VolumeWeightedAveragePriceHey guys,
here i present an advanced version of the standard VWAP indicator, with some configurable offsets.
The basic VWAP is an intraday average price weighted by volume to offer great levels to enter a trade (long or short).
The Formula looks like this:
VWAP= (∑Price * Volume) / ∑Volume
Its very simple to use: if the price closes above the VWAP its bullish, if it closes below its bearish. Because it acts as support and resistance, you can find good entries around this level and also on its offsets.
Feel free to ask if something is unclear now.
Cheers
ابحث في النصوص البرمجية عن "vwap"
Chart Mojo Neutral Unwound CloudPlots days high/low and the Chart Mojo neutral cloud, the zone between vwap and 50% range. A secondary gravity right behind the opening 1 min range. The gray crosses are the vwap the gold dots are 50% of developing range. The shaded area between vwap and 50% range is the Chart Mojo cloud...I think of it as traders from the open tend to unwind to it many times a day. More returns on a trend day but you will see urges toward it on trend days. Price tends to urge to it ahead of 10:30 session "1" and 1:15 Session 2. If you get used to watching it and its relationship to price and the opening 1 min range you should start to see tendencies as to when price unwinds toward it.. etc. Where price is in relation to the cloud and the clouds relationship to the opening 1 min range can reveal real time bias. You will being to see, upon observation how traders target the vwap and 50% with target tier of buys and sells etc. Often unwinds to the zones gravity. It takes force or a catalyst to break the gravity. I use it in conjuction with Time Zone theory and Wave and Pattern force...and look to leading correlating hi beta movers and internals like tick and new streaming highs-new straming lows to get jump on what you see on a big etf or index etc. If you intraday tendencies the neutral is very helpful.
[Linus] VWAO DeviationThe VWAP (Volume Weighted Average Price) Deviation Script is a sophisticated tool designed to help traders analyze the interplay between price and volume. By calculating deviations from the VWAP, it identifies critical support and resistance levels, enabling more informed trading decisions.
This script computes the VWAP based on a selected data source (defaulting to the closing price) and determines deviations above and below it using either the Average Deviation or Standard Deviation method. Users can customize their preference through the script's input settings. These deviations are visually plotted as bands on the chart, offering clear insights into areas where price may revert or break out.
A standout feature of the script is its Cross Count Monitor, which tracks how often the price crosses above the Upper Deviation Level 2 and below the Lower Deviation Level 2 within a user-defined lookback period. This data is displayed in a table at the bottom-right corner of the chart and can be toggled on or off via an input setting.
The Cross Count Monitor provides traders with valuable historical insights into the frequency of price interactions with deviation levels, helping to identify potential trading opportunities based on established price behaviors. This functionality makes the script an indispensable tool for traders seeking to enhance their market analysis and strategy development.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
CPR by NKDCentral Pivot Range (CPR) Trading Strategy:
The Central Pivot Range (CPR) is a widely-used tool in technical analysis, helping traders pinpoint potential support and resistance levels in the market. By using the CPR effectively, traders can better gauge market trends and determine favorable entry and exit points. This guide explores how the CPR works, outlines its calculation, and describes how traders can enhance their strategies using an extended 10-line version of CPR.
What Really Central Pivot Range (CPR) is?
At its core, the CPR consists of three key lines:
Pivot Point (PP) – The central line, calculated as the average of the previous day’s high, low, and closing prices.
Upper Range (R1) – Positioned above the Pivot Point, acting as a potential ceiling where price may face resistance.
Lower Range (S1) – Found below the Pivot Point, serving as a potential floor where price might find support.
Advanced traders often expand on the traditional three-line CPR by adding extra levels above and below the pivot, creating up to a 10-line system. This extended CPR allows for a more nuanced understanding of the market and helps identify more detailed trading opportunities.
Applying CPR for Trading Success
1. How CPR is Calculation
The CPR relies on the previous day's high (H), low (L), and close (C) prices to create its structure:
Pivot Point (PP) = (H + L + C) / 3
First Resistance (R1) = (2 * PP) - L
First Support (S1) = (2 * PP) - H
Additional resistance levels (R2, R3) and support levels (S2, S3) are calculated by adding or subtracting multiples of the previous day’s price range (H - L) from the Pivot Point.
2. Recognizing the Market Trend
To effectively trade using CPR, it’s essential to first determine whether the market is trending up (bullish) or down (bearish). In an upward-trending market, traders focus on buying at support levels, while in a downward market, they look to sell near resistance.
3. Finding Ideal Entry Points
Traders often look to enter trades when price approaches key levels within the CPR range. Support levels (S1, S2) offer buying opportunities, while resistance levels (R1, R2) provide selling opportunities. These points are considered potential reversal zones, where price may bounce or reverse direction.
4. Managing Risk with Stop-Loss Orders
Proper risk management is crucial in any trading strategy. A stop-loss should be set slightly beyond the support level for buy positions and above the resistance level for sell positions, ensuring that losses are contained if the market moves against the trader’s position.
5. Determining Profit Targets
Profit targets are typically set based on the distance between entry points and the next support or resistance level. Many traders apply a risk-reward ratio, aiming for larger potential profits compared to the potential losses. However, if the next resistance and support level is far then middle levels are used for targets (i.e. 50% of R1 and R2)
6. Confirmation Through Other Indicators
While CPR provides strong support and resistance levels, traders often use additional indicators to confirm potential trade setups. Indicators such as moving averages can
help validate the signals provided by the CPR.
7. Monitoring Price Action At CPR Levels
Constantly monitoring price movement near CPR levels is essential. If the price fails to break through a resistance level (R1) or holds firm at support (S1), it can offer cues on when to exit or adjust a trade. However, a strong price break past these levels often signals a continued trend.
8. Trading Breakouts with CPR
When the price breaks above resistance or below support with strong momentum, it may signal a potential breakout. Traders can capitalize on these movements by entering positions in the direction of the breakout, ideally confirmed by volume or other technical indicators.
9. Adapting to Changing Market Conditions
CPR should be used in the context of broader market influences, such as economic reports, news events, or geopolitical shifts. These factors can dramatically affect market direction and how price reacts to CPR levels, making it important to stay informed about external market conditions.
10. Practice and Backtesting for Improvements
Like any trading tool, the CPR requires practice. Traders are encouraged to backtest their strategies on historical price data to get a better sense of how CPR works in different market environments. Continuous analysis and practice help improve decision-making and strategy refinement.
The Advantages of Using a 10-Line CPR System
An extended 10-line CPR system—comprising up to five resistance and five support levels—provides more granular control and insight into market movements. This expanded view helps traders better gauge trends and identify more opportunities for entry and exit. Key benefits include:
R2, S2 Levels: These act as secondary resistance or support zones, giving traders additional opportunities to refine their trade entries and exits.
R3, S3 Levels: Provide an even wider range for identifying reversals or trend continuations in more volatile markets.
Flexibility: The broader range of levels allows traders to adapt to changing market conditions and make more precise decisions based on market momentum.
So in Essential:
The Central Pivot Range is a valuable tool for traders looking to identify critical price levels in the market. By providing a clear framework for identifying potential support and resistance zones, it helps traders make informed decisions about entering and exiting trades. However, it’s important to combine CPR with sound risk management and additional confirmation through other technical indicators for the best results.
Although no trading tool guarantees success, the CPR, when used effectively and combined with practice, can significantly enhance a trader’s ability to navigate market fluctuations.
MTF Regression with Forecast### **MTF Regression with Forecast, Treasury Yield, Additional Variable & VWAP Filter - Enhanced with Long Regression**
Unlock advanced market insights with our **MTF Regression** indicator, meticulously designed for traders seeking comprehensive multi-timeframe analysis combined with powerful forecasting tools. Whether you're a seasoned trader or just starting out, this indicator offers a suite of features to enhance your trading strategy.
#### **🔍 Key Features:**
- **Multi-Timeframe (MTF) Regression:**
- **Fast, Slow, & Long Regressions:** Analyze price trends across multiple timeframes to capture both short-term movements and long-term trends.
- **Customizable Price Inputs:**
- **Flexible Price Selection:** Choose between Close, Open, High, or Low prices to suit your trading style.
- **Price Transformation:** Option to apply Exponential Moving Averages (EMA) for smoother trend analysis.
- **Diverse Regression Methods:**
- **Multiple Algorithms:** Select from Linear, Exponential, Hull Moving Average (HMA), Weighted Moving Average (WMA), or Spline regressions to best fit your analysis needs.
- **Integrated External Data:**
- **10-Year Treasury Yield:** Incorporate macroeconomic indicators to refine regression accuracy.
- **Additional Variables:** Enhance your analysis by integrating data from other tickers (e.g., NASDAQ:AAPL).
- **Advanced Filtering Options:**
- **VWAP Filter:** Align signals with the Volume Weighted Average Price for improved trade entries.
- **Price Action Filter:** Ensure price behavior supports the generated signals for higher reliability.
- **Enhanced Signal Generation:**
- **Bullish & Bearish Signals:** Identify potential trend reversals and continuations with clear visual cues.
- **Predictive Signals:** Forecast future price movements with forward-looking arrows based on regression slopes.
- **Slope & Acceleration Thresholds:** Customize minimum slope and acceleration levels to fine-tune signal sensitivity.
- **Forecasting Capabilities:**
- **Projection Lines:** Visualize future price trends by extending regression lines based on current slope data.
- **User-Friendly Interface:**
- **Organized Settings Groups:** Easily navigate through price inputs, regression settings, integration options, and more.
- **Customizable Alerts:** Stay informed with configurable alerts for bullish, bearish, and predictive signals.
#### **📈 Why Choose MTF Regression Indicator?**
- **Comprehensive Analysis:** Combines multiple regression techniques and external data sources for a well-rounded market view.
- **Flexibility:** Highly customizable to fit various trading strategies and preferences.
- **Enhanced Decision-Making:** Provides clear signals and forecasts to support informed trading decisions.
- **Efficiency:** Optimized to deliver reliable performance without overloading your trading platform.
Elevate your trading game with the **MTF Regression with Forecast, Treasury Yield, Additional Variable & VWAP Filter** indicator. Harness the power of multi-timeframe analysis and predictive forecasting to stay ahead in the dynamic markets.
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*Feel free to reach out for more information or support. Happy Trading!*
Multi-Timeframe Trend TableThe "Multi-Timeframe Trend Table" indicator is a tool that consolidates a variety of critical trading metrics into a single, easy-to-read table format. This indicator is especially useful for traders who need to analyze multiple timeframes and indicators simultaneously to make informed trading decisions. By displaying a broad spectrum of data including trend information, rangebound status, volatility levels, VWAP (Volume Weighted Average Price), and specific candlestick patterns, the indicator provides a comprehensive overview of market conditions across different timeframes.
