PROFIT INDICATORFirst let me tell you which indicators have been used in this script so that you have the confidence while taking the trade:
(a) Bollinger Band with 20 SMA Inside it - Currently it is off, you can turn it on from settings.
(b) HMA 33, I have added the option of using two HMA's simultaneously. You can use HMA, EMA, SMA as per your settings and it would be color trending.
(c) VWAP- you can turn it on from settings
(d) CPR- you can turn it on from settings
(e) EMA's 20, 50, 200. Currently off, you can turn it on from settings.
(d) SMA's 50 and 200. Currently off, yu can turn it on from settings, if you want to use 20 SMA you can use bollinger band basis that is 20 period SMA.
(f) Trend bar at bottom on the basis of 50 EMA.
(g) Half Trend
(h) Trend strength Detector
(d) EMA 50 high and low to show the pac channel. I am not using this however as per request I have added this. Currently, it is trun on and you can turn it off from settings.
(f) Auto Fib levels
Please use a stick note for few days and mention imp notes before taking trade to check if all the conditions are matching to take the trade.
Buy Condition:-
1. Bolling band should be widely open.
2. Check the support and resistance from CPR. Candle should close above support in green.
3. Check the trend bar at bottom, it should be green, if it is grey in colour dont enter in trade.
4. Candle should be closing above EMA 50 and its upto you if you need additional confirmation, you can use EMA 20, 50, 200 and SMA 50 and 200, this is optional.
5. You can use VWAP as support or resistance and you can turn it on from settings.
6. Trending HMA of 33 should be in green for buy.
7. Half trend Indicator should give buy signal.
8. Trend Strength Indicator for checking the strength of the trend, if the arrow is big upside, you can go for buy.
9. Exit from buy trade when it start showing very small arrow which means trend is about to change.
10.Exit buy trade at 61.8 Fib level
Sell Condition:-
1. Bolling band should be widely open.
2. Check the support and resistance from CPR. Candle should close below resistance in red.
3. Check the trend bar at bottom, it should be red, if it is grey in colour dont enter in trade.
4. Candle should be closing below EMA 50 and its upto you if you need additional confirmation, you can use EMA 20, 50, 200 and SMA 50 and 200, this is optional.
5. You can use VWAP as support or resistance and you can turn it on from settings.
6. Trending HMA of 33 should be in red for sell.
7. Half trend Indicator should give sell signal.
8. Trend Strength Indicator for checking the strength of the trend, if the arrow is big downside, you can go for sell.
9. Exit from sell trade when down arrows start showing very small in size which means trend is about to change.
10.Exit sell trade at 61.8 Fib level
Search in scripts for "vwap"
Pulu's 3 Moving Averages
Pulu's 3 Moving Averages
Release version 1, date 2021-09-28
This script allows you to customize three sets of moving averages, turn on/off, set color and parameters. It also tags the start date of the last set of moving average if there is. This, release version 1, supports eight moving average algorithms:
ALMA, Arnaud Legoux Moving Average
EMA, Exponential Moving Average
RMA, Adjusted exponential moving average (aka Wilder’s EMA)
SMA, Simple Moving Average
SWMA, Symmetrically-Weighted Moving Average
VWAP, Volume-Weighted Average Price
VWMA, Volume-Weighted Moving Average
WMA, Weighted Moving Average
The availability and function parameters
Func. Availability Parameters
ALMA
MA1, MA2, MA3
source
length
offset
sigma
EMA
RMA
SMA
VWMA
WMA
MA1, MA2, MA3
source
length
SWMA
VWAP
MA1
source
Parameters
Parameter Description
source the series of values to process. The default is to use the closing price to calculate the moving average.
length an integer value that defines the number of bars to calculate the moving average on. The SWMA and VWAP do not use this parameter.
ALMA offset a floating-point value that controls the tradeoff between smoothness (with a value closer to 1) and responsiveness (with a value closer to 0). This parameter is only used by ALMA.
ALMA sigma a floating-point value that specifies the ALMA’s smoothness. The larger this value, the smoother the moving average is. This parameter is only used by ALMA.
I'm not sure if it is needed, so I do not let the three Moving Averages of the script to have indivial algorithm setting. Because that will involve much complicated condition testing and use up more TradingView script lines limit. If you need to combine different algorithms in the three sets of moving averages, or have other ideas, leave a message to let me know; maybe I will try it in the next update.
我不確定是否需要，所以我沒有讓腳本的三組移動平均線有各別的算法設置。因為這將涉及更多複雜的條件測試，並使用更多 TradingView 腳本列數限制。如果您需要在三組均線中組合不同的算法，或者有其他想法，請留言告訴我；也許我會在下一次更新中嘗試。
Exponential moving averages Convergence to identify Strength of Exponential moving averages Convergence to identify Strength of the stock.
Description:
This script is developed to find Convergences for many indicators. It analyses Convergences of 20days, 50days, 100days, 150days and 200days exponential moving averages. When all the plotted lines are converged and Price of stock is above the Convergence the stock is bullish, similarly if the price of the stock is below the convergence stock is bearish.
This indicator gives you VWAP and EMA’s for convergence along with Bollinger Bands.
VWAP and Bollinger bands and EMA’s can be altered as you required.
In settings menu we can enable and disable VWAP, EMA’S & Bollinger bands and in style menu even we can choose required EMA
It helps for convergence.
TWAP TrendHere we are experimenting with using TWAP for trend analysis. It appears to work better than VWAP on lower timeframes.
TWAP is a tool used by algorithm based traders that allows them to distribute their orders throughout the day without disturbing price or having their positions known to rival traders in the market. It's similar to VWAP and serves the same function, except it lacks the volume aspect. This can be an issue when position entry/exit may be affected by slippage.
The main benefit of TWAP is deciding how to distribute orders throughout the chosen timeframe. However, just like the VWAP traders will normally use it as a moving average or target for price action to pull into.
There is an option to change the timeframe that TWAP is calculated from.
Originally by NeoButane:
Non Parametric Adaptive Moving AverageIntroduction
Not be confused with non-parametric statistics, i define a "non-parametric" indicator as an indicator who does not have any parameter input. Such indicators can be useful since they don't need to go through parameter optimization. I present here a non parametric adaptive moving average based on exponential averaging using a modified ratio of open-close to high-low range indicator as smoothing variable.
The Indicator
The ratio of open-close to high-low range is a measurement involving calculating the ratio between the absolute close/open price difference and the range (high - low) , now the relationship between high/low and open/close price has been studied in econometrics for some time but there are no reason that the ohlc range ratio may be an indicator of volatility, however we can make the hypothesis that trending markets contain less indecision than ranging market and that indecision is measured by the high/low movements, this is an idea that i've heard various time.
Since the range is always greater than the absolute close/open difference we have a scaled smoothing variable in a range of 0/1, this allow to perform exponential averaging. The ratio of open-close to high-low range is calculated using the vwap of the close/high/low/open price in order to increase the smoothing effect. The vwap tend to smooth more with low time frames than higher ones, since the indicator use vwap for the calculation of its smoothing variable, smoothing may differ depending on the time frame you are in.
1 minute tf
1 hour tf
Conclusion
Making non parametric indicators is quite efficient, but they wont necessarily outperform classical parametric indicators. I also presented a modified version of the ratio of open-close to high-low range who can provide a smoothing variable for exponential averaging. I hope the indicator can help you in any way.
Thanks for reading !
Johnny's Machine Learning Moving Average (MLMA) w/ Trend Alerts📖 Overview
Johnny's Machine Learning Moving Average (MLMA) w/ Trend Alerts is a powerful adaptive moving average indicator designed to capture market trends dynamically. Unlike traditional moving averages (e.g., SMA, EMA, WMA), this indicator incorporates volatility-based trend detection, Bollinger Bands, ADX, and RSI, offering a comprehensive view of market conditions.
The MLMA is "machine learning-inspired" because it adapts dynamically to market conditions using ATR-based windowing and integrates multiple trend strength indicators (ADX, RSI, and volatility bands) to provide an intelligent moving average calculation that learns from recent price action rather than being static.
