ToxicJ3ster - Day Trading SignalsThis Pine Script™ indicator, "ToxicJ3ster - Signals for Day Trading," is designed to assist traders in identifying key trading signals for day trading. It employs a combination of Moving Averages, RSI, Volume, ATR, ADX, Bollinger Bands, and VWAP to generate buy and sell signals. The script also incorporates multiple timeframe analysis to enhance signal accuracy. It is optimized for use on the 5-minute chart.
Purpose:
This script uniquely combines various technical indicators to create a comprehensive and reliable day trading strategy. Each indicator serves a specific purpose, and their integration is designed to provide multiple layers of confirmation for trading signals, reducing false signals and increasing trading accuracy.
1. Moving Averages: These are used to identify the overall trend direction. By calculating short and long period Moving Averages, the script can detect bullish and bearish crossovers, which are key signals for entering and exiting trades.
2. RSI Filtering: The Relative Strength Index (RSI) helps filter signals by ensuring trades are only taken in favorable market conditions. It detects overbought and oversold levels and trends within the RSI to confirm market momentum.
3. Volume and ATR Conditions: Volume and ATR multipliers are used to identify significant market activity. The script checks for volume spikes and volatility to confirm the strength of trends and avoid false signals.
4. ADX Filtering: The ADX is used to confirm the strength of a trend. By filtering out weak trends, the script focuses on strong and reliable signals, enhancing the accuracy of trade entries and exits.
5. Bollinger Bands: Bollinger Bands provide additional context for the trend and help identify potential reversal points. The script uses Bollinger Bands to avoid false signals and ensure trades are taken in trending markets.
6. Higher Timeframe Analysis: This feature ensures that signals align with broader market trends by using higher timeframe Moving Averages for trend confirmation. It adds a layer of robustness to the signals generated on the 5-minute chart.
7. VWAP Integration: VWAP is used for intraday trading signals. By calculating the VWAP and generating buy and sell signals based on its crossover with the price, the script provides additional confirmation for trade entries.
8. MACD Analysis: The MACD line, signal line, and histogram are calculated to generate additional buy/sell signals. The MACD is used to detect changes in the strength, direction, momentum, and duration of a trend.
9. Alert System: Custom alerts are integrated to notify traders of potential trading opportunities based on the signals generated by the script.
How It Works:
- Trend Detection: The script calculates short and long period Moving Averages and identifies bullish and bearish crossovers to determine the trend direction.
- Signal Filtering: RSI, Volume, ATR, and ADX are used to filter and confirm signals, ensuring trades are taken in strong and favorable market conditions.
- Multiple Timeframe Analysis: The script uses higher timeframe Moving Averages to confirm trends, aligning signals with broader market movements.
- Additional Confirmations: VWAP, MACD, and Bollinger Bands provide multiple layers of confirmation for buy and sell signals, enhancing the reliability of the trading strategy.
Usage:
- Customize the input parameters to suit your trading strategy and preferences.
- Monitor the generated signals and alerts to make informed trading decisions.
- This script is made to work best on the 5-minute chart.
Disclaimer:
This indicator is not perfect and can generate false signals. It is up to the trader to determine how they would like to proceed with their trades. Always conduct thorough research and consider seeking advice from a financial professional before making trading decisions. Use this script at your own risk.
Cerca negli script per "adx"
Quantiple Direction IndexThis indicator indicates market trends by analyzing the following signals:
1. RSI which is a momentum oscillator
2. Directional Movement Index (DMI) which measures the direction of the movement
3. Price in comparison to EMA 13 and 21 to determine whether the trend is clear or there is an ambiguity
4. ADX that shows the strength of the momentum
Scoring logic
While we have kept the source code open which gives the scoring logic, for ease of the user, I am summarizing the scoring logic
A. We break down RSI and DMI into a 9 point scale (-4 to +4) from extremely bearish to bullish. Then we give equal weight to both and come out with a direction score.