Functionality and Components
At its core, the indicator provides real-time insights into market trends by showing whether each timeframe is experiencing an upward, downward, or neutral trend based on simple moving averages. This is complemented by the "Rangebound" status, which indicates whether the price is trading within a defined range, giving insights into market consolidation periods. This can be critical for identifying breakouts or breakdowns from established ranges.
Volatility Measurement
Another key feature of the indicator is the "Volatility" column, which rates the market's volatility on a scale from 1 to 10. This feature uses the Average True Range (ATR) to assess how drastically prices are changing within a given timeframe, providing a numerical value that helps traders understand the intensity of price movements. High volatility levels (scores above 6) are highlighted, which can be crucial for strategies that prefer high volatility.
VWAP and Candlestick Patterns
The indicator also displays the VWAP, which is essential for traders who focus on volume as it shows the average price a security has traded at throughout the day, based on both volume and price. It is especially useful for traders looking to confirm trend directions or catch potential reversals. Additionally, the "Candle" column enhances the indicator's utility by identifying specific candlestick patterns like Doji, Hammer, Inverted Hammer, Bullish Engulfing, and Bearish Engulfing, which are pivotal for pinpointing momentum changes and potential entry or exit points.
Usage Strategy
Traders can utilize this indicator by setting up specific rules based on the information provided. For instance, a possible strategy could involve entering a trade when a Bullish Engulfing pattern appears in a low-volatility environment as indicated by a volatility score under 6, suggesting a potential uptrend start with limited downside risk. Similarly, a trader might consider exiting a position or taking a short position when a Bearish Engulfing pattern is identified during high volatility periods, signaling possible sharp price declines.
Adaptability and Customization
An added advantage is the indicator’s adaptability; traders can customize which columns to display based on their trading preferences and strategies. Whether focusing on trends, volatility, or candlestick patterns, users can configure the table to match their specific needs. This makes it a versatile tool suited for various trading styles and objectives, from day trading to swing trading.
Overall Utility
Overall, the "Multi-Timeframe Trend Table" indicator is an invaluable asset for traders who manage multiple instruments across different timeframes, offering a bird's-eye view of the markets in one concise table. It aids in quick decision-making by providing all necessary data points at a glance, reducing the need to switch between multiple charts and potentially missing critical market movements. By integrating trend analysis with volatility and candlestick patterns, it equips traders with a powerful synthesis of technical analysis tools to enhance their trading strategies and improve market timing.
Trend Deviation strategy - BTC [IkkeOmar]Intro:
This is an example if anyone needs a push to get started with making strategies in pine script. This is an example on BTC, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay.
This strategy integrates several technical indicators to determine market trends and potential trade setups. These indicators include:
Directional Movement Index (DMI)
Bollinger Bands (BB)
Schaff Trend Cycle (STC)
Moving Average Convergence Divergence (MACD)
Momentum Indicator
Aroon Indicator
Supertrend Indicator
Relative Strength Index (RSI)
Exponential Moving Average (EMA)
Volume Weighted Average Price (VWAP)
It's crucial for you guys to understand the strengths and weaknesses of each indicator and identify synergies between them to improve the strategy's effectiveness.
Indicator Settings:
DMI (Directional Movement Index):
Length: This parameter determines the number of bars used in calculating the DMI. A higher length may provide smoother results but might lag behind the actual price action.
Bollinger Bands:
Length: This parameter specifies the number of bars used to calculate the moving average for the Bollinger Bands. A longer length results in a smoother average but might lag behind the price action.
Multiplier: The multiplier determines the width of the Bollinger Bands. It scales the standard deviation of the price data. A higher multiplier leads to wider bands, indicating increased volatility, while a lower multiplier results in narrower bands, suggesting decreased volatility.
Schaff Trend Cycle (STC):
Length: This parameter defines the length of the STC calculation. A longer length may result in smoother but slower-moving signals.
Fast Length: Specifies the length of the fast moving average component in the STC calculation.
Slow Length: Specifies the length of the slow moving average component in the STC calculation.
MACD (Moving Average Convergence Divergence):
Fast Length: Determines the number of bars used to calculate the fast EMA (Exponential Moving Average) in the MACD.
Slow Length: Specifies the number of bars used to calculate the slow EMA in the MACD.
Signal Length: Defines the number of bars used to calculate the signal line, which is typically an EMA of the MACD line.
Momentum Indicator:
Length: This parameter sets the number of bars over which momentum is calculated. A longer length may provide smoother momentum readings but might lag behind significant price changes.
Aroon Indicator:
Length: Specifies the number of bars over which the Aroon indicator calculates its values. A longer length may result in smoother Aroon readings but might lag behind significant market movements.
Supertrend Indicator:
Trendline Length: Determines the length of the period used in the Supertrend calculation. A longer length results in a smoother trendline but might lag behind recent price changes.
Trendline Factor: Specifies the multiplier used in calculating the trendline. It affects the sensitivity of the indicator to price changes.
RSI (Relative Strength Index):
Length: This parameter sets the number of bars over which RSI calculates its values. A longer length may result in smoother RSI readings but might lag behind significant price changes.
EMA (Exponential Moving Average):
Fast EMA: Specifies the number of bars used to calculate the fast EMA. A shorter period results in a more responsive EMA to recent price changes.
Slow EMA: Determines the number of bars used to calculate the slow EMA. A longer period results in a smoother EMA but might lag behind recent price changes.
VWAP (Volume Weighted Average Price):
Default settings are typically used for VWAP calculations, which consider the volume traded at each price level over a specific period. This indicator provides insights into the average price weighted by trading volume.
backtest range and rules:
You can specify the start date for backtesting purposes.
You can can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
LONG:
DMI Cross Up: The Directional Movement Index (DMI) indicates a bullish trend when the positive directional movement (+DI) crosses above the negative directional movement (-DI).
Bollinger Bands (BB): The price is below the upper Bollinger Band, indicating a potential reversal from the upper band.
Momentum Indicator: Momentum is positive, suggesting increasing buying pressure.
MACD (Moving Average Convergence Divergence): The MACD line is above the signal line, indicating bullish momentum.
Supertrend Indicator: The Supertrend indicator signals an uptrend.
Schaff Trend Cycle (STC): The STC indicates a bullish trend.
Aroon Indicator: The Aroon indicator signals a bullish trend or crossover.
When all these conditions are met simultaneously, the strategy considers it a favorable opportunity to enter a long trade.
SHORT:
DMI Cross Down: The Directional Movement Index (DMI) indicates a bearish trend when the negative directional movement (-DI) crosses above the positive directional movement (+DI).
Bollinger Bands (BB): The price is above the lower Bollinger Band, suggesting a potential reversal from the lower band.
Momentum Indicator: Momentum is negative, indicating increasing selling pressure.
MACD (Moving Average Convergence Divergence): The MACD line is below the signal line, signaling bearish momentum.
Supertrend Indicator: The Supertrend indicator signals a downtrend.
Schaff Trend Cycle (STC): The STC indicates a bearish trend.
Aroon Indicator: The Aroon indicator signals a bearish trend or crossover.
When all these conditions align, the strategy considers it an opportune moment to enter a short trade.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Furthermore this strategy uses both trend and mean-reversion systems, that is usually a no-go if you want to build robust trend systems .
Don't hesitate to comment if you have any questions or if you have some good notes for a beginner.
ATR Bands with Optional Risk/Reward Colors█ OVERVIEW
This indicator projects ATR bands and, optionally, colors them based on a risk/reward advantage for those who trade breakouts/breakdowns using moving averages as partial or full exit points.
█ DEFINITIONS
► True Range
The True Range is a measure of the volatility of a financial asset and is defined as the maximum difference among one of the following values:
- The high of the current period minus the low of the current period.
- The absolute value of the high of the current period minus the closing price of the previous period.
- The absolute value of the low of the current period minus the closing price of the previous period.
► Average True Range
The Average True Range was developed by J. Welles Wilder Jr. and was introduced in his 1978 book titled "New Concepts in Technical Trading Systems". It is calculated as an average of the true range values over a certain number of periods (usually 14) and is commonly used to measure volatility and set stop-loss and profit targets (1).
For example, if you are looking at a daily chart and you want to calculate the 14-day ATR, you would take the True Range of the previous 14 days, calculate their average, and this would be the ATR for that day. The process is then repeated every day to obtain a series of ATR values over time.
The ATR can be smoothed using different methods, such as the Simple Moving Average (SMA), the Exponential Moving Average (EMA), or others, depending on the user's preferences or analysis needs.
► ATR Bands
The ATR bands are created by adding or subtracting the ATR from a reference point (usually the closing price). This process generates bands around the central point that expand and contract based on market volatility, allowing traders to assess dynamic support and resistance levels and to adapt their trading strategies to current market conditions.
█ INDICATOR
► ATR Bands
The indicator provides all the essential parameters for calculating the ATR: period length, time frame, smoothing method, and multiplier.
It is then possible to choose the reference point from which to create the bands. The most commonly used reference points are Open, High, Low, and Close, but you can also choose the commonly used candle averages: HL2, HLC3, HLCC4, OHLC4. Among these, there is also a less common "OC2", which represents the average of the candle body. Additionally, two parameters have been specifically created for this indicator: Open/Close and High/Low.
With the "Open/Close" parameter, the upper band is calculated from the higher value between Open and Close, while the lower one is calculated from the lower value between Open and Close. In the case of bullish candles, therefore, the Close value is taken as the starting point for the upper band and the Open value for the lower one; conversely, in bearish candles, the Open value is used for the upper band and the Close value for the lower band. This setting can be useful for precautionally generating broader bands when trading with candlesticks like hammers or inverted hammers.
The "High/Low" parameter calculates the upper band starting from the High and the lower band starting from the Low. Among all the available options, this one allows drawing the widest bands.
Other possible options to improve the drawing of ATR bands, aligning them with the price action, are:
• Doji Smoothing: When the current candle is a doji (having the same Open and Close price), the bands assume the values they had on the previous candle. This can be useful to avoid steep fluctuations of the bands themselves.
• Extend to High/Low: Extends the bands to the High or Low values when they exceed the value of the band.
• Round Last Cent: Expands the upper band by one cent if the price ends with x.x9, and the lower band if the price ends with x.x1. This function only works when the asset's tick is 0.01.
► Risk/Reward Advantage
The indicator optionally colors the ATR bands after setting a breakpoint, one or two risk/reward ratios, and a series of moving averages. This function allows you to know in advance whether entering a trade can provide an advantage over the risk. The band is colored when the ratio between the distance from the break point to the band and the distance from the break point to the first available moving average reaches at least the set ratio value. It is possible to set two colorings, one for a minimum risk/reward ratio and one for an optimal risk/reward ratio.
The break point can be chosen between High/Low (High in case of breakout, Low in case of breakdown) or Open/Close (on breakouts, Close with bullish candles or Open with bearish candles; on breakdowns, Close with bearish candles or Open with bullish candles).