🛠 How It Works
1️⃣ Adaptive Moving Average Selection
The MLMA automatically selects one of four different moving averages:
📊 EMA (Exponential Moving Average) – Reacts quickly to price changes.
🔵 HMA (Hull Moving Average) – Smooth and fast, reducing lag.
🟡 WMA (Weighted Moving Average) – Gives recent prices more importance.
🔴 VWAP (Volume Weighted Average Price) – Accounts for volume impact.
The user can select which moving average type to use, making the indicator customizable based on their strategy.
2️⃣ Dynamic Trend Detection
ATR-Based Adaptive Window 📏
The Average True Range (ATR) determines the window size dynamically.
When volatility is high, the moving average window expands, making the MLMA more stable.
When volatility is low, the window shrinks, making the MLMA more responsive.
Trend Strength Filters 📊
ADX (Average Directional Index) > 25 → Indicates a strong trend.
RSI (Relative Strength Index) > 70 or < 30 → Identifies overbought/oversold conditions.
Price Position Relative to Upper/Lower Bands → Determines bullish vs. bearish momentum.
3️⃣ Volatility Bands & Dynamic Support/Resistance
Bollinger Bands (BB) 📉
Uses standard deviation-based bands around the MLMA to detect overbought and oversold zones.
Upper Band = Resistance, Lower Band = Support.
Helps traders identify breakout potential.
Adaptive Trend Bands 🔵🔴
The MLMA has built-in trend envelopes.
When price breaks the upper band, bullish momentum is confirmed.
When price breaks the lower band, bearish momentum is confirmed.
4️⃣ Visual Enhancements
Dynamic Gradient Fills 🌈
The trend strength (ADX-based) determines the gradient intensity.
Stronger trends = More vivid colors.
Weaker trends = Lighter colors.
Trend Reversal Arrows 🔄
🔼 Green Up Arrow: Bullish reversal signal.
🔽 Red Down Arrow: Bearish reversal signal.
Trend Table Overlay 🖥
Displays ADX, RSI, and Trend State dynamically on the chart.
📢 Trading Signals & How to Use It
1️⃣ Bullish Signals 📈
✅ Conditions for a Long (Buy) Trade:
The MLMA crosses above the lower band.
The ADX is above 25 (confirming trend strength).
RSI is above 55, indicating positive momentum.
Green trend reversal arrow appears (confirmation of a bullish reversal).
🔹 How to Trade It:
Enter a long trade when the MLMA turns bullish.
Set stop-loss below the lower Bollinger Band.
Target previous resistance levels or use the upper band as take-profit.
2️⃣ Bearish Signals 📉
✅ Conditions for a Short (Sell) Trade:
The MLMA crosses below the upper band.
The ADX is above 25 (confirming trend strength).
RSI is below 45, indicating bearish pressure.
Red trend reversal arrow appears (confirmation of a bearish reversal).
🔹 How to Trade It:
Enter a short trade when the MLMA turns bearish.
Set stop-loss above the upper Bollinger Band.
Target the lower band as take-profit.
💡 What Makes This a Machine Learning Moving Average?
📍 1️⃣ Adaptive & Self-Tuning
Unlike static moving averages that rely on fixed parameters, this MLMA automatically adjusts its sensitivity to market conditions using:
ATR-based dynamic windowing 📏 (Expands/contracts based on volatility).
Adaptive smoothing using EMA, HMA, WMA, or VWAP 📊.
Multi-indicator confirmation (ADX, RSI, Volatility Bands) 🏆.
📍 2️⃣ Intelligent Trend Confirmation
The MLMA "learns" from recent price movements instead of blindly following a fixed-length average.
It incorporates ADX & RSI trend filtering to reduce noise & false signals.
📍 3️⃣ Dynamic Color-Coding for Trend Strength
Strong trends trigger more vivid colors, mimicking confidence levels in machine learning models.
Weaker trends appear faded, suggesting uncertainty.
🎯 Why Use the MLMA?
✅ Pros
✔ Combines multiple trend indicators (MA, ADX, RSI, BB).
✔ Automatically adjusts to market conditions.
✔ Filters out weak trends, making it more reliable.
✔ Visually intuitive (gradient colors & reversal arrows).
✔ Works across all timeframes and assets.
⚠️ Cons
❌ Not a standalone strategy → Best used with volume confirmation or candlestick analysis.
❌ Can lag slightly in fast-moving markets (due to smoothing).
Enhanced Retail vs Institutional ActivityThis script highlights market activity in real-time, making it easier to infer the type of market participants driving price and volume changes.
Here’s a list of what the script analyzes:
Volume:
Current volume of the candle.
Moving average of volume over a specified number of periods.
Volume spikes: Current volume compared to a threshold multiple of the moving average.
Price Movement:
Percentage change in price between the current and previous candle.
Identifies significant price changes based on a user-defined threshold.
Institutional Activity:
High volume spikes combined with significant price movements.
Retail Activity:
Periods without volume spikes or significant price changes.
VWAP (Volume-Weighted Average Price):
The average traded price over a specified lookback period, weighted by volume, used as a benchmark.
Market Context Visualization:
Background colors to differentiate institutional (red) and retail (green) activity.
Overlays for:
-Volume bars.
-Average volume line.
-VWAP line.
In summary:
Red = Institutional activity: High volume + significant price change.
Green = Retail activity: Low volume or insignificant price change.
---------------------------------------------------------------------------------------------------------------------
Analysis Explanation:
I’m forecasting that Bitcoin will retest its November 12th low (~$85,098.75) around January 20th, 2025, where the horizontal support line intersects with the downtrend line. This conclusion is based on the following:
Trend Analysis:
The chart shows a clear downtrend with price respecting the descending trendline.
The intersection of the horizontal support and the downtrend line on January 20th indicates a confluence point where price action may gravitate.
Volume and Activity Insights:
Using the Retail vs Institutional Activity indicator, the chart highlights periods dominated by institutional (red background) or retail (green background) activity.
Current price action is in a green zone, suggesting predominantly retail participation with lower volume and insignificant price movements.
Retail vs Institutional Dynamics:
Institutional activity (red zones) aligns with significant price movements and volume spikes, often marking key turning points or trends.
The recent green retail-dominated periods suggest a lack of strong momentum, which may lead to continued price decline until institutions re-enter around the confluence area.
Volume Observations:
Volume remains relatively low during the current retail phase, indicating weak buying pressure.
A potential surge in institutional activity (red zones) near the support level could trigger a rebound or breakdown.
I expect Bitcoin’s price to drop further and test the November 12th low near $85,098.75 on January 20th, 2025. This projection is supported by the convergence of the downtrend line and horizontal support, low retail-driven volume, and historical institutional activity patterns observed using the "Retail vs Institutional Activity" indicator.
OHOL_VWAP_STIts all about OH and OL concept for Nifty Future.
1.When OH candle formed and breaks the high we can enter the position, candle should be below supertrend , moving average and vwap .
2..When OL candle formed and breaks the high we can enter the position, candle should be above supertrend , moving average and vwap .
Hilega-Milega-RSI-EMA-WMA indicator designed by NKThis indicator is works on RSI, Price and volume to give leading Indicator to Buy or Sell.
This indicator works on all financial markets
Hilega-Milega-RSI-EMA-WMA indicator designed by Nitish Sir
For intraday trade, enter with 15 mins chart.
For positional trade, enter with 1-hour chart.
For Investment this system can be used with daily/weekly/monthly chart.
• RED line is for Volume.
• Green line is for the Price.
• Black line is for the RSI (9).
SELL Trade
1. When Volume (RED line) is above/crossed above Price (Green line) and Strength (Black line), then stock price will go down. This means we will SELL.
2. When there is a GAP in the RED line and the Green line till the time price will go down.
Exit criteria
Whenever Red line exit the shaded area of Oversold zone OR Red line cross over the Green and black line then we will exit.
In case of the SELL trade, after the entry we will monitor the trade in 5 min chart, if the candle is closed above the VWAP then exit.
If the price is crossed the 50 SMA then we will exit trade.
BUY Trade
1. When Volume (RED line) is below/crossed below Price (Green line) and Strength (Black line), then stock price will go up. This means we will BUY.