B. We use EMA to determine if their is clarity in the price trend. While the direction is deduced from point A, if there is clarity we know that the confidence on the direction is high. If EMA 13 is higher than EMA 21 and the price is above EMA 13, then we assign it as a score of +1 as we get clear bullish trend. Similarly if EMA 13 is below EMA 21 and the price is below both the EMAs then we assign it a score of -1 as we get clear bearish trend. Anything else is considered as inconclusive and given a score of 0
C. We use ADX to determine the strength of the directional momentum. It is like acceleration. We use ADX score as an strength adjustment factor. If the value is above 25 - we multiply A+B by 1.25. Similarly we multiply it by 0.75 if the strength is weak and no change if the strength is neutral.
Finally this indicator categorizes market direction into five levels:
- Very Bullish
- Bullish
- Neutral
- Bearish
- Very Bearish
Scores range from +6 (very bullish) to -6 (very bearish), with the user setting thresholds for each category. The midpoint between Bullish and Bearish defines the neutral zone.
Again all the exact values are in the code and the user can also customize as per their trading system.
Why does it make sense to combine these different indicators rather than looking at them in isolation?
We give equal weight to RSI and DMI to derive the direction of the price movement. Using two different indicators provide a better confirmation on the direction. However, this alone is not sufficient.
We want clarity of the direction and for that we use the EMA score (please refer to point B above). If we have clarity, the probability of the direction being right goes up.
Once we know the direction, we want to know what is the strength of that direction. This point is very valuable for an option trader. This is where this indicator brings value.
Please note that by looking at these indicators in isolation one can get a sense of direction or a sense of strength of the direction. But, when you combine them, you get whether the direction move is with strength or not. If you are into option trading, you will clearly understand the rational behind it when you look at the trading rules provided in this description. For example if one knows that the direction is bullish (which one can potentially get from RSI or DMI), one can either buy a call or sell a put. But one knows that not only the direction is bullish, but it has the right acceleration (strength of the momentum), then one will assign higher probability of higher profit from buying call than from selling put.
To summarize we have combined indicators to achieve the following
1. Get confirmation from two different indicators on the direction of the price movement (RSI and DMI)
2. Confirm that the direction is clear (Price relative to EMA)
3. Combine with the strength of the direction (ADX)
Direction, clarity of the direction and the strength of the directional movement is a valuable trading indicator in our opinion.
Suggested trading rules
1. Short strangle strategy when the trend is neutral with one's usual option selling quantity. Equal quantity on put and call.
2. Full quantity short put and half quantity short call when the trend is bullish.
3. Full quantity short put and call long when the indicator is very bullish.
4. Vice versa for bearish ( full call short, half put short) and very bearish (full call short, put long)
Suggested to use 5 min timeframe for scalping, 15 min for intraday positions, 1 hour for weekly and monthly positions, and daily/weekly for investments.
The value of this indicator oscillates between +6 to -6. You can tweak the range for V bullish, bullish, bearish, and v bearish. The values in between will default to the neutral zone.
Disclaimers:
1. While the creator has used this in the live market, no claim is being made on its effectiveness or profit making ability. Please use it for trading only after you have tested it and are satisfied.
2. There may be thousands or millions of better trader in this world than the creator of this script. The creator makes no claim of his intelligence or trading ability.
3. The creator has no intention of selling this particular script now or in future. This is purely for community use and there's no intention to make any monetary profit from it.
4. The creator is not requesting or soliciting anyone to like or promote this script. The creator is also not asking anyone to give him any business now or in future even if they like this script and benefit from it.
Enhanced Reversal DetectionScript Description:
The "Enhanced Reversal Detection" indicator is a powerful tool designed to identify potential market reversals across various financial instruments. It incorporates a sophisticated algorithm that analyzes price action along with key technical indicators such as the Relative Strength Index (RSI), Bollinger Bands, and Moving Average (MA).