It is possible to choose up to 10 moving averages of various types, including the VWAP with the Anchor Period (2).
Depending on the "Price to MA" setting, the bands can be individually or simultaneously colored.
By selecting "Single Direction," the risk/reward calculation is performed only when all moving averages are above or below the break point, resulting in only one band being colored at a time. For this reason, when the break point is in between the moving averages, the calculation is not executed. This setting can be useful for strategies involving price movement from a level towards a series of specific moving averages (for example, in reversals starting from a certain level towards the VWAP with possible partial take profits on some previous moving averages, or simply in trend following towards one or more moving averages).
Choosing "Both Directions" the risk/reward ratio is calculated based on the first available moving averages both above and below the price. This setting is useful for those who operate in range bound markets or simply take advantage of movements between moving averages.
█ NOTE
This script may not be suitable for scalping strategies that require immediate entries due to the inability to know the ATR of a candle in advance until its closure. Once the candle is closed, you should have time to place a stop or stop-limit order, so your strategy should not anticipate an immediate start with the next candle. Even more conveniently, if your strategy involves an entry on a pullback, you can place a limit order at the breakout level.
(1) www.tradingview.com
(2) For convenience, the code for the Anchor Period has been entirely copied from the VWAP code provided by TradingView.
Market Internals (TICK, ADD, VOLD, TRIN, VIX)OVERVIEW
This script allows you to perform data transformations on Market Internals, across exchanges, and specify signal parameters, to more easily identify sentiment extremes.
Notable transformations include:
1. Cumulative session values
2. Directional bull-bear Ratios and Percent Differences
3. Data Normalization
4. Noise Reduction
This kind of data interaction is very useful for understanding the relationship between two mutually exclusive metrics, which is the essence of Market Internals: Up vs. Down. Even so, they are not possible with symbol expressions alone. And the kind of symbol expression needed to produce baseline data that can be reliably transformed is opaque to most traders, made worse by the fact that prerequisite symbol expressions themselves are not uniform across symbols. It's very nuanced, and if this last bit was confusing … exactly.
All this to say, rather than forcing that burden onto you, I've baked the baseline symbol expressions into the indicator so: 1) the transform functions consistently ingest the baseline data in the correct format and 2) you don't have to spend time trying to figure it all out. Trading is hard. There's no need to make it harder.
INPUTS
Indicator
Allows you to specify the base Market Internal and Exchange data to use. The list of Market Internals is simplified to their fundamental representation (TICK, ADD, VOLD, TRIN, VIX, ABVD, TKCD), and the list of Exchange data is limited to the most common (NYSE, NASDAQ, All US Stocks). There are also options for basic exchange combinations (Sum or Average of NYSE & NASDAQ).
Mode
Short for "Plot Mode", this is where you specify the bars style (Candles, Bars, Line, Circles, Columns) and the source value (used for single value plots and plot color changes).
Scale
This is the first and second data transformation grouped together. The default is to show the origin data as it might appear on a chart. You can then specify if each bar should retain it's unique value (Bar Value) or be added to a running total (Cumulative). You can also specify if you would like the data to remain unaltered (Raw) or converted to a directional ratio (Ratio) or a percentage (Percent Diff). These options determine the scale of the plot.
Both Ratio and Percent Diff. convert a given symbol into a positive or negative number, where positive numbers are bullish and negative numbers are bearish.
Ratio will divide Bull values by Bear values, then further divide -1 by the quotient if it is less than 1. For example, if "0.5" was the quotient, the Ratio would be "-2".
Percent Diff. subtracts Bear values from Bull values, then divides that difference by the sum of Bull and Bear values multiplied by 100. If a Bull value was "3" and Bear value was "7", the difference would be "-4", the sum would be "10", and the Percent Diff. would be "-40", as the difference is both bearish and 40% of total.
Ratio Norm. Threshold
This is the third data transformation . While quotients can be less than 1, directional ratios are never less than 1. This can lead to barcode-like artifacts as plots transition between positive and negative values, visually suggesting the change is much larger than it actually is. Normalizing the data can resolve this artifact, but undermines the utility of ratios. If, however, only some of the data is normalized, the artifact can be resolved without jeopardizing its contextual usefulness.
The utility of ratios is how quickly they communicate proportional differences. For example, if one side is twice as big as the other, "2" communicates this efficiently. This necessarily means the numerical value of ratios is worth preserving. Also, below a certain threshold, the utility of ratios is diminished. For example, an equal distribution being represented as 0, 1, 1:1, 50/50, etc. are all equally useful. Thus, there is a threshold, above which we want values to be exact, and below which the utility of linear visual continuity is more important. This setting accounts for that threshold.
When this setting is enabled, a ratio will be normalized to 0 when 1:1, scaled linearly toward the specified threshold when greater than 1:1, and then retain its exact value when the threshold is crossed. For example, with a threshold of "2", 1:1 = 0, 1.5:1 = 1, 2:1 = 2, 3:1 = 3, etc.
With all this in mind, most traders will want to set the ratios threshold at a level where accuracy becomes more important than visual continuity. If this level is unknown, "2" is a good baseline.
Reset cumulative total with each new session
Cumulative totals can be retained indefinitely or be reset each session. When enabled, each session has its own cumulative total. When disabled, the cumulative total is maintained indefinitely.
Show Signal Ranges
Because everything in this script is designed to make identifying sentiment extremes easier, an obvious inclusion would be to not only display ranges that are considered extreme for each Market Internal, but to also change the color of the plot when it is within, or beyond, that range. That is exactly what this setting does.
Override Max & Min
While the min-max signal levels have reasonable defaults for each symbol and transformation type, the Override Max and Override Min options allow you to … (wait for it) … override the max … and min … signal levels. This may be useful should you find a different level to be more suitable for your exact configuration.
Reduce Noise
This is the fourth data transformation . While the previous Ratio Norm. Threshold linearly stretches values between a threshold and 0, this setting will exponentially squash values closer to 0 if below the lower signal level.
The purpose of this is to compress data below the signal range, then amplify it as it approaches the signal level. If we are trying to identify extremes (the signal), minimizing values that are not extreme (the noise) can help us visually focus on what matters.
Always keep both signal zones visible
Some traders like to zoom in close to the bars. Others prefer to keep a wider focus. For those that like to zoom in, if both signals were always visible, the bar values can appear squashed and difficult to discern. For those that keep a wider focus, if both signals were not always visible, it's possible to lose context if a signal zone is vertically beyond the pane. This setting allows you to decide which scenario is best for you.
Plot Colors
These define the default color, within signal color, and beyond signal color for Bullish and Bearish directions.
Plot colors should be relative to zero
When enabled, the plot will inherit Bullish colors when above zero and Bearish colors when below zero. When disabled and Directional Colors are enabled (below), the plot will inherit the default Bullish color when rising, and the default Bearish color when falling. Otherwise, the plot will use the default Bullish color for all directions.
Directional colors
When the plot colors should be relative to zero (above), this changes the opacity of a bars color if moving toward zero, where "100" percent is the full value of the original color and "0" is transparent. When the plot colors are NOT relative to zero, the plot will inherit Bullish colors when rising and Bearish colors when falling.
Differentiate RTH from ETH
Market Internal data is typically only available during regular trading hours. When this setting is enabled, the background color of the indicator will change as a reminder that data is not available outside regular trading hours (RTH), if the chart is showing electronic trading hours (ETH).
Show zero line
Similar to always keeping signal zones visible (further up), some traders prefer zooming in while others prefer a wider context. This setting allows you to specify the visibility of the zero line to best suit your trading style.
Linear Regression
Polynomial regressions are great for capturing non-linear patterns in data. TradingView offers a "linear regression curve", which this script is using as a substitute. If you're unfamiliar with either term, think of this like a better moving average.
Symbol
While the Market Internal symbol will display in the status line of the indicator, the status line can be small and require more than a quick glance to read properly. Enabling this setting allows you to specify if / where / how the symbol should display on the indicator to make distinguishing between Market Internals more efficient.
Speaking of symbols, this indicator is designed for, and limited to, the following …
TICK - The TICK subtracts the total number of stocks making a downtick from the total number of stocks making an uptick.
ADD - The Advance Decline Difference subtracts the total number of stocks below yesterdays close from the total number of stocks above yesterdays close.
VOLD - The Volume Difference subtracts the total declining volume from the total advancing volume.
TRIN - The Arms Index (aka. Trading Index) divides the ratio of Advancing Stocks / Volume by the ratio of Declining Stocks / Volume. Given the inverse correlation of this index to market movement, when transforming it to a Ratio or Percent Diff., its values are inverted to preserve the bull-bear sentiment of the transformations.
VIX - The CBOE Volatility Index is derived from SPX index option prices, generating a 30-day forward projection of volatility. Given the inverse correlation of this index to market movement, when transforming it to a Ratio or Percent Diff., its values are inverted and normalized to the sessions first bar to preserve the bull-bear sentiment of the transformations. Note: If you do not have a Cboe CGIF subscription , VIX data will be delayed and plot unexpectedly.
ABVD - The Above VWAP Difference is an unofficial index measuring all stocks above VWAP as a percent difference. For the purposes of this indicator (and brevity), TradingViews PCTABOVEVWAP has has been shortened to simply be ABVD.
TKCD - The Tick Cumulative Difference is an unofficial index that subtracts the total number of market downticks from the total number of market upticks. Where "the TICK" (further up) is a measurement of stocks ticking up and down, TKCD is a measurement of the ticks themselves. For the purposes of this indicator (and brevity), TradingViews UPTKS and DNTKS symbols have been shorted to simply be TKCD.
INSPIRATION
I recently made an indicator automatically identifying / drawing daily percentage levels , based on 4 assumptions. One of these assumptions is about trend days. While trend days do not represent the majority of days, they can have big moves worth understanding, for both capitalization and risk mitigation.
To this end, I discovered:
• Article by Linda Bradford Raschke about Capturing Trend Days.
• Video of Garrett Drinon about Trend Day Trading.
• Videos of Ryan Trost about How To Use ADD and TICK.
• Article by Jason Ruchel about Overview of Key Market Internals.
• Including links to resources outside of TradingView violates the House Rules, but they're not hard to find, if interested.
These discoveries inspired me adopt the underlying symbols in my own trading. I also found myself wanting to make using them easier, the net result being this script.
While coding everything, I also discovered a few symbols I believe warrant serious consideration. Specifically the Percent Above VWAP symbols and the Up Ticks / Down Ticks symbols (referenced as ABVD and TKCD in this indicator, for brevity). I found transforming ABVD or TKCD into a Ratio or Percent Diff. to be an incredibly useful and worthy inclusion.
ABVD is a Market Breadth cousin to Brian Shannon's work, and TKCD is like the 3rd dimension of the TICKs geometry. Enjoy.