2. When there is a GAP in the RED line and the Green line till the time price will go down.
Exit criteria
Whenever Red line exit the shaded area of Overbought zone OR Red line cross over the Green and black line then we will exit.
In case of the Buy trade, after the entry we will monitor the trade candle is closed below the VWAP then exit.
If the price is crossed the 50 SMA then we will exit trade.
DeepSignalFilterHelpersLibrary "DeepSignalFilterHelpers"
filter_intraday_intensity(useIiiFilter)
Parameters:
useIiiFilter (bool)
filter_vwma(src, length, useVwmaFilter)
Parameters:
src (float)
length (int)
useVwmaFilter (bool)
filter_nvi(useNviFilter)
Parameters:
useNviFilter (bool)
filter_emv(length, emvThreshold, useEmvFilter, useMovingAvg)
EMV filter for filtering signals based on Ease of Movement
Parameters:
length (int) : The length of the EMV calculation
emvThreshold (float) : The EMV threshold
useEmvFilter (bool) : Whether to apply the EMV filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_adi(length, threshold, useAdiFilter, useMovingAvg)
ADI filter for filtering signals based on Accumulation/Distribution Index
Parameters:
length (int) : The length of the ADI moving average calculation
threshold (float) : The ADI threshold
useAdiFilter (bool) : Whether to apply the ADI filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_mfi(length, mfiThreshold, useMfiFilter, useMovingAvg)
MFI filter for filtering signals based on Money Flow Index
Parameters:
length (int) : The length of the MFI calculation
mfiThreshold (float) : The MFI threshold
useMfiFilter (bool) : Whether to apply the MFI filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
detect_obv_states(obvThresholdStrong, obvThresholdModerate, lookbackPeriod, obvMode)
detect_obv_states: Identify OBV states with three levels (Strong, Moderate, Weak) over a configurable period
Parameters:
obvThresholdStrong (float) : Threshold for strong OBV movements
obvThresholdModerate (float) : Threshold for moderate OBV movements
lookbackPeriod (int) : Number of periods to analyze OBV trends
obvMode (string) : OBV mode to filter ("Strong", "Moderate", "Weak")
Returns: OBV state ("Strong Up", "Moderate Up", "Weak Up", "Positive Divergence", "Negative Divergence", "Consolidation", "Weak Down", "Moderate Down", "Strong Down")
filter_obv(src, length, obvMode, threshold, useObvFilter, useMovingAvg)
filter_obv: Filter signals based on OBV states
Parameters:
src (float) : The source series (default: close)
length (int) : The length of the OBV moving average calculation
obvMode (string) : OBV mode to filter ("Strong", "Moderate", "Weak")
threshold (float) : Optional threshold for additional filtering
useObvFilter (bool) : Whether to apply the OBV filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_cmf(length, cmfThreshold, useCmfFilter, useMovingAvg)
CMF filter for filtering signals based on Chaikin Money Flow
Parameters:
length (int) : The length of the CMF calculation
cmfThreshold (float) : The CMF threshold
useCmfFilter (bool) : Whether to apply the CMF filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_vwap(useVwapFilter)
VWAP filter for filtering signals based on Volume-Weighted Average Price
Parameters:
useVwapFilter (bool) : Whether to apply the VWAP filter
Returns: Filtered result indicating whether the signal should be used
filter_pvt(length, pvtThreshold, usePvtFilter, useMovingAvg)
PVT filter for filtering signals based on Price Volume Trend
Parameters:
length (int) : The length of the PVT moving average calculation
pvtThreshold (float) : The PVT threshold
usePvtFilter (bool) : Whether to apply the PVT filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_vo(shortLength, longLength, voThreshold, useVoFilter, useMovingAvg)
VO filter for filtering signals based on Volume Oscillator
Parameters:
shortLength (int) : The length of the short-term volume moving average
longLength (int) : The length of the long-term volume moving average
voThreshold (float) : The Volume Oscillator threshold
useVoFilter (bool) : Whether to apply the VO filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_cho(shortLength, longLength, choThreshold, useChoFilter, useMovingAvg)
CHO filter for filtering signals based on Chaikin Oscillator
Parameters:
shortLength (int) : The length of the short-term ADI moving average
longLength (int) : The length of the long-term ADI moving average
choThreshold (float) : The Chaikin Oscillator threshold
useChoFilter (bool) : Whether to apply the CHO filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_fi(length, fiThreshold, useFiFilter, useMovingAvg)
FI filter for filtering signals based on Force Index
Parameters:
length (int) : The length of the FI calculation
fiThreshold (float) : The Force Index threshold
useFiFilter (bool) : Whether to apply the FI filter
useMovingAvg (bool) : Whether to use moving average as threshold
Returns: Filtered result indicating whether the signal should be used
filter_garman_klass_volatility(length, useGkFilter)
Parameters:
length (int)
useGkFilter (bool)
filter_frama(src, length, useFramaFilter)
Parameters:
src (float)
length (int)
useFramaFilter (bool)
filter_bollinger_bands(src, length, stdDev, useBollingerFilter)
Parameters:
src (float)
length (int)
stdDev (float)
useBollingerFilter (bool)
filter_keltner_channel(src, length, atrMult, useKeltnerFilter)
Parameters:
src (float)
length (simple int)
atrMult (float)
useKeltnerFilter (bool)
regime_filter(src, threshold, useRegimeFilter)
Regime filter for filtering signals based on trend strength
Parameters:
src (float) : The source series
threshold (float) : The threshold for the filter
useRegimeFilter (bool) : Whether to apply the regime filter
Returns: Filtered result indicating whether the signal should be used
regime_filter_v2(src, threshold, useRegimeFilter)
Regime filter for filtering signals based on trend strength
Parameters:
src (float) : The source series
threshold (float) : The threshold for the filter
useRegimeFilter (bool) : Whether to apply the regime filter
Returns: Filtered result indicating whether the signal should be used
filter_adx(src, length, adxThreshold, useAdxFilter)
ADX filter for filtering signals based on ADX strength
Parameters:
src (float) : The source series
length (simple int) : The length of the ADX calculation
adxThreshold (int) : The ADX threshold
useAdxFilter (bool) : Whether to apply the ADX filter
Returns: Filtered result indicating whether the signal should be used
filter_volatility(minLength, maxLength, useVolatilityFilter)
Volatility filter for filtering signals based on volatility
Parameters:
minLength (simple int) : The minimum length for ATR calculation
maxLength (simple int) : The maximum length for ATR calculation
useVolatilityFilter (bool) : Whether to apply the volatility filter
Returns: Filtered result indicating whether the signal should be used
filter_ulcer(src, length, ulcerThreshold, useUlcerFilter)
Ulcer Index filter for filtering signals based on Ulcer Index
Parameters:
src (float) : The source series
length (int) : The length of the Ulcer Index calculation
ulcerThreshold (float) : The Ulcer Index threshold (default: average Ulcer Index)
useUlcerFilter (bool) : Whether to apply the Ulcer Index filter
Returns: Filtered result indicating whether the signal should be used
filter_stddev(src, length, stdDevThreshold, useStdDevFilter)
Standard Deviation filter for filtering signals based on Standard Deviation
Parameters:
src (float) : The source series
length (int) : The length of the Standard Deviation calculation
stdDevThreshold (float) : The Standard Deviation threshold (default: average Standard Deviation)
useStdDevFilter (bool) : Whether to apply the Standard Deviation filter
Returns: Filtered result indicating whether the signal should be used
filter_macdv(src, shortLength, longLength, signalSmoothing, macdVThreshold, useMacdVFilter)
MACD-V filter for filtering signals based on MACD-V
Parameters:
src (float) : The source series
shortLength (simple int) : The short length for MACD calculation
longLength (simple int) : The long length for MACD calculation
signalSmoothing (simple int) : The signal smoothing length for MACD
macdVThreshold (float) : The MACD-V threshold (default: average MACD-V)
useMacdVFilter (bool) : Whether to apply the MACD-V filter
Returns: Filtered result indicating whether the signal should be used
