crypto, forex etc).
🦄 –––UNIQUENESS–––
The uniqueness of the HVC Setup lies in its flexibility to determine an important price level based on historically important bar. The idea is to identify significant bars (e.g. those who have created the HIGHEST VOLUME: Ever, Yearly, Quarterly and meet additional criteria from the settings) and plot on the chart the close on that day as a significant level as well as theoretical stop loss and target levels. This approach allows traders to discern high volume bars that are contextually significant — a method not commonly found in standard trading tools.
🎯 ––––WHAT IT DOES––––
The HVC Setup indicator performs a series of calculations to identify high volume close bars/bar (HVC bars) based on the user requirements.
These bars are determined based on the highest volume recorded within a user-inputs:
👉 Period (Ever, Yearly, Quarterly) and must meet additional criteria such as:
👉 a minimum percentage Price Change (change is calculated based on a close/close) and
👉 specific Closing Range requirements for the HVC da.
The theory is that this is a significant bar that is important to know where it is on the chart.
The script includes a comparative analysis of the HVC bar's price against historical price highs (all-time, yearly, quarterly), which provides further context and significance to the identified bars. All of these USER input requirement are then taken into account as a condition to identity the High Volume Close Bar (HVC).
The visual representation includes color-coded bar (default is yellow) and lines to delineate these key trading signals. It then draws a blue line for the place where the close ofthe bar is, a red line that would signify a stop loss and 2 target profit levels equal to 2R and 3R of the risked level (close-stop loss). Additional lines can be turned on/off with their coresponding checkboxes in the settings.
If the user chooses "Ever" for Period - the script will look at the first available bar ever in Tradingview - this is generally the IPO bar;
If the users chooses "Yearly" - the script would look at the highest available bar for a completed year;
If the users chooses "Quarterly" - it would do the same for the quarter. (works on daily timeframe only);
While we have not backtested the performance of the script, this methodology has been widely publicised.
🛠️ ––––HOW TO USE IT––––
To utilize the HVC Setup effectively:
👉Customize Input Settings: Choose the HVC period, percentage change threshold, closing range, stop loss distance, and target multiples according to your trading strategy. Use the tick boxes to enable and disable if a given condition is used within the calculation.
👉Identify HVC Bars: The script highlights HVC bars, indicating potential opportunities based on volume and price action analysis.
👉Interpret Targets and Stop Losses: Use the color-coded lines (green for targets, red for stop losses) to guide your trade entries and exits.
👉Contextual Analysis: Always consider the HVC bar signals in conjunction with overall market trends and additional technical indicators for comprehensive trading decisions.
This script is designed to assist traders in identifying high-potential trading setups by using a combination of volume and price analysis, enhancing traditional methods with a unique, algorithmically driven approach.
Price Volume Harmony Indicator [Nasan]The indicator "Price Volume Harmony Indicator " (abbreviated as PVHI) combines relative volume intensity (RVI) and relative price change (PC) to identify potential synergy or divergence between price and volume movements. Let's break down the key components and discuss how to interpret the output:
Relative Volume Intensity (RVI):
It calculates the mean volume intensity using simple moving averages (SMA) of different periods (5, 8, 13, and 144).
It then computes point volume intensity based on the current volume compared to the previous bar's volume.
The final RVI is a combination of mean and point volume intensities.
Relative Price Change (PC):
It calculates the median absolute deviation (MAD) and the price change relative to MAD for three different lengths (5, 8, and 13).
The average relative PC is a weighted combination of the three PC values.
Normalization:
RVI and PC are normalized using Z-scores (standard scores) to bring them to the same scale. This enables easier comparison.
Histogram Plotting:
The RVI and PC are plotted as histograms below the main price chart. Green color bars represent RVI, and blue color bars indicate PC. The RVI bars are light green when the RVI values are decreasing compared to previous bar. Similarly, when PC bars are light blue it indicates that the PC values are decreasing compared to previous bars.
There is a zero line +/- 0.5 SD lines movements above and below the SD lines are practically
significant.
Interpretation :
(1) Strong Bullish Movement :
This is when both the green bars (RVI) and blue bars (PC) increases and are on the same side above zero .
(2) Strong Bearish Movement :
This is when the green bars (RVI) increases and blue bars (PC) decreases. The green bars above zero but blue bars below zero.
(3) Weak Bullish Movement :
This is when the green bars (RVI) decreases and are below zero but the blue bars (PC) increases and are above zero .
(2) Weak Bearish Movement :
This is when both the green bars (RVI) and blue bars (PC) decreases. The green bars and blue bars are below zero.