Buying Selling Volume StrategyFirst I would like to give the original credit and thanks to @ceyhun for his amazing volume script.
The way I decided to convert it into a strategy is divided into multiple types.
First, I decided in order to smooth out the values and make it more accurate to adapt the values to multiple timeframes.
After that I took the initial values from the buyers and sellers , and made a rest operation between them to have a flat difference between the power of both sides.
WIth that later on I decided to to apply a volatility filter,in this case bollinger bands, in order to find out potential leading trends.
At the same time in order to filter even more, I decided to make use as well for weekly VWAP values of the asset used.
Lastly I added a dynamic risk management into it , based on the ATR Daily values of the asset values.
As for the rules used, for example for long, I am looking that the price of the asset is above the weekly VWAP, after that I am checking that the MTF volume rest operation is both bullish and above the upper side of the bollinger.
For short we would want the asset to be below the weekly VWAP, and the volume to be bearish and above the upper side of bollinger.
The exit is either based on daily ATR values multipliers, or if we have a reverse condition.
If you have any questions, please let me know !
Balance Zone ExtensionBalance zones are an aspect of trading that many traders notice. Balance Zones are formed when a market is in equilibrium and respects a certain high and low multiple times. These zones could also be called accumulation or distribution areas depending on the price action. If the term "choppy" is used to describe a given markets price action, it is probably a fair statement to say that the market is currently in a Balance Zone.
This script is a take on vwaptrader1's teachings where you take a balance zone and "double it" to get a target if/when it does break out of balance. It provides an automated way of extending levels based on a given balance range.
The lines plotted by the script are calculated based off of the balance high/low inputs, how many sections are desired per zone, and how many boxes to plot based on the other user inputs.
Warning: Due to a current limitation of the Pine, this script is only allowed to plot up to 500 lines total. If you start to notice lines starting to disappear or you begin getting a script error, double check the input settings as the script may have crossed the 500 line threshold.
This can be used in conjunction with Fixed Range Volume Profile . Select the balance range with the Fixed Volume Profile . Note the Value Area High and Value Area Low prices and input those into the balance range High/Low inputs.
Use to create price targets from Balance Zone Breakouts
A recent example of this idea in action on ticker ES1! 2 hour chart where the balance range was found and the target (double the box size of the balance range) was hit.
Another example of this same concept but on a normal security like AAPL but on a 30 minute chart:
Extending the usefulness even further to crypto on BTCUSD with a 5 minute chart:
Use to create reference levels for future price action
The other way to utilize this is to provide future reference levels from a key balance range from the past.
Here is another example utilizing the AMD daily chart . First, a balance zone was noted for all of 2017:
Moving forward to the most recent price action in 2023, notice that the box extension levels are still fairly well respected almost 6 years later!
Range Analysis - By LeviathanThe Interactive Range Analysis script is an essential tool for analyzing price ranges. It automatically draws important range levels, generates a Volume Profile or Open Interest profile and horizontal/vertical heatmaps, plots the anchored VWAP, draws Fibonacci levels, and much more.
How to use the indicator:
1. The script will prompt you to select the "Start Time" and "End Time" using Tradingview's interactive interface. These two points will determine the length of the range.
2. Once you have selected the range, the script will automatically anchor the range highs and lows to the highest and lowest close/wick/hlc3/ohlc4 (whichever you prefer).
3. You can then begin exploring different tools and options such as Quarters, Eighths, Fibonacci, Outer Levels, VWAP, Horizontal Volume/OI Heatmap, Vertical Volume/OI Heatmap, Fixed Range Volume Profile, Open Interest Profile, Value Area, VAH, VAL, and POC.
4. You can adjust the range by dragging the Start Time and End Time anchors or by removing/reapplying the script.
Tool overview
Range Levels
After selecting your preferred time range, the script will identify and draw a range high level and a range low level, which serve as a base for other important levels. “Half” is the level halfway between the range high and range low. “Quarters” will, as the name suggests, split the range into four equal zones (quarters) and “Eighths” will split the range into eight equal zones (eighths).
”Fibonacci” option allows you to display Fibonacci retracement levels (0.786, 0.618, 0.382, 0.236). “VWAP” will plot a Volume Weighted Average Price, anchored to the start of the range. “Direction” input lets you choose whether your range is UP or DOWN trending in order to make sure that the Fibonacci levels and labels are generated and assigned correctly. With “Outer” turned ON, the script will also generate active levels (quarters/eighths/Fibonacci) above and below the selected price range. “Extend Right” will extend all levels to the right indefinitely, while “Extend (+Bars)” lets you choose how far right the levels get extended. “Diagonal Line” is drawn from the bottom left of the range to the top right of the range or from the top left of the range to the bottom right of the range, depending on the “Direction” input.
Volume Profile / Open Interest Profile
After selecting the “Data Type”, Volume Profile or OI Profile can be generated by turning ON the “Volume/OI Profile” option.
“Resolution” input defines the amount of nodes/rows in the range that are used in profile/heatmap generation for distributing the data. While you can increase the “Resolution” to get better, more granular profiles, you should keep in mind that you might need to lower the resolution when generating profiles for larger ranges.
”Node Type” offers you two options when it comes to the representation of data: Up/Down - divides a node in two sections for up volume/OI and down volume/OI, Total - one node for total volume/OI and Delta - net difference in up volume/OI and down volume/OI.
”Profile Position” lets you choose whether the profile is positioned on the left side of the range or on the right side of the range.
“Profile Direction” determines whether the profile nodes are facing right or left.
“Profile Type” enables you to visualize the nodes in a classic way (Type 1) or in a way where down volume/negative OI are positioned on the left side of the y axis and up volume/positive OI on the right side of the y axis.
“Node Size (%)” defines how much space in the range can be taken by the profile’s nodes. Eg. 50% will allow the largest node to extend to the middle of the range (and others scaled accordingly), 100% will allow the largest node to extend the max right point of the range (and others scaled accordingly).
”Value Area (%)” defines the VA zone, which represents the area where the most volume occured (usually 70% or 68%).
”Horizontal Heatmap” will display a heatmap-like overlay, that will help you identify the price levels where most volume/open interest action occurred.
”Vertical Heatmap” will display a heatmap-like overlay, that will help you identify the points in time where most volume/open interest action occurred.
A more detailed description of this indicator is coming in the next few days.
Important:
* If volume or OI profile does not get generated, try lowering the resolution.
* Once in a while, the script will disappear from your chart. Just remove and reapply.
* Open Interest data is only avaiable on Binance Perpetual Futures pairs
To learn more, read the tooltips in the indicator’s settings and stay tuned for upcoming additions (Range Market Structure, Liquidation Levels, Range Statistics,…)
Big Poppa Code Strat & Momentum Strategy IndicatorThis indicator is a combination of a few things in order to work with a unique trading style gleaned from Callme100k, jrgreatness, TrustMyLevels , FaithInTheStrat, Rob Smith and Saty Mahajan.
This Indicator is created to help you day trade using, ATR Fibonacci Levels, Price Action and Momentum.
It displays Fibonacci Levels Based on ATR to indicate when a security is 0.236, 0.382 +- the Days Open, +- the Days Open, 0.618 +- the Days Open and 1.0 +- Days Open.
To understand this script you need to understand
Average True Range (ATR)
1 Bar Inside Bar
2 Bar Outside Bar (Break either the top or bottom)
3 Bar Engulfing Bar
Strat Setups - 212, 322, 312
Fibonacci - 0.236, 0.382, 0.618, 1.0
Moving Averages
A Trend is considered bullish when (green)
Current Price is greater than the Fast EMA Value (8)
Fast EMA is greater than PIVOT EMA Value (21)
Pivot EMA is greater than SLOW EMA Value (34)
OR Hull is trending up and the Price is above the Volume Weighted Moving Average and price is above VWAP
A trend is considered Bearish when (red)
Current Price is less than the Fast EMA Value (8)
Fast EMA is less than PIVOT EMA Value (21)
Pivot EMA is less than SLOW EMA Value (34)
OR Hull is trending down and the Price is below the Volume Weighted Moving Average and price is below VWAP
If these conditions are not met then the Momentum is in Conflict (orange)
The Momentum band will match the color of the current trend
The table that is present can be turned off at any time lets you see
1) If Moving Averages are showing bullish, bearish or in conflict
2) If There us Time Frame Continuity, (if 5 min up, are all the other timeframes up also)
3) How much of the ATR have we moved on the day
4) Are we in Call or Put range for the day based on ATR Fib Levels
The Ideal situation for entering a call
1) Momentum is Green
2) FTFC on Green
3) A Strat Actionable Signal is present
4) You are in the call range, 0.236 - 0.618 ATR + the Price
5) The ATR still has room, I.e only 50% of the ATR has been run already
Ideal situation from entering a put
1) Momentum is red
2) FTFC on Red
3) A Strat Actionable Signal is present
4) You are in the put range, 0.236 - 0.618 ATR - the Price
5) The ATR still has room, I.e only 50% of the ATR has been run already
Exit the trade for these reasons you entered (for profit or loss)
1) ATR has no more room
2) FTFC is now in conflict
3) Momentum has shifted
Take Profit when
1) You reach a new ATR Level 0.618, 1.0 , -0.618, -1, etc
Passive Stop Loss
1) Open Price if you are aggressive
2) Next ATR Level Down or Up
Feel free to take profit and leave runners
This script does not give signals, you should do your own research, I am not a financial advisors, I am simply applying principles of seasoned veterans to code. You make all decisions about how you buy, sell and trade. The creator of this script makes no promises and takes no responsibility for your personal trading.
To research the methods described above look up
Rob Smith : The Strat
Saty Mahajan : ATR Levels
Fibonacci
Using the HULL Moving Average
Exponential Moving Averages
VWAP
VWMA
TurntLibraryLibrary "TurntLibrary"
Collection of functions created for simplification/easy referencing. Includes variations of moving averages, length value oscillators, and a few other simple functions based upon HH/LL values.
ma(source, length, type)
Apply a moving average to a float value
Parameters:
source : Value to be used
length : Number of bars to include in calculation
type : Moving average type to use ("SMA","EMA","RMA","WMA","VWAP","SWMA","LRC")
Returns: Smoothed value of initial float value
curve(src, len, lb1, lb2)
Exaggerates curves of a float value designed for use as an exit signal.