filter_atr(length, atrThreshold, useAtrFilter)
ATR filter for filtering signals based on Average True Range (ATR)
Parameters:
length (simple int) : The length of the ATR calculation
atrThreshold (float) : The ATR threshold (default: average ATR)
useAtrFilter (bool) : Whether to apply the ATR filter
Returns: Filtered result indicating whether the signal should be used
filter_candle_body_and_atr(length, bodyThreshold, atrThreshold, useFilter)
Candle Body and ATR filter for filtering signals
Parameters:
length (simple int) : The length of the ATR calculation
bodyThreshold (float) : The threshold for candle body size (relative to ATR)
atrThreshold (float) : The ATR threshold (default: average ATR)
useFilter (bool) : Whether to apply the candle body and ATR filter
Returns: Filtered result indicating whether the signal should be used
filter_atrp(length, atrpThreshold, useAtrpFilter)
ATRP filter for filtering signals based on ATR Percentage (ATRP)
Parameters:
length (simple int) : The length of the ATR calculation
atrpThreshold (float) : The ATRP threshold (default: average ATRP)
useAtrpFilter (bool) : Whether to apply the ATRP filter
Returns: Filtered result indicating whether the signal should be used
filter_jma(src, length, phase, useJmaFilter)
Parameters:
src (float)
length (simple int)
phase (float)
useJmaFilter (bool)
filter_cidi(src, rsiLength, shortMaLength, longMaLength, useCidiFilter)
Parameters:
src (float)
rsiLength (simple int)
shortMaLength (int)
longMaLength (int)
useCidiFilter (bool)
filter_rsi(src, length, rsiThreshold, useRsiFilter)
Parameters:
src (float)
length (simple int)
rsiThreshold (float)
useRsiFilter (bool)
filter_ichimoku_oscillator(length, threshold, useFilter)
Ichimoku Oscillator filter for filtering signals based on Ichimoku Oscillator
Parameters:
length (int) : The length of the Ichimoku Oscillator calculation
threshold (float) : The threshold for the filter (default: average Ichimoku Oscillator)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_cmb_composite_index(src, shortLength, longLength, threshold, useFilter)
CMB Composite Index filter for filtering signals based on CMB Composite Index
Parameters:
src (float) : The source series
shortLength (simple int) : The short length for CMB calculation
longLength (simple int) : The long length for CMB calculation
threshold (float) : The threshold for the filter (default: average CMB Composite Index)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_connors_rsi(src, rsiLength, rocLength, streakLength, threshold, useFilter)
Connors RSI filter for filtering signals based on Connors RSI
Parameters:
src (float) : The source series
rsiLength (simple int) : The length for RSI calculation
rocLength (int) : The length for ROC calculation
streakLength (simple int) : The length for streak calculation
threshold (float) : The threshold for the filter (default: average Connors RSI)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_coppock_curve(src, roc1Length, roc2Length, wmaLength, threshold, useFilter)
Coppock Curve filter for filtering signals based on Coppock Curve
Parameters:
src (float) : The source series
roc1Length (int) : The length for the first ROC calculation
roc2Length (int) : The length for the second ROC calculation
wmaLength (int) : The length for the WMA calculation
threshold (float) : The threshold for the filter (default: average Coppock Curve)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_pmo(src, pmoLength, smoothingLength, threshold, useFilter)
DecisionPoint Price Momentum Oscillator filter for filtering signals based on PMO
Parameters:
src (float) : The source series
pmoLength (simple int) : The length for PMO calculation
smoothingLength (simple int) : The smoothing length for PMO
threshold (float) : The threshold for the filter (default: average PMO Oscillator)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_macd(src, shortLength, longLength, signalSmoothing, threshold, useFilter)
MACD filter for filtering signals based on MACD
Parameters:
src (float) : The source series
shortLength (simple int) : The short length for MACD calculation
longLength (simple int) : The long length for MACD calculation
signalSmoothing (simple int) : The signal smoothing length for MACD
threshold (float) : The threshold for the filter (default: average MACD)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_macd_histogram(src, shortLength, longLength, signalSmoothing, threshold, useFilter)
MACD-Histogram filter for filtering signals based on MACD-Histogram
Parameters:
src (float) : The source series
shortLength (simple int) : The short length for MACD calculation
longLength (simple int) : The long length for MACD calculation
signalSmoothing (simple int) : The signal smoothing length for MACD
threshold (float) : The threshold for the filter (default: average MACD-Histogram)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_kst(src, r1, r2, r3, r4, sm1, sm2, sm3, sm4, signalLength, threshold, useFilter)
Pring's Know Sure Thing filter for filtering signals based on KST
Parameters:
src (float) : The source series
r1 (int) : The first ROC length
r2 (int) : The second ROC length
r3 (int) : The third ROC length
r4 (int) : The fourth ROC length
sm1 (int) : The first smoothing length
sm2 (int) : The second smoothing length
sm3 (int) : The third smoothing length
sm4 (int) : The fourth smoothing length
signalLength (int) : The signal line smoothing length
threshold (float) : The threshold for the filter (default: average KST Oscillator)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_special_k(src, r1, r2, r3, r4, sm1, sm2, sm3, sm4, threshold, useFilter)
Pring's Special K filter for filtering signals based on Special K
Parameters:
src (float) : The source series
r1 (int) : The first ROC length
r2 (int) : The second ROC length
r3 (int) : The third ROC length
r4 (int) : The fourth ROC length
sm1 (int) : The first smoothing length
sm2 (int) : The second smoothing length
sm3 (int) : The third smoothing length
sm4 (int) : The fourth smoothing length
threshold (float) : The threshold for the filter (default: average Special K)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_roc_momentum(src, rocLength, momentumLength, threshold, useFilter)
ROC and Momentum filter for filtering signals based on ROC and Momentum
Parameters:
src (float) : The source series
rocLength (int) : The length for ROC calculation
momentumLength (int) : The length for Momentum calculation
threshold (float) : The threshold for the filter (default: average ROC and Momentum)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_rrg_relative_strength(src, length, threshold, useFilter)
RRG Relative Strength filter for filtering signals based on RRG Relative Strength
Parameters:
src (float) : The source series
length (int) : The length for RRG Relative Strength calculation
threshold (float) : The threshold for the filter (default: average RRG Relative Strength)
useFilter (bool) : Whether to apply the filter
Returns: Filtered result indicating whether the signal should be used
filter_alligator(useFilter)
Parameters:
useFilter (bool)
filter_wyckoff(useFilter)
Parameters:
useFilter (bool)
filter_squeeze_momentum(bbLength, bbStdDev, kcLength, kcMult, useFilter)
Parameters:
bbLength (int)
bbStdDev (float)
kcLength (simple int)
kcMult (float)
useFilter (bool)
filter_atr_compression(length, atrThreshold, useFilter)
Parameters:
length (simple int)
atrThreshold (float)
useFilter (bool)
filter_low_volume(length, useFilter)
Parameters:
length (int)
useFilter (bool)
filter_nvi_accumulation(useFilter)
Parameters:
useFilter (bool)
filter_ma_slope(src, length, slopeThreshold, useFilter)
Parameters:
src (float)
length (int)
slopeThreshold (float)
useFilter (bool)
filter_adx_low(len, lensig, adxThreshold, useFilter)
Parameters:
len (simple int)
lensig (simple int)
adxThreshold (int)
useFilter (bool)
filter_choppiness_index(length, chopThreshold, useFilter)
Parameters:
length (int)
chopThreshold (float)
useFilter (bool)
filter_range_detection(length, useFilter)
Parameters:
length (int)
useFilter (bool)
Volume Based Price Prediction [EdgeTerminal]This indicator combines price action, volume analysis, and trend prediction to forecast potential future price movements. The indicator creates a dynamic prediction zone with confidence bands, helping you visualize possible price trajectories based on current market conditions.