How to Use:
Adjustable Parameters: The indicator offers a range of adjustable parameters to cater to different trading preferences and market conditions.
RSI Length: Adjusts the length of the RSI calculation to fine-tune sensitivity.
Overbought Level: Sets the threshold for identifying overbought conditions on the RSI scale.
Oversold Level: Sets the threshold for identifying oversold conditions on the RSI scale.
Bollinger Bands Length: Determines the length of the Bollinger Bands calculation.
Bollinger Bands Multiplier: Adjusts the standard deviation multiplier for the Bollinger Bands, influencing band width.
Moving Average Length: Defines the length of the Moving Average calculation to capture trend direction.
Min Bars Between Signals: Sets the minimum number of bars required between consecutive reversal signals.
ADX Length: Adjusts the length of the Average Directional Index (ADX) calculation.
ADX Threshold: Defines the threshold value for ADX, serving as a filter for reversal signals.
Signal Generation: The indicator generates signals for both bullish and bearish reversals based on predefined criteria. A bullish reversal signal is triggered when the closing price exceeds the lower Bollinger Band and RSI falls below the oversold threshold. Conversely, a bearish reversal signal occurs when the closing price falls below the upper Bollinger Band and RSI surpasses the overbought threshold.
Alerts: Traders can opt to receive alerts for bullish and bearish reversal signals, enabling them to stay informed of potential trading opportunities even when away from the platform.
Publication Readiness:
To ensure readiness for publication in the TradingView public library, the script has been meticulously crafted and documented:
The code is extensively commented to provide clear explanations of parameters, calculations, and signal generation logic.
Best coding practices have been followed to enhance readability and maintainability.
Rigorous testing has been conducted to validate the accuracy and reliability of signal generation across various market conditions.
The script adheres to TradingView's guidelines and policies for script publication, ensuring compliance with platform standards and user expectations.
With its comprehensive features and user-friendly design, the "Enhanced Reversal Detection" indicator is poised to become a valuable asset for traders seeking to identify high-probability reversal opportunities in the financial markets.
MyLibrary_functions_D_S_3D_D_T_PART_1Library "MyLibrary_functions_D_S_3D_D_T_PART_1"
TODO: add library description here
color_(upcolor_txt, upcolor, dncolor_txt, dncolor, theme)
Parameters:
upcolor_txt (color)
upcolor (color)
dncolor_txt (color)
dncolor (color)
theme (string)
Source_Zigzag_F(Source)
Parameters:
Source (string)
p_lw_hg(Source_low, Source_high, Depth)
Parameters:
Source_low (float)
Source_high (float)
Depth (int)
lowing_highing(Source_low, Source_high, p_lw, p_hg, Deviation)
Parameters:
Source_low (float)
Source_high (float)
p_lw (int)
p_hg (int)
Deviation (int)
ll_lh(lowing, highing)
Parameters:
lowing (bool)
highing (bool)
down_ll_down_lh(ll, lh, Backstep)
Parameters:
ll (int)
lh (int)
Backstep (int)
down(down_ll, down_lh, lw, hg)
Parameters:
down_ll (bool)
down_lh (bool)