Parameters:
src : Initial value to curve
len : Number of bars to include in calculation
lb1 : (Default = 1) First lookback length
lb2 : (Default = 2) Second lookback length
Returns: Curved Average
fragma(src, len, space, str)
Average of a moving average and the previous value of the moving average
Parameters:
src : Initial float value to use
len : Number of bars to include in calculation
space : Lookback integer for second half of average
str : Moving average type to use ("SMA","EMA","RMA","WMA","VWAP","SWMA","LRC")
Returns: Fragmented Average
maxmin(x, y)
Difference of 2 float values, subtracting the lowest from the highest
Parameters:
x : Value 1
y : Value 2
Returns: The +Difference between 2 float values
oscLen(val, type)
Variable Length using a oscillator value and a corresponding slope shape ("Incline",Decline","Peak","Trough")
Parameters:
val : Oscillator Value to use
type : Slope of length curve ("Incline",Decline","Peak","Trough")
Returns: Variable Length Integer
hlAverage(val, smooth, max, min, type, include)
Average of HH,LL with variable lengths based on the slope shape ("Incline","Decline","Trough") value relative to highest and lowest
Parameters:
val : Source Value to use
smooth
max
min
type
include : Add "val" to the averaging process, instead of more weight to highest or lowest value
Returns: Variable Length Average of Highest Lowest "val"
pct(val)
Convert a positive float / price to a percentage of it's highest value on record
Parameters:
val : Value To convert to a percentage of it's highest value ever
Returns: Percentage
hlrange(x, len)
Difference between Highest High and Lowest Low of float value
Parameters:
x : Value to use in calculation
len : Number of bars to include in calculation
Returns: Difference
midpoint(x, len, smooth)
The average value of the float's Highest High and Lowest Low in a number of bars
Parameters:
x : Value to use in calculation
len
smooth : (Default=na) Optional smoothing type to use ("SMA","EMA","RMA","WMA","VWAP","SWMA","LRC")
Returns: Midpoint
Musashi_Katana=== Musashi-Katana ===
This tool was designed to fit my particular trading style and personal theories about the "Alchemy of the markets" and ''Harmonic Structure'.
Context
When following a Technical approach to to surf the markets, there are teachings that must be understood before reaching a confort-zone, this usually happen the possible worst way by constant experimentation, it hurts.
Here few technical hints:
- Align High timeframes with lower timeframes:
This simple concept relax a lot complexity of finding of a trend bias. Musashi-Katana allows you to use technical indicator corresponding to specific timeframes, like daily weekly or yearly. They wont change when you change the chart's timeframe, its very useful as you know where you're standing in the long term, Its quite relaxing.
- Use volume:
The constant usage of volume will allow you to sync with the market's breathing. This shows you the mass of money flowing into and out of the market, is key if you want to understand momentum. This tool can help here, as it have multi-period vwaps. You can use yearly, monthly for swing trading, and even weekly if you enjoy scalping.
Useful stuff:
- You have access to baselines, AMA and Kijun-sen with the possibility of adding ATR bands.
- AMAs come as two lines strategies for different approaches, fast medium or slow.
- You can experiment with normal and multi timeframe moving averages and other trend tools.
Final Note
If used correctly Musashi-Katana is a very powerful tool, which makes no sense as there is no correct usage. Don't add everything at the same time, experiment, combine stuff, every market is different.
Backtest every possible strategy before using it, see what works and doesn't. This gives you a lot of peace, specially while you're at the tip of the spear surfing the markets
--> I personally use this in combination with 'Musashi_Slasher (Mometum+Volatility)', as it gives me volatility and momentum in a very precise way.
Physics CandlesPhysics Candles embed volume and motion physics directly onto price candles or market internals according to the cyclic pattern of financial securities. The indicator works on both real-time “ticks” and historical data using statistical modeling to highlight when these values, like volume or momentum, is unusual or relatively high for some periodic window in time. Each candle is made out of one or more sub-candles that each contain their own information of motion, which converts to the color and transparency, or brightness, of that particular candle segment. The segments extend throughout the entire candle, both body and wicks, and Thick Wicks can be implemented to see the color coding better. This candle segmentation allows you to see if all the volume or energy is evenly distributed throughout the candle or highly contained in one small portion of it, and how intense these values are compared to similar time periods without going to lower time frames. Candle segmentation can also change a trader’s perspective on how valuable the information is. A “low” volume candle, for instance, could signify high value short-term stopping volume if the volume is all concentrated in one segment.
The Candles are flexible. The physics information embedded on the candles need not be from the same price security or market internal as the chart when using the Physics Source option, and multiple Candles can be overlayed together. You could embed stock price Candles with market volume, market price Candles with stock momentum, market structure with internal acceleration, stock price with stock force, etc. My particular use case is scalping the SPX futures market (ES), whose price action is also dictated by the volume action in the associated cash market, or SPY, as well as a host of other securities. Physics allows you to embed the ES volume on the SPY price action, or the SPY volume on the ES price action, or you can combine them both by overlaying two Candle streams and increasing the Number of Overlays option to two. That option decreases the transparency levels of your coloring scheme so that overlaying multiple Candles converges toward the same visual color intensity as if you had one. The Candle and Physics Sources allows for both Symbols and Spreads to visualize Candle physics from a single ticker or some mathematical transformation of tickers.
Due to certain TradingView programming restrictions, each Candle can only be made out of a maximum of 8 candle segments, or an “8-bit” resolution. Since limits are just an opportunity to go beyond, the user has the option to stack multiple Candle indicators together to further increase the candle resolution. If you don’t want to see the Candles for some particular period of the day, you can hide them, or use the hiding feature to have multiple Candles calibrated to show multiple parts of the trading day. Securities tend to have low volume after hours with sharp spikes at the open or close. Multiple Candles can be used for multiple parts of the trading day to accommodate these different cycles in volume.
The Candles do not need be associated with the nominal security listed on the TV chart. The Candle Source allows the user to look at AAPL Candles, for instance, while on a TSLA or SPY chart, each with their respective volume actions integrated into the candles, for instance, to allow the user to see multiple security price and volume correlation on a single chart.
The physics information currently embeddable on Candles are volume or time, velocity, momentum, acceleration, force, and kinetic energy. In order to apply equations of motion containing a mass variable to financial securities, some analogous value for mass must be assumed. Traders often regard volume or time as inextricable variables to a securities price that can indicate the direction and strength of a move. Since mass is the inextricable variable to calculating the momentum, force, or kinetic energy of motion, the user has the option to assume either time or volume is analogous to mass. Volume may be a better option for mass as it is not strictly dependent on the speed of a security, whereas time is.
Data transformations and outlier statistics are used to color code the intensity of the physics for each candle segment relative to past periodic behavior. A million shares during pre-market or a million shares during noontime may be more intense signals than a typical million shares traded at the open, and should have more intense color signals. To account for a specific cyclic behavior in the market, the user can specify the Window and Cycle Time Frames. The Window Time Frame splits up a Cycle into windows, samples and aggregates the statistics for each window, then compares the current physics values against past values in the same window. Intraday traders may benefit from using a Daily Cycle with a 30-minute Window Time Frame and 1-minute Sample Time Frame. These settings sample and compare the physics of 1-minute candles within the current 30-minute window to the same 30-minute window statistics for all past trading days, up until the data limit imposed by TradingView, or until the Data Collection Start Date specified in the settings. Longer-term traders may benefit from using a Monthly Cycle with a Weekly Time Frame, or a Yearly Cycle with a Quarterly Time Frame.
Multiple statistics and data transformation methods are available to convey relative intensity in different ways for different trading signals. Physics Candles allows for both Normal and Log-Normal assumptions in the physics distribution. The data can then be transformed by Linear, Logarithmic, Z-Score, or Power-Law scoring, where scoring simply assigns an intensity to the relative physics value of each candle segment based on some mathematical transformation. Z-scoring often renders adequate detection by scoring the segment value, such as volume or momentum, according to the mean and standard deviation of the data set in each window of the cycle. Logarithmic or power-law transformation with a gamma below 1 decreases the disparity between intensities so more less-important signals will show up, whereas the power-law transformation with gamma values above 1 increases the disparity between intensities, so less more-important signals will show up. These scores are then converted to color and transparency between the Min Score and the Max Score Cutoffs. The Auto-Normalization feature can automatically pick these cutoffs specific to each window based on the mean and standard deviation of the data set, or the user can manually set them. Physics was developed with novices in mind so that most users could calibrate their own settings by plotting the candle segment distributions directly on the chart and fiddling with the settings to see how different cutoffs capture different portions of the distribution and affect the relative color intensities differently. Security distributions are often skewed with fat-tails, known as kurtosis, where high-volume segments for example, have a higher-probabilities than expected for a normal distribution. These distribution are really log-normal, so that taking the logarithm leads to a standard bell-shaped distribution. Taking the Z-score of the Log-Normal distribution could make the most statistical sense, but color sensitivity is a discretionary preference.
Background Philosophy
This indicator was developed to study and trade the physics of motion in financial securities from a visually intuitive perspective. Newton’s laws of motion are loosely applied to financial motion:
“A body remains at rest, or in motion at a constant speed in a straight line, unless acted upon by a force”.
Financial securities remain at rest, or in motion at constant speed up or down, unless acted upon by the force of traders exchanging securities.
“When a body is acted upon by a force, the time rate of change of its momentum equals the force”.
Momentum is the product of mass and velocity, and force is the product of mass and acceleration. Traders render force on the security through the mass of their trading activity and the acceleration of price movement.
“If two bodies exert forces on each other, these forces have the same magnitude but opposite directions.”
Force arises from the interaction of traders, buyers and sellers. One body of motion, traders’ capitalization, exerts an equal and opposite force on another body of motion, the financial security. A securities movement arises at the expense of a buyer or seller’s capitalization.
Volume
The premise of this indicator assumes that volume, v, is an analogous means of measuring physical mass, m. This premise allows the application of the equations of motion to the movement of financial securities. We know from E=mc^2 that mass has energy. Energy can be used to create motion as kinetic energy. Taking a simple hypothetical example, the interaction of one short seller looking to cover lower and one buyer looking to sell higher exchange shares in a security at an agreed upon price to create volume or mass, and therefore, potential energy. Eventually the short seller will actively cover and buy the security from the previous buyer, moving the security higher, or the buyer will actively sell to the short seller, moving the security lower. The potential energy inherent in the initial consolidation or trading activity between buy and seller is now converted to kinetic energy on the subsequent trading activity that moves the securities price. The more potential energy that is created in the consolidation, the more kinetic energy there is to move price. This is why point and figure traders are said to give price targets based on the level of volatility or size of a consolidation range, or why Gann traders square price and time, as time is roughly proportional to mass and trading activity. The build-up of potential energy between short sellers and buyers in GME or TSLA led to their explosive moves beyond their standard fundamental valuations.
Position
Position, p, is simply the price or value of a financial security or market internal.
Time
Time, t, is another means of measuring mass to discover price behavior beyond the time snapshots that simple candle charts provide. We know from E=mc^2 that time is related to rest mass and energy given the speed of light, c, where time ≈ distance * sqrt(mass/E). This relation can also be derived from F=ma. The more mass there is, the longer it takes to compute the physics of a system. The more energy there is, the shorter it takes to compute the physics of a system. Similarly, more time is required to build a “resting” low-volatility trading consolidation with more mass. More energy added to that trading consolidation by competing buyers and sellers decreases the time it takes to build that same mass. Time is also related to price through velocity.