Key Features
Dynamic price prediction based on volume-weighted trend analysis
Confidence bands showing potential price ranges
Volume-based candle coloring for enhanced market insight
VWAP and Moving Average overlay
Customizable prediction parameters
Real-time updates with each new bar
Technical Components:
Volume-Price Correlation: The indicator analyzes the relationship between price movements and volume, Identifies stronger trends through volume confirmation and uses Volume-Weighted Average Price (VWAP) for price equilibrium
Trend Strength Analysis: Calculates trend direction using exponential moving averages, weights trend strength by relative volume and incorporates momentum for improved accuracy
Prediction Algorithm: combines current price, trend, and volume metrics, projects future price levels using weighted factors and generates confidence bands based on price volatility
Customizable Parameters:
Moving Average Length: Controls the smoothing period for calculations
Volume Weight Factor: Adjusts how much volume influences predictions
Prediction Periods: Number of bars to project into the future
Confidence Band Width: Controls the width of prediction bands
How to use it:
Look for strong volume confirmation with green candles, watch for prediction line slope changes, use confidence bands to gauge potential volatility and compare predictions with key support/resistance levels
Some useful tips:
Start with default settings and adjust gradually
Use wider confidence bands in volatile markets
Consider prediction lines as zones rather than exact levels
Best applications of this indicator:
Trend continuation probability assessment
Potential reversal point identification
Risk management through confidence bands
Volume-based trend confirmation
CSVParser█ OVERVIEW
The library contains functions for parsing and importing complex CSV configurations (with a special simple syntax) into a special hierarchical object (of type objProps ) as follows:
Functions:
parseConfig() - reads CSV text into an objProps object.
toT() - displays the contents of an objProps object in a table form, which allows to check the CSV text for syntax errors.
getPropAr() - returns objProps.arS array for child object with `prop` key in mpObj map (or na if not found)
This library is handy in allowing users to store presets for the scripts and switch between them (see, e.g., my HTF moving averages script where users can switch between several preset configuations of 24 MA's across 5 timeframes).
█ HOW THE SCRIPT WORKS.
The script works as follows:
all values read from config text are stored as strings
Nested brackets in config text create a named nested objects of objProps0, ... , objProps9 types.
objProps objects of each level have the following fields:
- array arS for storing values without names (e.g. "12, 23" will be imported into a string array arS as )
- map mpS for storing items with names (e.g. "tf = 60, length = 21" will be imported as <"tf", "60"> and <"length", "21"> pairs into mpS )
- map mpObj for storing nested objects (e.g. "TF1(tf=60, length(21,50,100))" creates a <"TF1, objProps0 object> pair in mpObj map property of the top level object (objProps) , "tf=60" is stored as <"tf", "60"> key-value pair in mpS map property of a next level object (objProps0) and "length (...)" creates a <"length", objProps1> pair in objProps0.mpObj map while length values are stored in objProps1.arS array as strings. Every opening bracket creates a next level objProps object.
If objects or properties with duplicate names are encountered only the latest is imported
(e.g. for "TF1(length(12,22)), TF1(tf=240)" only "TF1(tf=240)" will be imported
Line breaks are not regarded as part of syntax (i.e. values are imported with line breaks, you can supply
symbols "(" , ")" , "," and "=" are special characters and cannot be used within property values (with the exception of a quoted text as a value of a property as explained below)
named properties can have quoted text as their value. In that case special characters within quotation marks are regarded as normal characters. Text between "=" and opening quotation mark as well as text following the closing quotation mark and until next property value is ignored. E.g. "quote = ignored "The quote" also ignored" will be imported as <"quote", "The quote">. Quotation marks within quotes must be excaped with "\" .
if a key names happens to be a multi-line then only first line containing non-space characters (trimmed from spaces) is taken as a key.
")," or ") ," and similar do not create an empty ("") array item while ",," does. (",)" creates an "" array item)
█ CSV CONFIGURATION SYNTAX
Unnamed values: just list them comma separated and they will be imported into arS of the object of the current level.
Named values: use "=" sign as follows: "property1=value1, property2 = value2"
Value of several objects: Use brackets after the name of the object ant list all object properties within the brackets (including its child objects if necessary). E.g. "TF1(tf =60, length(21,200), TF2(tf=240, length(50,200)"
Named and unnamed values as well as objects can go in any order. E.g. "12, tf=60, 21" will be imported as follows: "12", "21" will go to arS array and <"tf", "60"> will go to mpS maP of objProps (the top level object).
You can play around and test your config text using demo in this library, just edit your text in script settings and see how it is parsed into objProps objects.
█ USAGE RECOMMENDATIONS AND SAMPLE USE
I suggest the following approach:
- create functions for your UDT which can set properties by name.
- create enumerator functions which iterates through all the property names (supplied as a const string array) and imports their values into the object
█ SAMPLE USE
A sample use of this library can be seen in my Multi-timeframe 24 moving averages + BB+SAR+Supertrend+VWAP script where settings for the MAs across many timeframes are imported from CSV configurations (presets).
█ FULL LIST OF FUNCTIONS AND PROPERTIES
nzs(_s, nz)
Like nz() but for strings. Returns `nz` arg (default = "") if _s is na.
Parameters:
_s (string)
nz (string)
method init(this)
Initializes objProps obj (creates child maps and arrays)
Namespace types: objProps
Parameters:
this (objProps)
method toT(this, nz)
Outputs objProps to string matrices for further display using autotable().
Namespace types: objProps, objProps1, ..., objProps9
Parameters:
this (objProps/objProps1/..../objProps9)
nz (string)
Returns: A tuple - value, merge and color matrix (autotable() parameters)
method parseConfig(this, s)
Reads config text into objProps (unnamed values into arS, named into mpS, sub-levels into mpObj)
Namespace types: objProps
Parameters:
this (objProps)
s (string)
method getPropArS(this, prop)
Returns a string array of values for a given property name `prop`. Looks for a key `prop` in objProps.mpObj
if finds pair returns obj.arS, otherwise returns na. Returns a reference to the original, not a copy.
Namespace types: objProps, objProps1, ..., objProps8
Parameters:
this (objProps/objProps1/..../objProps8)
prop (string)
method getPropVal(this, prop, id)
Checks if there is an array of values for property `prop` and returns its `id`'s element or na if not found
Namespace types: objProps, objProps1, ..., objProps8
Parameters:
this (objProps/objProps1/..../objProps8) : objProps object containing array of property values in a child objProp object corresponding to propertty name.
prop (string) : (string) Name of the property
id (int) : (int) Id of the element to be returned from the array pf property values
objProps9 type
Object for storing values read from CSV relating to a particular object or property name.
Fields:
mpS (map) : (map() Stores property values as pairs
arS (array) : (string ) Array of values
objProps, objProps0, ... objProps8 types
Object for storing values read from CSV relating to a particular object or property name.
Fields:
mpS (map) : (map() Stores property values as pairs
arS (array) : (string ) Array of values
mpObj (map) : (map() Stores objProps objects containing properties's data as pairs
TCLC(TraderChitra Learning Class)-Option ChainThis indicator plots the Option chain data of the following instruments and columns..
It plots 11 rows ,
5 Rows above the input strike price
1 Row for the input strike price
5 Rows below the input strike price
Instruments :
1. NIFTY
2. BANKNIFTY
3. FINNIFTY
4. MIDCPNifty
Columns :
1. StrikePrice
2.CMP
3.Volume
4.VWAP
5.Diff (Open-Close)
Traders need to change the expiry date to check the premium of the corresponding instruments...
There are few key things,
1. Rows in yellow are marked as ATM strike price
2. Cell values in red / green indicates the prices are trading above / below the VWAP
The prices are expected to be bullish when cmp trades above VWAP and we can gauge the trend
The column Volume provides the details in which strike price more traders are actively traded..
The far month contracts can also be changed in the settings and it helps the swing/positional traders
The Strike price can be modified to check the appropriate strikes
Overlay-ChartOverlay-Chart Indicator
The Overlay-Chart Indicator is an advanced script designed for scalpers and day traders, providing comprehensive insights into daily, weekly, monthly, and previous period price levels. This indicator helps traders visualize critical price levels and make informed decisions based on historical and current data.
Key Features:
Drawing Future Lines with Labels:
The script uses the drawFutureLine function to plot future price levels with customizable labels. This helps traders anticipate and react to key price points.