This output is slightly hard to read but with practice can be read easily.
chrono_utilsLibrary "chrono_utils"
📝 Description
Collection of objects and common functions that are related to datetime windows session days and time ranges. The main purpose of this library is to handle time-related functionality and make it easy to reason about a future bar checking if it will be part of a predefined session and/or inside a datetime window. All existing session functionality I found in the documentation e.g. "not na(time(timeframe, session, timezone))" are not suitable for strategy scripts, since the execution of the orders is delayed by one bar, due to the script execution happening at the bar close. Moreover, a history operator with a negative value that looks forward is not allowed in any pinescript expression. So, a prediction for the next bar using the bars_back argument of "time()"" and "time_close()" was necessary. Thus, I created this library to overcome this small but very important limitation. In the meantime, I added useful functionality to handle session-based behavior. An interesting utility that emerged from this development is data anomaly detection where a comparison between the prediction and the actual value is happening. If those two values are different then a data inconsistency happens between the prediction bar and the actual bar (probably due to a holiday, half session day, a timezone change etc..)
🤔 How to Guide
To use the functionality this library provides in your script you have to import it first!
Copy the import statement of the latest release by pressing the copy button below and then paste it into your script. Give a short name to this library so you can refer to it later on. The import statement should look like this:
import jason5480/chrono_utils/2 as chr
To check if a future bar will be inside a window first of all you have to initialize a DateTimeWindow object.
A code example is the following:
var dateTimeWindow = chr.DateTimeWindow.new().init(fromDateTime = timestamp('01 Jan 2023 00:00'), toDateTime = timestamp('01 Jan 2024 00:00'))
Then you have to "ask" the dateTimeWindow if the future bar defined by an offset (default is 1 that corresponds th the next bar), will be inside that window:
// Filter bars outside of the datetime window
bool dateFilterApproval = dateTimeWindow.is_bar_included()
You can visualize the result by drawing the background of the bars that are outside the given window:
bgcolor(color = dateFilterApproval ? na : color.new(color.fuchsia, 90), offset = 1, title = 'Datetime Window Filter')
In the same way, you can "ask" the Session if the future bar defined by an offset it will be inside that session.
First of all, you should initialize a Session object.
A code example is the following:
var sess = chr.Session.new().from_sess_string(sess = '0800-1700:23456', refTimezone = 'UTC')
Then check if the given bar defined by the offset (default is 1 that corresponds th the next bar), will be inside the session like that:
// Filter bars outside the sessions
bool sessionFilterApproval = view.sess.is_bar_included()
You can visualize the result by drawing the background of the bars that are outside the given session:
bgcolor(color = sessionFilterApproval ? na : color.new(color.red, 90), offset = 1, title = 'Session Filter')
In case you want to visualize multiple session ranges you can create a SessionView object like that:
var view = SessionView.new().init(SessionDays.new().from_sess_string('2345'), array.from(SessionTimeRange.new().from_sess_string('0800-1600'), SessionTimeRange.new().from_sess_string('1300-2200')), array.from('London', 'New York'), array.from(color.blue, color.orange))
and then call the draw method of the SessionView object like that:
view.draw()
🏋️♂️ Please refer to the "EXAMPLE DATETIME WINDOW FILTER" and "EXAMPLE SESSION FILTER" regions of the script for more advanced code examples of how to utilize the full potential of this library, including user input settings and advanced visualization!
⚠️ Caveats
As I mentioned in the description there are some cases that the prediction of the next bar is not accurate. A wrong prediction will affect the outcome of the filtering. The main reasons this could happen are the following:
Public holidays when the market is closed
Half trading days usually before public holidays
Change in the daylight saving time (DST)
A data anomaly of the chart, where there are missing and/or inconsistent data.
A bug in this library (Please report by PM sending the symbol, timeframe, and settings)
Special thanks to @robbatt and @skinra for the constructive feedback 🏆. Without them, the exposed API of this library would be very lengthy and complicated to use. Thanks to them, now the user of this library will be able to get the most, with only a few lines of code!
Trend Lines [LuxAlgo]Our new "Trend Lines" indicator detects and highlights relevant trendlines on the user chart while keeping it free of as much clutter as possible.
The indicator is thought for real-time usage and includes several filters as well as the ability to estimate trendline angles.
🔶 USAGE
Trendlines can act as support/resistance, with a higher number of tests indicating a more significant support/resistance role.
A broken TrendLine can be indicative of a potential trend reversal. The script highlights breaks with a label.
Users can additionally filter trendlines, only showing trendlines whose angles fall within a user set range:
This allows for the removal of potential clutter from the chart but also helps keep steeper or more horizontal trendlines.
🔶 DETAILS
When a swing (pivot point) is found, a Trendline is drawn when certain conditions are fulfilled.
An essential condition is that a Bearish Trendline (red) always occurs on a lower high, while a Bullish Trendline (blue) occurs on a higher low.
Our implementation will first show an initial dotted-styled TrendLine on confirmation, after which a solid-styled secondary TrendLine will develop. The latter will be used for the real-time detection of breaks at that line:
Furthermore, the script allows you to add more conditions:
🔹 Length (Swings)
A swing develops when a high/low is the highest/lowest against x highs/lows on the left AND right of that bar. x can be set by "Length" in settings.