Velocity = (p(t1) – p(t0)) / p(t0)
Velocity, v, is the relative percent change of a securities price, p, over a period of time, t0 to t1. The period of time is between subsequent candles, and since time is constant between candles within the same timeframe, it is not used to calculate velocity or acceleration. Price moves faster with higher velocity, and slower with slower velocity, over the same fixed period of time. The product of velocity and mass gives momentum.
Momentum = mv
This indicator uses physics definition of momentum, not finance’s. In finance, momentum is defined as the amount of change in a securities price, either relative or absolute. This is definition is unfortunate, pun intended, since a one dollar move in a security from a thousand shares traded between a few traders has the exact same “momentum” as a one dollar move from millions of shares traded between hundreds of traders with everything else equal. If momentum is related to the energy of the move, momentum should consider both the level of activity in a price move, and the amount of that price move. If we equate mass to volume to account for the level of trading activity and use physics definition of momentum as the product of mass and velocity, this revised definition now gives a thousand-times more momentum to a one-dollar price move that has a thousand-times more volume behind it. If you want to use finance’s volume-less definition of momentum, use velocity in this indicator.
Acceleration = v(t1) – v(t0)
Acceleration, a, is the difference between velocities over some period of time, t0 to t1. Positive acceleration is necessary to increase a securities speed in the positive direction, while negative acceleration is necessary to decrease it. Acceleration is related to force by mass.
Force = ma
Force is required to change the speed of a securities valuation. Price movements with considerable force have considerably more impact on future direction. A change in direction requires force.
Kinetic Energy = 0.5mv^2
Kinetic energy is the energy that a financial security gains from the change in its velocity by force. The built-up of potential energy in trading consolidations can be converted to kinetic energy on a breakout from the consolidation.
Cycle Theory and Relativity
Just as the physics of motion is relative to a point of reference, so too should the physics of financial securities be relative to a point of reference. An object moving at a 100 mph towards another object moving in the same direction at 100 mph will not appear to be moving relative to each other, nor will they collide, but from an outsider observer, the objects are going 100 mph and will collide with significant impact if they run into a stationary object relative to the observer. Similarly, trading with a hundred thousand shares at the open when the average volume is a couple million may have a much smaller impact on the price compared to trading a hundred thousand shares pre-market when the average volume is ten thousand shares. The point of reference used in this indicator is the average statistics collected for a given Window Time Frame for every Cycle Time Frame. The physics values are normalized relative to these statistics.
Examples
The main chart of this publication shows the Force Candles for the SPY. An intense force candle is observed pre-market that implicates the directional overtone of the day. The assumption that direction should follow force arises from physical observation. If a large object is accelerating intensely in a particular direction, it may be fair to assume that the object continues its direction for the time being unless acted upon by another force.
The second example shows a similar Force Candle for the SPY that counters the assumption made in the first example and emphasizes the importance of both motion and context. While it’s fair to assume that a heavy highly accelerating object should continue its course, if that object runs into an obstacle, say a brick wall, it’s course may deviate. This example shows SPY running into the 50% retracement wall from the low of Mar 2020, a significant support level noted in literature. The example also conveys Gann’s idea of “lost motion”, where the SPY penetrated the 50% price but did not break through it. A brick wall is not one atom thick and price support is not one tick thick. An object can penetrate only one layer of a wall and not go through it.
The third example shows how Volume Candles can be used to identify scalping opportunities on the SPY and conveys why price behavior is as important as motion and context. It doesn’t take a brick wall to impede direction if you know that the person driving the car tends to forget to feed the cats before they leave. In the chart below, the SPY breaks down to a confluence of the 5-day SMA, 20-day SMA, and an important daily trendline (not shown) after the bullish bounce from the 50% retracement days earlier. High volume candles on the SMA signify stopping volume that reverse price direction. The character of the day changes. Bulls become more aggressive than bears with higher volume on upswings and resistance, whiles bears take on a defensive position with lower volume on downswings and support. High volume stopping candles are seen after rallies, and can tell you when to take profit, get out of a position, or go short. The character change can indicate that its relatively safe to re-enter bullish positions on many major supports, especially given the overarching bullish theme from the large reaction off the 50% retracement level.
The last example emphasizes the importance of relativity. The Volume Candles in the chart below are brightest pre-market even though the open has much higher volume since the pre-market activity is much higher compared to past pre-markets than the open is compared to past opens. Pre-market behavior is a good indicator for the character of the day. These bullish Volume Candles are some of the brightest seen since the bounce off the 50% retracement and indicates that bulls are making a relatively greater attempt to bring the SPY higher at the start of the day.
Infrequently Asked Questions
Where do I start?
The default settings are what I use to scalp the SPY throughout most of the extended trading day, on a one-minute chart using SPY volume. I also overlay another Candle set containing ES future volume on the SPY price structure by setting the Physics Source to ES1! and the Number of Overlays setting to 2 for each Candle stream in order to account for pre- and post-market trading activity better. Since the closing volume is exponential-like up until the end of the regular trading day, adding additional Candle streams with a tighter Window Time Frame (e.g., 2-5 minute) in the last 15 minutes of trading can be beneficial. The Hide feature can allow you to set certain intraday timeframes to hide one Candle set in order to show another Candle set during that time.
How crazy can you get with this indicator?
I hope you can answer this question better. One interesting use case is embedding the velocity of market volume onto an internal market structure. The PCTABOVEVWAP.US is a market statistic that indicates the percent of securities above their VWAP among US stocks and is helpful for determining short term trends in the US market. When securities are rising above their VWAP, the average long is up on the day and a rising PCTABOVEVWAP.US can be viewed as more bullish. When securities are falling below their VWAP, the average short is up on the day and a falling PCTABOVEVWAP.US can be viewed as more bearish. (UPVOL.US - DNVOL.US) / TVOL.US is a “spread” symbol, in TV parlance, that indicates the decimal percent difference between advancing volume and declining volume in the US market, showing the relative flow of volume between stocks that are up on the day, and stocks that are down on the day. Setting PCTABOVEVWAP.US in the Candle Source, (UPVOL.US - DNVOL.US) / TVOL.US in the Physics Source, and selecting the Physics to Velocity will embed the relative velocity of the spread symbol onto the PCTABOVEVWAP.US candles. This can be helpful in seeing short term trends in the US market that have an increasing amount of volume behind them compared to other trends. The chart below shows Volume Candles (top) and these Spread Candles (bottom). The first top at 9:30 and second top at 10:30, the high of the day, break down when the spread candles light up, showing a high velocity volume transfer from up stocks to down stocks.
How do I plot the indicator distribution and why should I even care?
The distribution is visually helpful in seeing how different normalization settings effect the distribution of candle segments. It is also helpful in seeing what physics intensities you want to ignore or show by segmenting part of the distribution within the Min and Max Cutoff values. The intensity of color is proportional to the physics value between the Min and Max Cutoff values, which correspond to the Min and Max Colors in your color scheme. Any physics value outside these Min and Max Cutoffs will be the same as the Min and Max Colors.
Select the Print Windows feature to show the window numbers according to the Cycle Time Frame and Window Time Frame settings. The window numbers are labeled at the start of each window and are candle width in size, so you may need to zoom into to see them. Selecting the Plot Window feature and input the window number of interest to shows the distribution of physics values for that particular window along with some statistics.
A log-normal volume distribution of segmented z-scores is shown below for 30-minute opening of the SPY. The Min and Max Cutoff at the top of the graph contain the part of the distribution whose intensities will be linearly color-coded between the Min and Max Colors of the color scheme. The part of the distribution below the Min Cutoff will be treated as lowest quality signals and set to the Min Color, while the few segments above the Max Cutoff will be treated as the highest quality signals and set to the Max Color.
What do I do if I don’t see anything?
Troubleshooting issues with this indicator can involve checking for error messages shown near the indicator name on the chart or using the Data Validation section to evaluate the statistics and normalization cutoffs. For example, if the Plot Window number is set to a window number that doesn’t exist, an error message will tell you and you won’t see any candles. You can use the Print Windows option to show windows that do exist for you current settings. The auto-normalization cutoff values may be inappropriate for your particular use case and literally cut the candles out of the chart. Try changing the chart time frame to see if they are appropriate for your cycle, sample and window time frames. If you get a “Timeframe passed to the request.security_lower_tf() function must be lower than the timeframe of the main chart” error, this means that the chart timeframe should be increased above the sample time frame. If you get a “Symbol resolve error”, ensure that you have correct symbol or spread in the Candle or Physics Source.
How do I see a relative physics values without cycles?
Set the Window Time Frame to be equal to the Cycle Time Frame. This will aggregate all the statistics into one bucket and show the physics values, such as volume, relative to all the past volumes that TV will allow.
How do I see candles without segmentation?
Segmentation can be very helpful in one context or annoying in another. Segmentation can be removed by setting the candle resolution value to 1.
Notes
I have yet to find a trading platform that consistently provides accurate real-time volume and pricing information, lacking adequate end-user data validation or quality control. I can provide plenty of examples of real-time volume counts or prices provided by TradingView and other platforms that were significantly off from what they should have been when comparing against the exchanges own data, and later retroactively corrected or not corrected at all. Since no indicator can work accurately with inaccurate data, please use at your own discretion.
The first version is a beta version. Debugging and validating code in Pine script is difficult without proper unit testing. Please report any bugs with enough information to reproduce them and indicate why they are important. I also encourage you to export the data from TradingView and verify the calculations for your particular use case.
The indicator works on real-time updates that occur at a higher frequency than the candle time frame, which TV incorrectly refers to as ticks. They use this terminology inaccurately as updates are really aggregated tick data that can take place at different prices and may not accurately reflect the real tick price action. Consequently, this inaccuracy also impacts the real-time segmentation accuracy to some degree. TV does not provide a means of retaining “tick” information, so the higher granularity of information seen real-time will be lost on a disconnect.
TV does not provide time and sales information. The volume and price information collected using the Sample Time Frame is intraday, which provides only part of the picture. Intraday volume is generally 50 to 80% of the end of day volume. Consequently, the daily+ OHLC prices are intraday, and may differ significantly from exchanged settled OHLC prices.
The Cycle and Window Time Frames refer to calendar days and time, not trading days or time. For example, the first window week of a monthly cycle is the first seven days of the month, not the first Monday through Friday of trading for the month.
Chart Time Frames that are higher than the Window Time Frames average the normalized physics for price action that occurred within a given Candle segment. It does not average price action that did not occur.