Daily Levels:
Displays the open, low, high, close, and equilibrium (EQ) prices for the current day. This provides a quick reference for daily trading ranges and significant price points.
Weekly Levels:
Shows the open, low, high, close, and equilibrium prices for the current week, offering a broader view of market trends and key weekly price levels.
Monthly Levels:
Illustrates the open, low, high, close, and equilibrium prices for the current month, enabling traders to understand long-term trends and significant monthly price points.
Previous Day, Week, and Month Levels:
Historical data from previous periods (day, week, month) is displayed, allowing traders to compare past and present price levels to identify patterns and potential support/resistance levels.
Customizable Colors:
Traders can choose colors for daily, weekly, monthly, and previous day levels to enhance chart readability and personalization.
Flexible Display Options:
Users can select which price levels (Open, Low, High, Close, EQ) to display for each period (daily, weekly, monthly, previous day, week, month).
How It Works:
The script fetches historical and current price data using the request.security function. It then uses these data points to draw lines on the chart representing significant price levels. These lines are drawn into the future to help traders visualize where these levels will be in upcoming bars. Labels are added to these lines for easy identification.
How to Use:
Configure Inputs:
Enable or disable the display of daily, weekly, monthly, and previous period levels using the input options.
Customize colors for different levels to match your charting preferences.
Analyze Key Levels:
Observe the plotted lines and labels to understand critical price points for the current and past periods.
Use this information to identify potential entry and exit points, support and resistance levels, and overall market trends.
Future Planned Features:
The script includes several features that are currently commented out but planned for future updates:
Volume Weighted Average Price (VWAP):
Display VWAP for daily, weekly, and monthly periods to provide an average price based on volume.
Point of Control (POC):
Show the price level with the highest trading volume for daily, weekly, and monthly periods.
Value Area High (VAH) and Low (VAL):
Display the upper and lower boundaries of the value area where most trading activity occurs for daily, weekly, and monthly periods.
These enhancements will offer additional insights into volume distribution and market sentiment, further improving the utility of the Overlay-Chart Indicator for traders.
This script is specifically designed to cater to the needs of scalpers and day traders who require precise, visually intuitive data for their trading strategies. The planned features will further enhance its effectiveness, providing a comprehensive tool for market analysis.
Uptrick: TrendVol IndicatorPurpose:
The "Uptrick: TrendVol Indicator," known by its abbreviated title 'U:TVI,' is meticulously crafted to offer traders insights into both trend strength and volume dynamics within the market. By visualizing trend strength relative to a moving average, analyzing volume activity, and assessing potential price movements, traders can make informed decisions and navigate the markets more effectively.
Explanation:
Moving Averages and Trend Direction:
The script computes a moving average (MA) over a specified period, allowing traders to gauge the prevailing trend direction.
Trend strength is assessed by measuring the distance between the closing price and the moving average, providing a quantitative representation of market momentum.
By comparing the current price relative to the moving average, traders can determine potential price directionality, with prices above the MA suggesting bullish sentiment and prices below indicating bearish sentiment.
Volatility Analysis:
Volatility is measured using the Average True Range (ATR) indicator over a user-defined period, aiding traders in assessing the potential range of price movements.
By plotting the ATR value alongside trend strength, traders gain valuable insights into both trend stability and potential breakout opportunities.
Additional Moving Averages and Multiple Time Frame Analysis:
The script incorporates another moving average (MA2) over a different period, enabling traders to conduct multiple time frame analysis and validate trend signals across different time frames.
The inclusion of MA2 enhances the robustness of trend identification and facilitates a more comprehensive understanding of market trends.
Volume Analysis:
Volume analysis is conducted by computing a moving average of volume over a specified period, allowing traders to discern patterns of increasing or decreasing volume activity.
Bars with volume exceeding a predefined threshold are highlighted, providing traders with insights into significant volume spikes that may accompany price movements.
Determining Potential Price Movements:
Traders can utilize the "Uptrick: TrendVol Indicator" to assess the likelihood of potential price movements.
A bullish bias may be inferred when the current price is above both the moving average and the volume-weighted average price (VWAP), accompanied by rising volume.
Conversely, a bearish bias may be indicated when the price is below both the moving average and the VWAP, with declining volume reinforcing the potential for downward price movements.
Utility and Potential Usage:
The indicator serves as a powerful tool for traders, offering a holistic view of market dynamics encompassing trend strength, volume activity, and potential price movements.
Traders can leverage the insights provided by the indicator to identify trading opportunities, manage risk effectively, and capitalize on emerging market trends with confidence.
Through its comprehensive design and advanced features, the "Uptrick: TrendVol Indicator" equips traders with actionable insights into market dynamics, enabling them to make well-informed trading decisions and navigate the markets with precision.
Kalman Filter Volume Bands by TenozenHello there! I am excited to introduce a new original indicator, the Kalman Filter Volume Bands. This indicator is calculated using the Kalman Filter, which is an adaptive-based smoothing quantitative tool. The Kalman Filter Volume Bands have two components that support the calculation, namely VWAP and VaR.
VWAP is used to determine the weight of the Kalman Filter Returns, but it doesn't have a significant impact on the calculation. On the other hand, VaR or Value at risk is calculated using the 99th percentile, which means that there is a 1% chance for the returns to exceed the 99th percentile level. After getting the VaR value, I manually adjust the bands based on the current market I'm trading on. I take the highest point (VaR*2) and the lowest point (-(VaR*2)) from the Kalman Filter, and then divide them into segments manually based on my preference.
This process results in 8 segments, where 2 segments near the Kalman Filter are further divided, making a total of 12 segments. These segments classify the current state of the price based on code-based coloring. The five states are very bullish, bullish, very bearish, bearish, and neutral.
I created this indicator to have an adaptive band that is not biased toward the volatility of the market. Most band-based indicators don't capture reversals that well, but the Kalman Filter Volume Bands can capture both trends and reversals. This makes it suitable for both trend-following and reversal trading approaches.
That's all for the explanation! Ciao!
Additional Reminder:
- Please use hourly timeframes or higher as lower timeframes are too noisy for reliable readings of this indicator.
NASDAQ 100 Peak Hours StrategyNASDAQ 100 Peak Hours Trading Strategy
Description
Our NASDAQ 100 Peak Hours Trading Strategy leverages a carefully designed algorithm to trade within specific hours of high market activity, particularly focusing on the first two hours of the trading session from 09:30 AM to 11:30 AM GMT-5. This period is identified for its increased volatility and liquidity, offering numerous trading opportunities.
The strategy incorporates a blend of technical indicators to identify entry and exit points for both long and short positions. These indicators include:
Exponential Moving Averages (EMAs) : A short-term 9-period EMA and a longer-term 21-period EMA to determine the market trend and momentum.
Relative Strength Index (RSI) : A 14-period RSI to gauge the market's momentum.
Average True Range (ATR) : A 14-period ATR to assess market volatility and to set dynamic stop losses and trailing stops.
Volume Weighted Average Price (VWAP) : To identify the market's average price weighted by volume, serving as a benchmark for the trading day.
Our strategy uniquely applies a volatility filter using the ATR, ensuring trades are only executed in conditions that favor our setup. Additionally, we consider the direction of the EMAs to confirm the market's trend before entering trades.
Originality and Usefulness
This strategy stands out by combining these indicators within the NASDAQ 100's peak hours, exploiting the specific market conditions that prevail during these times. The inclusion of a volatility filter and dynamic stop-loss mechanisms based on the ATR provides a robust method for managing risk.
By focusing on the early trading hours, the strategy aims to capture the initial market movements driven by overnight news and the opening rush, often characterized by higher volatility. This approach is particularly useful for traders looking to maximize gains from short-term fluctuations while limiting exposure to longer-term market uncertainty.
Strategy Results
To ensure the strategy's effectiveness and reliability, it has undergone rigorous backtesting over a significant dataset to produce a sample size of more than 100 trades. This testing phase helps in identifying the strategy's potential in various market conditions, its consistency, and its risk-to-reward ratio.