lw (int)
hg (int)
f_x_P_S123_lw(lw_, hg_, p_lw_, down, Source_low)
Parameters:
lw_ (int)
hg_ (int)
p_lw_ (int)
down (int)
Source_low (float)
f_x_P_S123_hg(lw_, hg_, p_hg_, down, Source_high)
Parameters:
lw_ (int)
hg_ (int)
p_hg_ (int)
down (int)
Source_high (float)
Update_lw_hg_last_l_last_h(lw, hg, last_l, last_h, p_lw, p_hg, down, Source_low, Source_high)
Parameters:
lw (int)
hg (int)
last_l (int)
last_h (int)
p_lw (int)
p_hg (int)
down (int)
Source_low (float)
Source_high (float)
x1_P_y1_P_x2_P_y2_P_x3_P_y3_P_x4_P_y4_P(lw, hg, last_l, last_h, Source)
Parameters:
lw (int)
hg (int)
last_l (int)
last_h (int)
Source (string)
x1_P_os(lw, hg, x2_D, Diverjence_MACD_Line_, Diverjence_MACD_Histagram_, Diverjence_RSI_, Diverjence_Stochastic_, Diverjence_volume_, Diverjence_CCI_, Diverjence_MFI_, Diverjence_Momentum_, Diverjence_OBV_, Diverjence_ADX_, MACD, hist_MACD, RSI, volume_ok, Stochastic_K, CCI, MFI, momentum, OBV, adx)
Parameters:
lw (int)
hg (int)
x2_D (int)
Diverjence_MACD_Line_ (bool)
Diverjence_MACD_Histagram_ (bool)
Diverjence_RSI_ (bool)
Diverjence_Stochastic_ (bool)
Diverjence_volume_ (bool)
Diverjence_CCI_ (bool)
Diverjence_MFI_ (bool)
Diverjence_Momentum_ (bool)
Diverjence_OBV_ (bool)
Diverjence_ADX_ (bool)
MACD (float)
hist_MACD (float)
RSI (float)
volume_ok (float)
Stochastic_K (float)
CCI (float)
MFI (float)
momentum (float)
OBV (float)
adx (float)
x3_P_os(lw, hg, x2_D, x4_D, Diverjence_MACD_Line_, Diverjence_MACD_Histagram_, Diverjence_RSI_, Diverjence_Stochastic_, Diverjence_volume_, Diverjence_CCI_, Diverjence_MFI_, Diverjence_Momentum_, Diverjence_OBV_, Diverjence_ADX_, MACD, hist_MACD, RSI, volume_ok, Stochastic_K, CCI, MFI, momentum, OBV, adx)
Parameters:
lw (int)
hg (int)
x2_D (int)
x4_D (int)
Diverjence_MACD_Line_ (bool)
Diverjence_MACD_Histagram_ (bool)
Diverjence_RSI_ (bool)
Diverjence_Stochastic_ (bool)
Diverjence_volume_ (bool)
Diverjence_CCI_ (bool)
Diverjence_MFI_ (bool)
Diverjence_Momentum_ (bool)
Diverjence_OBV_ (bool)
Diverjence_ADX_ (bool)
MACD (float)
hist_MACD (float)
RSI (float)
volume_ok (float)
Stochastic_K (float)
CCI (float)
MFI (float)
momentum (float)
OBV (float)
adx (float)
Err_test(lw, hg, x1, y1, x2, y2, y_d, start, finish, Err_Rate)
Parameters:
lw (int)
hg (int)
x1 (int)
y1 (float)
x2 (int)
y2 (float)
y_d (float)
start (int)
finish (int)
Err_Rate (float)
divergence_calculation(Feasibility_RD, Feasibility_HD, Feasibility_ED, lw, hg, Source_low, Source_high, x1_P_pr, x3_P_pr, x1_P_os, x3_P_os, x2_P_pr, x4_P_pr, oscillator, Fix_Err_Mid_Point_Pr, Fix_Err_Mid_Point_Os, Err_Rate_permissible_Mid_Line_Pr, Err_Rate_permissible_Mid_Line_Os, Number_of_price_periods_R_H, Permissible_deviation_factor_in_Pr_R_H, Number_of_oscillator_periods_R_H, Permissible_deviation_factor_in_OS_R_H, Number_of_price_periods_E, Permissible_deviation_factor_in_Pr_E, Number_of_oscillator_periods_E, Permissible_deviation_factor_in_OS_E)
Parameters:
Feasibility_RD (bool)
Feasibility_HD (bool)
Feasibility_ED (bool)
lw (int)
hg (int)
Source_low (float)
Source_high (float)
x1_P_pr (int)
x3_P_pr (int)
x1_P_os (int)
x3_P_os (int)
x2_P_pr (int)
x4_P_pr (int)
oscillator (float)
Fix_Err_Mid_Point_Pr (bool)
Fix_Err_Mid_Point_Os (bool)
Err_Rate_permissible_Mid_Line_Pr (float)
Err_Rate_permissible_Mid_Line_Os (float)