The following images clarify this. The script confirms a swing where the yellow flag is shown; the high (here visualized with a purple label) is the highest point against x bars left and right of that point.
At that moment, this swing is checked against the previous swing. If all conditions are fulfilled, an initial TrendLine is drawn on confirmation.
After that point, a secondary thicker solid line is seen which keeps progressing bar after bar, until:
• a new TrendLine is formed
• the TrendLine is broken
🔹 Breaks between Swings
Once there is confirmation that a TrendLine can be drawn, the script allows you to filter for breakthroughs on that line. This can be set with "Check breaks between"
Disabled : the initial TrendLine is allowed to be pierced:
Check breaks between point A - point B : no breaks are allowed between both Swing points:
Point A - Current bar : no breaks are allowed between the first Swing point and the point of confirmation ('current' bar):
🔹 TrendLine breaks
As mentioned, the secondary TrendLine (solid line) progresses bar after bar until a new TrendLine is formed or the TrendLine is broken. When a TrendLine is broken, the TrendLine stops progressing, but if there isn't a new TrendLine and price return back, the TrendLine will re-appear, potentially giving several signals when the TrendLine is broken again.
Minimal bars allow you to regulate the amount of signals when the TrendLine is broken.
-> The secondary TrendLine must be uninterrupted for at least x bars before a potential break can be considered.
The following example shows 1 signal against 3 by adjusting this setting from 2 to 5:
🔹 Angles
Angles should normally be calculated when the units of the X and Y axis are the same. However, on our charts, the unit of the X-axis is bar_index (bars), and on the Y-axis the unit is price (¥, €, £, $,...).
It is not easy to normalize and create reasonably valid angles. Often certain angle calculations can differ through price changes or volatility.
Our calculate_slope() function tries to make corresponding angles through all bars.
We do this by calculating the difference between the highest/lowest price values in a certain bar range. The bar range is our X-axis, and the price difference is our Y-axis.
Zooming in/out will not change the amount of bars or the price. Since it does change our view on the chart, and thereby how we see the angles, we have included a setting where you can personalize the ratio between X and Y-axis (Angles -> Ratio X-Y axis).
Settings: Angles - Ratio X-Y axis:
🔶 SETTINGS
🔹 Swings
Length: Lookback period for the detection of swing points.
🔹 Trendline validation
Check breaks between :
Disabled : the initial TrendLine is allowed to be pierced
Check breaks between point A - point B : no breaks are allowed between both Swing points
Point A - Current bar : no breaks are allowed between the first Swing point and the point of confirmation ('current' bar)
Source (breaks) : Source which invalidates TrendLine, default: close
🔹 TrendLine breaks
Minimal bars : The secondary TrendLine must be uninterrupted for at least x bars before a potential break can be considered.
🔹 Angles
Show : Toggle labels.
Ratio X-Y axis : Every user has his preferences regarding zoom, chart layout,...
If the shown angles are not according to your expectations, you can adjust this number.
Only TrendLine between : Only allow TrendLines between the minimum and maximum degrees. Set only the minimal and maximum values above 0.
Lower timeframe chartHi all!
I've made this script to help with my laziness (and to help me (and now you) with efficiency). It's purpose is to, without having to change the chart timeframe, being able to view the lower timeframe bars (and trend) within the last chart bar. The defaults are just my settings (It's based on daily bars), so feel free to change them and maybe share yours! It's also based on stocks, which have limited trading hours, but if you want to view this for forex trading I suggest changing the 'lower time frame' to a higher value since it has more trading hours.
The script prints a label chart (ASCII) based on your chosen timeframe and the trend, based on @KivancOzbilgic script SuperTrend The printed ASCII chart has rows (slots) that are based on ATR (14 bars) and empty gaps are removed. The current trend is decided by a percentage of bars (user defined but defaults to 80%, which is really big but let's you be very conservative in defining a trend to be bullish. Set to 50% to have the trend being decided equally or lower to be more conservative in defining a trend to be bearish) that must have a bullish SuperTrend, it's considered to be bearish otherwise. Big price range (based on the ATR for 14 bars) and big volume (true if the volume is bigger than a user defined simple moving average (defaults to 20 bars)) can be disabled for faster execution.
The chart displayed will consist of bars and thicker bars that has a higher volume than the defined simple moving average. The bars that has a 'big range' (user defined value of ATR (14 days) factor that defaults to 0.5) will also have a wick. The characters used are the following:
Green bar = ┼
Green bar with large volume = ╪
Green bar wick = │
Red bar = ╋
Red bar with large volume = ╬
Red bar wick = ┃
Bar with no range = ─
Bar with no range and high volume = ═
Best of trading!