Our backtesting adheres to realistic trading conditions, accounting for slippage and commission to reflect actual trading scenarios accurately. The strategy is designed with a conservative approach to risk management, advising not to risk more than 5-10% of equity on a single trade. The default settings in the script align with these principles, ensuring that users can replicate our tested conditions.
Using the Strategy
The strategy is designed for simplicity and ease of use:
Trade Hours : Focuses on 09:30 AM to 11:30 AM GMT-5, during the NASDAQ 100's peak activity hours.
Entry Conditions : Trades are initiated based on the alignment of EMAs, RSI, VWAP, and the ATR's volatility filter within the designated time frame.
Exit Conditions : Includes dynamic trailing stops based on ATR, a predefined time exit strategy, and a trend reversal exit condition for risk management.
This script is a powerful tool for traders looking to leverage the NASDAQ 100's peak hours, providing a structured approach to navigating the early market hours with a robust set of criteria for making informed trading decisions.
lib_mathLibrary "lib_math"
a collection of functions calculating without history operator to avoid max_bars_back errors
mean(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return returns average/mean of value since last reset
vwap(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return returns vwap of value and volume since last reset
variance(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return returns variance of value since last reset
trend(value, reset)
Parameters:
value (float) : series to track
reset (bool) : flag to reset tracking
@return where slope is the trend direction, correlation is a measurement for how well the values fit to the trendline (positive means ), stddev is how far the values deviate from the trend, x1 would be the time where reset is true and x2 would be the current time
DIY Custom Strategy Builder [ZP] - v1DISCLAIMER:
This indicator as my first ever Tradingview indicator, has been developed for my personal trading analysis, consolidating various powerful indicators that I frequently use. A number of the embedded indicators within this tool are the creations of esteemed Pine Script developers from the TradingView community. In recognition of their contributions, the names of these developers will be prominently displayed alongside the respective indicator names. My selection of these indicators is rooted in my own experience and reflects those that have proven most effective for me. Please note that the past performance of any trading system or methodology is not necessarily indicative of future results. Always conduct your own research and due diligence before using any indicator or tool.
===========================================================================
Introducing the ultimate all-in-one DIY strategy builder indicator, With over 30+ famous indicators (some with custom configuration/settings) indicators included, you now have the power to mix and match to create your own custom strategy for shorter time or longer time frames depending on your trading style. Say goodbye to cluttered charts and manual/visual confirmation of multiple indicators and hello to endless possibilities with this indicator.
What it does
==================
This indicator basically help users to do 2 things:
1) Strategy Builder
With more than 30 indicators available, you can select any combination you prefer and the indicator will generate buy and sell signals accordingly. Alternative to the time-consuming process of manually confirming signals from multiple indicators! This indicator streamlines the process by automatically printing buy and sell signals based on your chosen combination of indicators. No more staring at the screen for hours on end, simply set up alerts and let the indicator do the work for you.
Available indicators that you can choose to build your strategy, are coded to seamlessly print the BUY and SELL signal upon confirmation of all selected indicators:
EMA Filter
2 EMA Cross
3 EMA Cross
Range Filter (Guikroth)
SuperTrend
Ichimoku Cloud
SuperIchi (LuxAlgo)
B-Xtrender (QuantTherapy)
Bull Bear Power Trend (Dreadblitz)
VWAP
BB Oscillator (Veryfid)
Trend Meter (Lij_MC)
Chandelier Exit (Everget)
CCI
Awesome Oscillator
DMI ( Adx )
Parabolic SAR
Waddah Attar Explosion (Shayankm)
Volatility Oscillator (Veryfid)
Damiani Volatility ( DV ) (RichardoSantos)
Stochastic
RSI
MACD
SSL Channel (ErwinBeckers)
Schaff Trend Cycle ( STC ) (LazyBear)
Chaikin Money Flow
Volume
Wolfpack Id (Darrellfischer1)
QQE Mod (Mihkhel00)
Hull Suite (Insilico)
Vortex Indicator
2) Overlay Indicators
Access the full potential of this indicator using the SWITCH BOARD section! Here, you have the ability to turn on and plot up to 14 of the included indicators on your chart. Simply select from the following options:
EMA
Support/Resistance (HeWhoMustNotBeNamed)
Supply/ Demand Zone ( SMC ) (Pmgjiv)
Parabolic SAR
Ichimoku Cloud
Superichi (LuxAlgo)
SuperTrend
Range Filter (Guikroth)
Average True Range (ATR)
VWAP
Schaff Trend Cycle ( STC ) (LazyBear)
PVSRA (TradersReality)
Liquidity Zone/Vector Candle Zone (TradersReality)
Market Sessions (Aurocks_AIF)
How it does it
==================
To explain how this indictor generate signal or does what it does, its best to put in points.
I have coded the strategy for each of the indicator, for some of the indicator you will see the option to choose strategy variation, these variants are either famous among the traders or its the ones I found more accurate based on my usage. By coding the strategy I will have the BUY and SELL signal generated by each indicator in the backend.
Next, the indicator will identify your selected LEADING INDICATOR and the CONFIRMATION INDICATOR(s).
On each candle close, the indicator will check if the selected LEADING INDICATOR generates signal (long or short).
Once the leading indicator generates the signal, then the indicator will scan each of the selected CONFIRMATION INDICATORS on candle close to check if any of the CONFIRMATION INDICATOR generated signal (long or short).
Until this point, all the process is happening in the backend, the indicator will print LONG or SHORT signal on the chart ONLY if LEADING INDICATOR and all the selected CONFIRMATION INDICATORS generates signal on candle close. example for long signal, the LEADING INDICATOR and all selected CONFIRMATION INDICATORS must print long signal.
The dashboard table will show your selected LEADING and CONFIRMATION INDICATORS and if LEADING or the CONFIRMATION INDICATORS have generated signal. Signal generated by LEADING and CONFIRMATION indicator whether long or short, is indicated by tick icon ✔. and if any of the selected CONFIRMATION or LEADING indicator does not generate signal on candle close, it will be indicated with cross symbol ✖.
how to use this indicator
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Using the indicator is pretty simple, but it depends on your goal, whether you want to use it for overlaying the available indicators or using it to build your strategy or for both.
To use for Building your strategy: Select your LEADING INDICATOR, and then select your CONFIRMATION INDICATOR(s). if on candle close all the indicators generate signal, then this indicator will print SHORT or LONG signal on the chart for your entry. There are plenty of indicators you can use to build your strategy, some indicators are best for longer time frame setups while others are responsive indicators that are best for short time frame.
To use for overlaying the indicators: Open the setting of this indicator and scroll to the SWITCHBOARD section, from there you can select which indicator you want to plot on the chart.
For each of the listed indicators, you have the flexibility to customize the settings and configurations to suit your preferences. simply open indicator setting and scroll down, you will find configuration for each of the indicators used.
I will also release the Strategy Backtester for this indicator soon.
Volume HeatMap With Profile [ChartPrime]The Volume Heatmap with Profile indicator is a tool designed to provide traders with a comprehensive view of market activity through customizable visualizations. This indicator goes beyond traditional volume analysis by offering a range of adjustable parameters and features that enhance analysis of volume and give a cleaner experience when analyzing it.
To get started click the start and end time for the profile.
Key Features:
Extended Calculation: This indicator extends its calculation to the last bar, ensuring that the user has insights into current market dynamics.
Point of Control (POC): Easily identify the price level at which the highest trading activity has occurred, helping the user pinpoint potential reversal points and significant support/resistance zones.
VWAP Point of Control: Display the Volume Weighted Average Price (VWAP) Point of Control, giving the user a clear reference for determining the average price traders are paying and potential price reversals.
Adjustable Colors for Heatmap: Change the heatmap colors to the users preference, allowing the user to match the indicator's appearance to their chart style and personal visual preferences.
Forecasted Zone: This feature allows traders to forecast areas of high activity by providing the option to adjust colors within this zone. This feature assists in identifying potential breakouts or areas where increased trading volume is anticipated.
Volume Profile: Customize the colors of the volume profile to make it distinct and easily distinguishable on the chart.
Adjustable Volume Levels: Specify the number volume levels that are most relevant to your trading strategy.