Number_of_price_periods_R_H (int)
Permissible_deviation_factor_in_Pr_R_H (float)
Number_of_oscillator_periods_R_H (int)
Permissible_deviation_factor_in_OS_R_H (float)
Number_of_price_periods_E (int)
Permissible_deviation_factor_in_Pr_E (float)
Number_of_oscillator_periods_E (int)
Permissible_deviation_factor_in_OS_E (float)
label_txt(label_ID, zigzag_Indicator_1_, zigzag_Indicator_2_, zigzag_Indicator_3_)
Parameters:
label_ID (string)
zigzag_Indicator_1_ (bool)
zigzag_Indicator_2_ (bool)
zigzag_Indicator_3_ (bool)
delet_scan_item_1(string_, NO_1, GAP)
Parameters:
string_ (string)
NO_1 (int)
GAP (int)
delet_scan_item_2(string_, NO_1, GAP)
Parameters:
string_ (string)
NO_1 (int)
GAP (int)
calculation_Final_total(MS_MN, Scan_zigzag_NO, zigzag_Indicator, zigzag_Indicator_1, zigzag_Indicator_2, zigzag_Indicator_3, LW_hg_P2, LW_hg_P1, lw_1, lw_2, lw_3, hg_1, hg_2, hg_3, lw_hg_D_POINT_ad_Array, lw_hg_D_POINT_id_Array, Array_Regular_MS, Array_Hidden_MS, Array_Exaggerated_MS, Array_Regular_MN, Array_Hidden_MN, Array_Exaggerated_MN)
Parameters:
MS_MN (string)
Scan_zigzag_NO (string)
zigzag_Indicator (bool)
zigzag_Indicator_1 (bool)
zigzag_Indicator_2 (bool)
zigzag_Indicator_3 (bool)
LW_hg_P2 (int)
LW_hg_P1 (int)
lw_1 (int)
lw_2 (int)
lw_3 (int)
hg_1 (int)
hg_2 (int)
hg_3 (int)
lw_hg_D_POINT_ad_Array (array)
lw_hg_D_POINT_id_Array (array)
Array_Regular_MS (array)
Array_Hidden_MS (array)
Array_Exaggerated_MS (array)
Array_Regular_MN (array)
Array_Hidden_MN (array)
Array_Exaggerated_MN (array)
Search_piote_1(array_id_7, scan_no)
Parameters:
array_id_7 (array)
scan_no (int)
Powertrend - Volume Range Filter Strategy [wbburgin]The Powertrend is a range filter that is based off of volume, instead of price. This helps the range filter capture trends more accurately than a price-based range filter, because the range filter will update itself from changes in volume instead of changes in price. In certain scenarios this means that the Powertrend will be more profitable than a normal range filter.
Essentials of the Strategy
This is a breakout strategy which works best on trending assets with high volume and liquidity. It should be used on middle to higher timeframes and can be used on all assets that have volume provided by the data source (stocks, crypto, forex). It is long-only as of now. It can work on lower timeframes if you optimize the strategy filters to make less trades or if your exchange/broker is low/no fees, provided that your exchange/broker has high liquidity and volume.
The strategy enters a long position if the range filter is trending upwards and the price crosses over the upper range band, which signifies a price-volume breakout. The strategy closes the long position if the range filter is trending downwards and the price crosses under the lower range band, which signifies a breakdown. Both these conditions can be altered by the three filter options in the settings. The default trend filter is not alterable because it helps prevent false entries and exits that are against the trend.
Settings
The Length setting is the lookback period for the range smoothing.
The ADX Filter setting enables you to turn on an ADX filter, which will halt entries and exits unless the ADX of your customizable length is above a ADX VWMA of that length.