One of the main performance bottleneck in TradingView’s Pine Script is client-side drawing and plotting. The performance of this indicator can be increased by lowering the resolution (the number of sub-candles this indicator plots), getting a faster computer, or increasing the performance of your computer like plugging your laptop in and eliminating unnecessary processes.
The statistical integrity of this indicator relies on the number of samples collected per sample window in a given cycle. Higher sample counts can be obtained by increasing the chart time frame or upgrading the TradingView plan for a higher bar count. While increasing the chart time frame doesn’t increase the visual number of bars plotted on the chart, it does increase the number of bars that can be pulled at a lower time frame, up to 100,000.
Due to a limitation in Pine Scripts request_lower_tf() function, using a spread symbol will only work for regular trading hours, not extended trading hours.
Ideally, velocity or momentum should be calculated between candle closes. To eliminate the need to deal with price gaps that would lead to an incorrect statistical distributions, momentum is calculated between candle open and closes as a percent change of the price or value, which should not be an issue for most liquid securities.
Moving Average Compendium RefurbishedThis is my effort to bring together in a single script the widest range of moving averages possible.
I aggregated the calculation of averages within a library.
For more information about the library follow the link:
Basically this indicator is the visual result of this library.
You can choose the moving average and the script updates the chart as per the type.
The unique parameters of certain moving averages remain at their default values.
To have a rainbow of moving averages I also made an indicator:
Available moving averages:
AARMA = 'Adaptive Autonomous Recursive Moving Average'
ADEMA = '* Alpha-Decreasing Exponential Moving Average'
AHMA = 'Ahrens Moving Average'
ALMA = 'Arnaud Legoux Moving Average'
ALSMA = 'Adaptive Least Squares'
AUTOL = 'Auto-Line'
CMA = 'Corrective Moving average'
CORMA = 'Correlation Moving Average Price'
COVWEMA = 'Coefficient of Variation Weighted Exponential Moving Average'
COVWMA = 'Coefficient of Variation Weighted Moving Average'
DEMA = 'Double Exponential Moving Average'
DONCHIAN = 'Donchian Middle Channel'
EDMA = 'Exponentially Deviating Moving Average'
EDSMA = 'Ehlers Dynamic Smoothed Moving Average'
EFRAMA = '* Ehlrs Modified Fractal Adaptive Moving Average'
EHMA = 'Exponential Hull Moving Average'
EMA = 'Exponential Moving Average'
EPMA = 'End Point Moving Average'
ETMA = 'Exponential Triangular Moving Average'
EVWMA = 'Elastic Volume Weighted Moving Average'
FAMA = 'Following Adaptive Moving Average'
FIBOWMA = 'Fibonacci Weighted Moving Average'
FISHLSMA = 'Fisher Least Squares Moving Average'
FRAMA = 'Fractal Adaptive Moving Average'
GMA = 'Geometric Moving Average'
HKAMA = 'Hilbert based Kaufman\'s Adaptive Moving Average'
HMA = 'Hull Moving Average'
JURIK = 'Jurik Moving Average'
KAMA = 'Kaufman\'s Adaptive Moving Average'
LC_LSMA = '1LC-LSMA (1 line code lsma with 3 functions)'
LEOMA = 'Leo Moving Average'
LINWMA = 'Linear Weighted Moving Average'
LSMA = 'Least Squares Moving Average'
MAMA = 'MESA Adaptive Moving Average'
MCMA = 'McNicholl Moving Average'
MEDIAN = 'Median'
REGMA = 'Regularized Exponential Moving Average'
REMA = 'Range EMA'
REPMA = 'Repulsion Moving Average'
RMA = 'Relative Moving Average'
RSIMA = 'RSI Moving average'
RVWAP = '* Rolling VWAP'
SMA = 'Simple Moving Average'
SMMA = 'Smoothed Moving Average'
SRWMA = 'Square Root Weighted Moving Average'
SW_MA = 'Sine-Weighted Moving Average'
SWMA = '* Symmetrically Weighted Moving Average'
TEMA = 'Triple Exponential Moving Average'
THMA = 'Triple Hull Moving Average'
TREMA = 'Triangular Exponential Moving Average'
TRSMA = 'Triangular Simple Moving Average'
TT3 = 'Tillson T3'
VAMA = 'Volatility Adjusted Moving Average'
VIDYA = 'Variable Index Dynamic Average'
VWAP = '* VWAP'
VWMA = 'Volume-weighted Moving Average'
WMA = 'Weighted Moving Average'
WWMA = 'Welles Wilder Moving Average'
XEMA = 'Optimized Exponential Moving Average'
ZEMA = 'Zero-Lag Exponential Moving Average'
ZSMA = 'Zero-Lag Simple Moving Average'
Moving_AveragesLibrary "Moving_Averages"
This library contains majority important moving average functions with int series support. Which means that they can be used with variable length input. For conventional use, please use tradingview built-in ta functions for moving averages as they are more precise. I'll use functions in this library for my other scripts with dynamic length inputs.
ema(src, len)
Exponential Moving Average (EMA)
Parameters:
src : Source
len : Period
Returns: Exponential Moving Average with Series Int Support (EMA)
alma(src, len, a_offset, a_sigma)
Arnaud Legoux Moving Average (ALMA)
Parameters:
src : Source
len : Period
a_offset : Arnaud Legoux offset
a_sigma : Arnaud Legoux sigma
Returns: Arnaud Legoux Moving Average (ALMA)
covwema(src, len)
Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
covwma(src, len)
Coefficient of Variation Weighted Moving Average (COVWMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Moving Average (COVWMA)
dema(src, len)
DEMA - Double Exponential Moving Average
Parameters:
src : Source
len : Period
Returns: DEMA - Double Exponential Moving Average
edsma(src, len, ssfLength, ssfPoles)
EDSMA - Ehlers Deviation Scaled Moving Average
Parameters:
src : Source
len : Period
ssfLength : EDSMA - Super Smoother Filter Length
ssfPoles : EDSMA - Super Smoother Filter Poles
Returns: Ehlers Deviation Scaled Moving Average (EDSMA)
eframa(src, len, FC, SC)
Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
Parameters:
src : Source
len : Period
FC : Lower Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
SC : Upper Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
Returns: Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
ehma(src, len)
EHMA - Exponential Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Exponential Hull Moving Average (EHMA)
etma(src, len)
Exponential Triangular Moving Average (ETMA)
Parameters:
src : Source
len : Period
Returns: Exponential Triangular Moving Average (ETMA)
frama(src, len)
Fractal Adaptive Moving Average (FRAMA)
Parameters:
src : Source
len : Period
Returns: Fractal Adaptive Moving Average (FRAMA)
hma(src, len)
HMA - Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Hull Moving Average (HMA)
jma(src, len, jurik_phase, jurik_power)
Jurik Moving Average - JMA
Parameters:
src : Source
len : Period
jurik_phase : Jurik (JMA) Only - Phase
jurik_power : Jurik (JMA) Only - Power
Returns: Jurik Moving Average (JMA)
kama(src, len, k_fastLength, k_slowLength)
Kaufman's Adaptive Moving Average (KAMA)
Parameters:
src : Source
len : Period
k_fastLength : Number of periods for the fastest exponential moving average
k_slowLength : Number of periods for the slowest exponential moving average
Returns: Kaufman's Adaptive Moving Average (KAMA)
kijun(_high, _low, len, kidiv)
Kijun v2
Parameters:
_high : High value of bar
_low : Low value of bar
len : Period
kidiv : Kijun MOD Divider
Returns: Kijun v2
lsma(src, len, offset)
LSMA/LRC - Least Squares Moving Average / Linear Regression Curve
Parameters:
src : Source
len : Period
offset : Offset
Returns: Least Squares Moving Average (LSMA)/ Linear Regression Curve (LRC)
mf(src, len, beta, feedback, z)
MF - Modular Filter
Parameters:
src : Source
len : Period
beta : Modular Filter, General Filter Only - Beta
feedback : Modular Filter Only - Feedback
z : Modular Filter Only - Feedback Weighting
Returns: Modular Filter (MF)
rma(src, len)
RMA - RSI Moving average
Parameters:
src : Source
len : Period
Returns: RSI Moving average (RMA)
sma(src, len)
SMA - Simple Moving Average
Parameters:
src : Source
len : Period
Returns: Simple Moving Average (SMA)
smma(src, len)
Smoothed Moving Average (SMMA)
Parameters:
src : Source
len : Period
Returns: Smoothed Moving Average (SMMA)
stma(src, len)
Simple Triangular Moving Average (STMA)
Parameters:
src : Source
len : Period
Returns: Simple Triangular Moving Average (STMA)
tema(src, len)
TEMA - Triple Exponential Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Exponential Moving Average (TEMA)
thma(src, len)
THMA - Triple Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Hull Moving Average (THMA)
vama(src, len, volatility_lookback)
VAMA - Volatility Adjusted Moving Average
Parameters:
src : Source
len : Period
volatility_lookback : Volatility lookback length
Returns: Volatility Adjusted Moving Average (VAMA)
vidya(src, len)
Variable Index Dynamic Average (VIDYA)
Parameters:
src : Source
len : Period
Returns: Variable Index Dynamic Average (VIDYA)
vwma(src, len)
Volume-Weighted Moving Average (VWMA)
Parameters:
src : Source
len : Period
Returns: Volume-Weighted Moving Average (VWMA)
wma(src, len)
WMA - Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Weighted Moving Average (WMA)
zema(src, len)
Zero-Lag Exponential Moving Average (ZEMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Exponential Moving Average (ZEMA)
zsma(src, len)
Zero-Lag Simple Moving Average (ZSMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Simple Moving Average (ZSMA)
evwma(src, len)
EVWMA - Elastic Volume Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Elastic Volume Weighted Moving Average (EVWMA)
tt3(src, len, a1_t3)
Tillson T3
Parameters:
src : Source
len : Period
a1_t3 : Tillson T3 Volume Factor
Returns: Tillson T3
gma(src, len)
GMA - Geometric Moving Average
Parameters:
src : Source
len : Period
Returns: Geometric Moving Average (GMA)
wwma(src, len)
WWMA - Welles Wilder Moving Average
Parameters:
src : Source
len : Period
Returns: Welles Wilder Moving Average (WWMA)
ama(src, _high, _low, len, ama_f_length, ama_s_length)
AMA - Adjusted Moving Average
Parameters:
src : Source
_high : High value of bar
_low : Low value of bar
len : Period
ama_f_length : Fast EMA Length
ama_s_length : Slow EMA Length
Returns: Adjusted Moving Average (AMA)
cma(src, len)
Corrective Moving average (CMA)
Parameters:
src : Source
len : Period
Returns: Corrective Moving average (CMA)
gmma(src, len)
Geometric Mean Moving Average (GMMA)
Parameters:
src : Source
len : Period
Returns: Geometric Mean Moving Average (GMMA)
ealf(src, len, LAPercLen_, FPerc_)
Ehler's Adaptive Laguerre filter (EALF)
Parameters:
src : Source
len : Period
LAPercLen_ : Median Length
FPerc_ : Median Percentage
Returns: Ehler's Adaptive Laguerre filter (EALF)
elf(src, len, LAPercLen_, FPerc_)
ELF - Ehler's Laguerre filter
Parameters:
src : Source
len : Period
LAPercLen_ : Median Length
FPerc_ : Median Percentage
Returns: Ehler's Laguerre Filter (ELF)
edma(src, len)
Exponentially Deviating Moving Average (MZ EDMA)
Parameters:
src : Source
len : Period
Returns: Exponentially Deviating Moving Average (MZ EDMA)
pnr(src, len, rank_inter_Perc_)
PNR - percentile nearest rank
Parameters:
src : Source
len : Period
rank_inter_Perc_ : Rank and Interpolation Percentage
Returns: Percentile Nearest Rank (PNR)
pli(src, len, rank_inter_Perc_)
PLI - Percentile Linear Interpolation
Parameters:
src : Source
len : Period
rank_inter_Perc_ : Rank and Interpolation Percentage
Returns: Percentile Linear Interpolation (PLI)
rema(src, len)
Range EMA (REMA)
Parameters:
src : Source
len : Period
Returns: Range EMA (REMA)
sw_ma(src, len)
Sine-Weighted Moving Average (SW-MA)
Parameters:
src : Source
len : Period
Returns: Sine-Weighted Moving Average (SW-MA)
vwap(src, len)
Volume Weighted Average Price (VWAP)
Parameters:
src : Source
len : Period
Returns: Volume Weighted Average Price (VWAP)
mama(src, len)
MAMA - MESA Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: MESA Adaptive Moving Average (MAMA)
fama(src, len)
FAMA - Following Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Following Adaptive Moving Average (FAMA)
hkama(src, len)
HKAMA - Hilbert based Kaufman's Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Hilbert based Kaufman's Adaptive Moving Average (HKAMA)
MA ClustersBackground :
This study allows to define ranges for contraction and expansion of a defined set of MA to analyse the the momentum at those specific situations.