Adjustable Placement for Volume Profile: Position the volume profile on the chart. Whether the user prefers it on the left, right, or at the center of the chart, this indicator offers placement flexibility.
The ratio of bull vs bear volume is plotted on the outside of the range indicating how bullish or bearish price action is in a given range.
AI-Bank-Nifty Tech AnalysisThis code is a TradingView indicator that analyzes the Bank Nifty index of the Indian stock market. It uses various inputs to customize the indicator's appearance and analysis, such as enabling analysis based on the chart's timeframe, detecting bullish and bearish engulfing candles, and setting the table position and style.
The code imports an external script called BankNifty_CSM, which likely contains functions that calculate technical indicators such as the RSI, MACD, VWAP, and more. The code then defines several table cell colors and other styling parameters.
Next, the code defines a table to display the technical analysis of eight bank stocks in the Bank Nifty index. It then defines a function called get_BankComponent_Details that takes a stock symbol as input, requests the stock's OHLCV data, and calculates several technical indicators using the imported CSM_BankNifty functions.
The code also defines two functions called get_EngulfingBullish_Detection and get_EngulfingBearish_Detection to detect bullish and bearish engulfing candles.
Finally, the code calculates the technical analysis for each bank stock using the get_BankComponent_Details function and displays the results in the table. If the engulfing input is enabled, the code also checks for bullish and bearish engulfing candles and displays buy/sell signals accordingly.
The FRAMA stands for "Fractal Adaptive Moving Average," which is a type of moving average that adjusts its smoothing factor based on the fractal dimension of the price data. The fractal dimension reflects self-similarity at different scales. The FRAMA uses this property to adapt to the scale of price movements, capturing short-term and long-term trends while minimizing lag. The FRAMA was developed by John F. Ehlers and is commonly used by traders and analysts in technical analysis to identify trends and generate buy and sell signals. I tried to create this indicator in Pine.
In this context, "RS" stands for "Relative Strength," which is a technical indicator that compares the performance of a particular stock or market sector against a benchmark index.
The "Alligator" is a technical analysis tool that consists of three smoothed moving averages. Introduced by Bill Williams in his book "Trading Chaos," the three lines are called the Jaw, Teeth, and Lips of the Alligator. The Alligator indicator helps traders identify the trend direction and its strength, as well as potential entry and exit points. When the three lines are intertwined or close to each other, it indicates a range-bound market, while a divergence between them indicates a trending market. The position of the price in relation to the Alligator lines can also provide signals, such as a buy signal when the price crosses above the Alligator lines and a sell signal when the price crosses below them.
In addition to these, we have several other commonly used technical indicators, such as MACD, RSI, MFI (Money Flow Index), VWAP, EMA, and Supertrend. I used all the built-in functions for these indicators from TradingView. Thanks to the developer of this TradingView Indicator.
I also created a BankNifty Components Table and checked it on the dashboard.
Multiple Moving Average ToolkitFeatures Overview:
Multiple Moving Averages: The script allows you to plot up to five different Moving Averages (MAs) on your chart at the same time. You can choose the type of MA (EMA, SMA, HMA, WMA, DEMA, VWMA, VWAP) and the length of each one.
Color Ribbon: You can turn the MAs into a color ribbon by selecting the "Turn into Color Ribbon?" option. This will make the area between the MAs colored and can help you identify trends more easily.
MA Value Table: You can draw a table on your chart that displays the current values of each MA, whether the trend is bullish or bearish along with the length of the MAs. The current ATR value is also shown in the last cell of the table. You can choose the location of the table (Top Left, Top Right, Bottom Left, Bottom Right) and the transparency of the background color.
Crosses: The script can detect when two MAs cross over each other (1st MA crosses 5th MA and vice versa), indicating a potential trend reversal. It will plot crosses on the chart at the point of the crossover and give an alert if the "Bullish Cross Detected" or "Bearish Cross Detected" condition is met.
How to use:
Once the script is added to your chart, you can customize the settings to fit your preferences. You can choose the type and length of each MA, whether to turn them into a color ribbon, whether to plot crosses, and whether to draw the MA Value Table.
The MA Value Table can be moved to a different location on the chart by selecting the "Location of Table" option and choosing Top Left, Top Right, Bottom Left, or Bottom Right.
Watch for MA crossovers and alerts to identify potential trend reversals. The script can help you identify bullish and bearish trends by color-coding the area between the MAs and displaying the current values of each MA in the table.
Breakdown of the script:
User Inputs
The first section of the script defines several user inputs that allows you to customize the indicator. These include options for turning the MAs into a color ribbon, plotting crosses when there is a bullish or bearish cross of the MAs, drawing a table of the MA values, and setting the transparency of the ribbon. You can also select the location of the MA value table and customize the settings for each individual MA.
Moving Average Calculation
The script defines a function called "getMA" that calculates the moving average for a given type and length. The function uses a switch statement to determine which type of moving average to use, such as an exponential moving average (EMA), simple moving average (SMA), Hull moving average (HMA), weighted moving average (WMA), double exponential moving average (DEMA), volume-weighted moving average (VWMA), or volume-weighted average price (VWAP).
The script then calls this function to calculate the values of up to five different MAs, depending on the user input. The ATR (average true range) is also calculated using the TA library.
Color Filter and Cross Detection
The script sets a color filter based on the relationship between the MAs. If the shorter-term MAs are above the longer-term MAs, the filter is set to green to indicate a bullish trend, and if the shorter-term MAs are below the longer-term MAs, the filter is set to red to indicate a bearish trend. You can adjust the transparency of the ribbon to make it more or less visible.
The script also detects when there is a bullish or bearish cross of the MAs and can generate alerts to notify you.
MA Plotting
The script plots up to five MAs on the chart, depending on the user input. The MAs are plotted as lines with different colors and thicknesses, and you can choose to turn them into a color ribbon if desired.
Cross Plotting
The script plots crosses on the chart when there is a bullish or bearish cross of the MAs. The crosses are plotted as X shapes at the location of the cross and are color-coded to indicate the direction of the cross.
MA Value Table
Finally, the script draws a table of the MA values on the chart, displaying the values of each MA as well as the current trend and the ATR. You can customize the location of the table, and the table is colored to match the color filter of the MAs.
Feel free to message me or comment on the post with any questions or issues!
Much more to come!
Thanks for reading, enjoy!
Typical Price Difference - TPD © with reversal zones and signalsv1.0 NOTE: The maths have been tested only for BTC and weekly time frame.
This is a concept that I came through after long long hours of VWAP trading and scalping.
The idea is pretty simple:
1) Typical Price is calculated by (h+l+c) / 3. If we take this price and adjust it to volume we get the VWAP value. The difference between this value and the close value, i call it " Typical Price Difference - TPD ".
2) We get the Historical Volatility as calculated by TradingView script and we add it up to TPD and divide it by two (average). This is what I call " The Source - TS ".
3) We apply the CCI formula to TS .
4) We calculate the Rate of Change (roc) of the CCI formula.
5) We apply the VIX FIX of Larry Williams (script used is from ChrisMoody - CM_Williams_Vix_Fix Finds Market Bottoms) *brilliant script!!!
How to use it:
a) When the (3) is over the TPD we have a bullish bias (green area). When it's under we have a bearish bias (red area).
b) If the (1) value goes over or under a certain value (CAUTION!!! it varies in different assets or timeframes) we get a Reversal Zone (RZ). Red/Green background.
c) If we are in a RZ and the VIX FIX gives a strong value (look for green bars in histogram) and roc (4) goes in the opposite direction, we get a reversal signal that works for the next week(s).
I applied this to BTC on a weekly time frame and after some corrections, it gives pretty good reversal zones and signals. Especially bottoms. Also look for divergences in the zones/signals.
As I said I have tested and confirmed it only on BTC/weekly. I need more time with the maths and pine to automatically adjust it to other time frames. You can play with it in different assets or time frames to find best settings by hand.
Feel free to share your thoughts or ideas on this.
P.S. I realy realy realy try to remember when or how or why I came up with the idea to combine typical price with historical volatility and CCI. I can't! It doesn't make any sense LOL