The Range Supertrend setting creates a supertrend from the top and bottom ranges, which can be used to filter entries and exits. The length is customizable. The filter can show you whether the range is making higher highs and lower lows. Below is an example of the Range Supertrend being used as a filter and plotted on-chart:
The VWMA setting halts entries if they are below a customizable length VWMA.
Both the Range Supertrend and the VWMA can also be plotted separately without actually filtering the strategy, so that you can use them independently if you wish. You can turn off the bar color, the highlighting, and the labels if you wish in the settings. A note about the bar color: if the color changes but the strategy does not signal an exit or entry this means that the crossover was against the trend. In these circumstances it may be indicative of a pullback to enter or exit or to add onto your position.
About the Strategy Results Below
A range filter is normally composed of two components - the range filter itself and a smoothing function. In the development of this script I tested both normal and volume-based varieties of the range filter and the smoothing function:
Tests Performed
Volume-based Range x VWMA smoothing
Price-based Range x VWMA smoothing
Price-based Range x EMA smoothing
Volume-based Range x EMA smoothing (final result)
The highest-performing was a volume-based range filter and a normal EMA-based smoothing function, but that does not mean that this strategy will be profitable - exits are based off of signal reversion so I strongly encourage you to develop your own take profits/stop losses for the strategy if you think it may be a good fit for you. The results below are with a commission value of 0.05% (because I built the strategy first for equities), slippage of 3, so if your exchange/broker has a higher fee schedule, I recommend adding filters and/or moving to higher timeframes for the strategy. Additionally, I used 10% of equity in each trade, while using the Range Supertrend filter (the previous upload was unrealistic because it used 100% of equity - missed a 0, apologies, and added in slippage).
TrendIndicatorsLibrary "TrendIndicators"
This is a library of 'Trend Indicators'.
It aims to facilitate the grouping of this category of indicators, and also offer the customized supply of
the source, not being restricted to just the closing price.
Indicators (this is a work in progress):
1. Absolute DI (Directional Moviment Index) (Difference between DI+ and DI-).
Used in 'DMI Stochastic Extreme' by Barbara Star.
2. DMI
DI_Abs(lengthDI, smoothDI, typeMA, lengthMA)
@description Absolute DI (Directional Moviment Index).
Used in 'DMI Stochastic Extreme' by Barbara Star.
Difference between DI+ and DI-
Parameters:
lengthDI : (int) Length of DI+/DI-
smoothDI : (bool) Sets whether absolute DI should be smoothed
typeMA : (int) Type of moving average of smoothing
lengthMA : (int) Length for moving average of smoothing
Returns: (float) Absolute value of DI
dmi(diLength, adxSmoothing)
@description DMI (Directional Movement Index)
Same as ta.dmi()
Parameters:
diLength : (int) Length of DI+/DI-
adxSmoothing : (int) ADX Smoothing
Returns: Tuple of three DMI series: Positive Directional
Movement (+DI), Negative Directional Movement (-DI) and Average Directional Movement Index (ADX).
dmi(source, diLength, adxSmoothing)
@description DMI (Directional Movement Index)
Customized version of ta.dmi(), with custom source
Parameters:
source : (float) Source for DI+/DI-
diLength : (int) Length of DI+/DI-
adxSmoothing : (int) ADX Smoothing
Returns: Tuple of three DMI series: Positive Directional
Movement (+DI), Negative Directional Movement (-DI) and Average Directional Movement Index (ADX).