In general all functions used are very basic but allows the user to set alerts when a cluster of MA enters a defined range within or outside the MAX and MIN of a selected MA cluster. The predefined length of the EMAs were put together by HurstHorns within a trading learning discord group and are designed for 1M timeframe to read the momentum for scalping entries - Thanks again for sharing.
Functions :
currently the following MA are available:
- ema
- sma
- smma
- wma
- vwma
- vma
the variable moving average is based on the calculation from lazybear.
- RSI Stoch Filter
- Wavetrend OB/OS filter
Currently only alerts for contraction are enabled to not overload the study but in case expansion would be from interest this can be added quickly.
Outlook:
Additional filters were added to see if they can add value in. the decision making or by simply filtering out noise. This is still quite experimental. Please share any useful observation I should add as additional filter option to find good setups. in relation to contractions or expansions.
Next version will get Bollinger bands for 1 selectable MA from the list for additional study options.
In case you are interested in more options such as more MA types or vwap.. just let me know. for VMA I need to do more research to add useful function for laddering or things like that.
In general The script itself can be easily extended by additional functions. As this is one of my first scripts the code itself might not be optimal or there are more elegant ways to come to the same goal. However please use for study purposes only and report bugs or enhancement requests.
good luck and happy trading!
NoBrain BreakoutUse 3min. Time frame.
Buy Stock Selection:-
When Close Price Cross Monthly Standard Pivot R1 & Monthly Standard Pivot R1 is Greater than Previous Day High( PDH ) Or Close.
Price must be Above 44 MA ,48 EMA & Vwap
***Buy When 3min Candle closed Above Camarilla R4 or Monthly Standard Pivot R1 whichever is High.
Sell Stock Selection:-
When Close Price Cross Monthly Standard Pivot S1 & Monthly Standard Pivot S1 is Less than Previous Day Low( PDL ) Or Close.
Price must be Below 44 MA ,48 EMA & Vwap
***Sell When 3min Candle closed Below Camarilla S4 or Monthly Standard Pivot S1 whichever is Low.
Trading time for
1st wave 9.30am to 10.45am.
2nd wave 12.45pm to 2.45pm.
(Based on NSE/ BSE India)
Indicators:-
1) Pivot Points Standard - Time Frame monthly.only select R1
2) Pivot Points Camarilla- Only select R4.
3) SMA 44
4) EMA 48
5) Vwap
6) For Trailing Stop Loss use SuperTrend- Length-13 Factor-2.7 or Length-15 Factor-3 (3min Timeframe)
Multi-Timeframe (MTF) Dashboard by RiTzMulti-Timeframe Dashboard
Shows values of different Indiactors on Multiple-Timeframes for the selected script/symbol
VWAP : if LTP is trading above VWAP then Bullish else if LTP is trading below VWAP then Bearish.
ST(21,1) : if LTP is trading above Supertrend (21,1) then Bullish , else if LTP is trading below Supertrend (21,1) then Bearish.
ST(14,2) : if LTP is trading above Supertrend (14,2) then Bullish , else if LTP is trading below Supertrend (14,2) then Bearish.
ST(10,3) : if LTP is trading above Supertrend (10,3) then Bullish , else if LTP is trading below Supertrend (10,3) then Bearish.
RSI(14) : Shows value of RSI (14) for the current timeframe.
ADX : if ADX is > 75 and DI+ > DI- then "Bullish ++".
if ADX is < 75 but >50 and DI+ > DI- then "Bullish +".
if ADX is < 50 but > 25 and DI+ > DI- then "Bullish".
if ADX is above 75 and DI- > DI+ then "Bearish ++".
if ADX is < 75 but > 50 and DI- > DI+ then "Bearish+".
if ADX is < 50 but > 25 and DI- > DI+ then "Bearish".
if ADX is < 25 then "Neutral".
MACD : if MACD line is above Signal Line then "Bullish", else if MACD line is below Signal Line then "Bearish".
PH-PL : "< PH > PL" means LTP is trading between Previous Timeframes High(PH) & Previous Timeframes Low(PL) which indicates Rangebound-ness.
"> PH" means LTP is trading above Previous Timeframes High(PH) which indicates Bullish-ness.
"< PL" means LTP is trading below Previous Timeframes Low(PL) which indicates Bearish-ness.
Alligator : If Lips > Teeth > Jaw then Bullish.
If Lips < Teeth < Jaw then Bearish.
If Lips > Teeth and Teeth < Jaw then Neutral/Sleeping.
If Lips < Teeth and Teeth > Jaw then Neutral/Sleeping.
Settings :
Style settings :-
Dashboard Location: Location of the dashboard on the chart
Dashboard Size: Size of the dashboard on the chart
Bullish Cell Color: Select the color of cell whose value is showing Bullish-ness.
Bearish Cell Color: Select the color of cell whose value is showing Bearish-ness.
Neutral Cell Color: Select the color of cell whose value is showing Rangebound-ness.
Cell Transparency: Select Transparency of cell.
Column Settings :-
You can select which Indicators values should be displayed/hidden.
Timeframe Settings :-
You can select which timeframes values should be displayed/hidden.
Note :- I'm not a pro Developer/Coder , so if there are any mistakes or any suggestions for improvements in the code then do let me know!
Note :- Use in Live market , might show wrong values for timeframes other than current timeframe in closed market!!
Nifty / Banknifty Dashboard by RiTzNifty / Banknifty Dashboard :
Shows Values of different Indicators on current Timeframe for the selected Index & it's main constituents according to weightage in index.
customized for Nifty & Banknifty (You can customize it according to your needs for the markets/indexes you trade in)
Interpretation :-
VWAP : if LTP is trading above VWAP then Bullish else if LTP is trading below VWAP then Bearish.
ST(21,1) : if LTP is trading above Supertrend (21,1) then Bullish , else if LTP is trading below Supertrend (21,1) then Bearish.
ST(14,2) : if LTP is trading above Supertrend (14,2) then Bullish , else if LTP is trading below Supertrend (14,2) then Bearish.
ST(10,3) : if LTP is trading above Supertrend (10,3) then Bullish , else if LTP is trading below Supertrend (10,3) then Bearish.
RSI(14) : Shows value of RSI (14) for the current timeframe.
ADX : if ADX is > 75 and DI+ > DI- then "Bullish ++".
if ADX is < 75 but >50 and DI+ > DI- then "Bullish +".
if ADX is < 50 but > 25 and DI+ > DI- then "Bullish".
if ADX is above 75 and DI- > DI+ then "Bearish ++".
if ADX is < 75 but > 50 and DI- > DI+ then "Bearish+".
if ADX is < 50 but > 25 and DI- > DI+ then "Bearish".
if ADX is < 25 then "Neutral".
MACD : if MACD line is above Signal Line then "Bullish", else if MACD line is below Signal Line then "Bearish".
PDH-PDL : "< PDH > PDL" means LTP is trading between Previous Days High(PDH) & Previous Days Low(PDL) which indicates Rangebound-ness.
"> PDH" means LTP is trading above Previous Days High(PDH) which indicates Bullish-ness.
"< PDL" means LTP is trading below Previous Days Low(PDL) which indicates Bearish-ness.
Alligator : If Lips > Teeth > Jaw then Bullish.
If Lips < Teeth < Jaw then Bearish.
If Lips > Teeth and Teeth < Jaw then Neutral/Sleeping.
If Lips < Teeth and Teeth > Jaw then Neutral/Sleeping.
Settings :
Style settings :-
Dashboard Location: Location of the dashboard on the chart
Dashboard Size: Size of the dashboard on the chart
Bullish Cell Color: Select the color of cell whose value is showing Bullish-ness.
Bearish Cell Color: Select the color of cell whose value is showing Bearish-ness.
Neutral Cell Color: Select the color of cell whose value is showing Rangebound-ness.
Cell Transparency: Select Transparency of cell.
Columns Settings :-
You can select which Indicators values should be displayed/hidden.
Rows Settings :-
You can select which Stocks/Symbols values should be displayed/hidden.
Symbol Settings :-
Here you can select the Index & Stocks/Symbols
Dashboard for Index : select Nifty/Banknifty
if you select Nifty then Nifty spot, Nifty current Futures and the stocks with most weightage in Nifty index will be displayed on the Dashboard/Table.
if you select Banknifty then Banknifty spot, Banknifty current Futures and the stocks with most weightage in Banknifty index will be displayed on the Dashboard/Table.
You can Customise it according to your needs, you can choose any Symbols you want to use.
Note :- This is inspired from "RankDelta" by AsitPati and "Nifty and Bank Nifty Dashboard v2" by cvsk123 (Both these scripts are closed source!)
I'm not a pro Developer/Coder , so if there are any mistakes or any suggestions for improvements in the code then do let me know!