Squeeze Momentum MTF [LPWN]//ENGLISH
Squeeze momentum of lazy bear, multiple time frames, It gives you information if the cycles with high temporality momentums are in harmony, by default two more momentums are shown, I prefer to use only one extra, in the options you can change the time frame of the momentums, in addition to the momentums you can add the RSI and ADX, if the momentum look small, you can change the value of general scale to make them bigger, the table gives us information on how the momentums and the adx are, in the options you can set the candles to color according to the harmony of the momentums
// SPANISH
Squeeze momentum de lazy bear, multiple time frames, te da informacion si los ciclos con momentums de temporalidad alta estan en armonia,por defecto se muestran dos momentums mas, yo prefiero usar solo uno extra, en las opcoines puedes cambiar la temporalidad de los momentums, ademas de los momentums puedes agregar el RSI y el ADX, si el momentum se ve pequeño, puedes cambiar el valor de general scale para hacerlos mas grandes, la tabla nos da infomracion de como estan los momentums y el adx, en las opciones puedes poner que las velas se pongan del color de acuerdo a la armonia de los momentums
MACD With Trend Filter: Visual Backtest Module TemplateSample Strategy: MACD Crossover with trend filter options
MA Filter : Price Close Above MA, Search for Buy, Price Close Below MA, Search for Sell
ADX Filter : Take trade only when ADX is above certain treshold
MACD Signal : MACD Cross above signal line while under 0 line indicate Buy Signal
MACD Cross below signal line while above 0 line indicate Sell Signal
-----------------------------
Using Alert Module:
Enable Alert --> Enable TV's alert and plot signal to chart
Alert Type --> Set to take Buy only, Sell only or Both alert
----------------------------
Using Backtest Module:
Enable Backtest --> Enable Backtest simulation
Backtest Type --> Set to take Buy only, Sell only or Both
SL Type -->
ATR : Set SL in ATR times Multiplier below/above entry price
Fixed : Set SL in fixed point below entry point (in 'Dollar'). e.g. for Stocks -> 0.5 equals to 50cent while for EURUSD currency -> 0.005 equal to 50 pips
HiLo Bar : Set SL at highest/lowest wick of previous bar plus/minus Fixed point. e.g. EURUSD HiLo=3 and Fixed Point = 0.0005, buy trade will place SL 5 Pips below lowest of previous 3 bar
SL ATR Period --> Set Lookback Period used for SL's ATR calculation
SL ATR Multi --> Set ATR Multiplier for SL
SL Fixed --> Set Fixed Level for SL (Use when SL Type is either Fixed or HiLo Bar)
SL Bar --> Set Number of previous bar to check for SL placement
TP RR Ratio --> Set TP based on RR multiplier. e.g. 2 means TP level will be twice further from entry point compared to Entry-SL distance.
Notes: The point is for preliminary testing, so it only supports 1 trade at a time and no Trailing Stop
----------------------------
Disclaimer:
This script main objective is to create my personal indicator template so that i just have to modify the indicator module for preliminary testing in future.
Testing Alert Module so i can re-use it as template in future study/indicator
Testing Visual Backtest Module so i can re-use it as template in future study/indicator
i believe using Strategy function is a better approach for this but the entry/exit level seems to be hit n miss (at least for me, still trying to figure what i did wrong)
also, i rather code the strategy in other platform where i can use the more accurate tick data if i want to validate backtest statistics.
My study scripts was built only to test/visualize an idea to see its viability and if it can be used to optimize existing strategy.
credit: ADX code are originally from "ADX and DI" by @BeikabuOyaji although i re-wrote so i can have cleaner read and use RMA instead of SMA
TST Signals & AlertsThis is an unofficial script for strategies tested on Trading Strategy Testing Youtube channel. Over time, most successful strategies will be added with an option to set strategy-specific alerts . TST Signals & Alerts will draw signals on the chart when the entry conditions are met. You can also opt for displaying indicators .
My script is meant for beginners but can be used by veterans too. Just pick one or two strategies, you don't want to flood your chart with conflicting signals. You may want to support your trades with a proper analysis. Is the market trending? Is there a fundament around the corner?
If a new signal occurs when there is still an open position, you are not supposed to take another.
The current version includes MACD and ADX + BB and BB strategies.
MACD strategy:
►Buy, when MACD crosses below the signal line when it is negative. The price must also be above 200 EMA.
►Sell, when MACD crosses above the signal line when it is positive. The price must also be below 200 EMA.
►This strategy was tested on 15-minute charts of EURUSD with reward-to-risk ratio 1,5 and win rate of 61% over 100 trades.
►►►MACD has to be added to your chart separately because it needs a new window. Ticking display indicators will not add MACD to your chart.
►►►MACD was also tested by a different channel I made a script for. You can view the results and the script here:
ADX + BB strategy:
►Buy, when the price is above 200 EMA and ADX becomes higher than 25.
►Sell, when the price is below 200 EMA and ADX becomes higher than 25.
►Stop-loss is either 200 EMA or Bollinger Bands level. Check the channel for more information.
►This strategy was tested on 5-minute charts of EURUSD, USDJPY, AUDUSD with reward-to-risk ratio 1,2 and win rate of 56% over 100 trades in total.
BB strategy:
►Buy, when the price is above 200 EMA and candle's low is below the lower Bollinger Band.
►Sell, when the price is below 200 EMA and candle's high is above the upper Bollinger Band.
►This strategy was tested on 15-minute charts of EURUSD with reward-to-risk ratio 1,5 and win rate of 52% over 100 trades in total.
►►►Due to the relatively low win rate of this strategy, you need to filter out potentially harmful signals with a proper analysis.
Bear in mind that backtesting performance doesn't guarantee future profitability. • Most systematic strategies are not suitable for each timeframe - if you use the different timeframe than the one it was tested on, the result can differ significantly. • You should perform your own backtest to base your trades on more data & to establish confidence in the selected strategy. • This script is not a replacement for proper analysis.
New strategies will be added when I have time. If I see multiple people asking for the same feature, I might agree to release it with a new version. I am not going to add input options in this script, it could come as a separate script though. I am in no way affiliated with the Youtube channel, so if you find the script helpful, shot me a message or send me some TradingView coins >)
If you encounter any bug, you can report it in a message or in comments. Support it with screenshot and relevant information such as a time when it occurred and what options were on etc.
Stochastic Pop and Drop by Jake Bernstein v1 [Bitduke]I found a simple strategy by Jake Bernstein, modified it a little and created a strategy with Risk Management System (SL+TP); After that I test it on the different cryptocurrency pairs.
About the Indicator
Basically it's the strategy of 2 indicators: Stochastic Oscillator to define the bias and Average Directional Index to confirm it.
One again, It uses Stochastic Oscillator to define the trading bias. In particular, the trading bias was deemed bullish when the weekly 14-period Stochastic Oscillator was above some default value (in him paper - 50) and rising and vice versa.
Once the trading bias is established, Steckler used the Average Directional Index (ADX) to define a slowdown in the trend. ADX measures the strength of the trend and a move below 20 signals a weak trend.
Modifications
I didn't implement Average Directional Index (ADX) and test just different sources for data, oscillator periods and different levels in relation to the crypto market.
So, it shows good results with two tight thresholds at 55 and 45 level.
The bar chart below the defining the bullish and bearish periods (green and red) and gives a signal to enter the trade (purple bars).
Backtesting
Backtested on XBTUSD , BTCPERP (FTX) pairs. You may notice it shows good results on 3h timeframe.
Relatively low drawdown
~ 10% (from 2019 to date) FTX
~ 22% (4 years from 2016) Bitmex
I backtested on the different altcoin pairs as well, but the results were just not good.
Relatively good results were shown by some index pairs from the FTX exchange ( FTX:SHITPERP ), but I think there is a few data for backtesting to be asure in them.
Bitmex 3h (2017 - 2020) :
i.imgur.com
FTX 3h (2019 - 2020):
i.imgur.com
Possible Improvements
- Regarding trading algorithm it would be good to check with strategy with ADX somehow. Maybe for the better entries
- As for Risk Management system, it can be improved by adding trailing stop to the strategy.
Link: school.stockcharts.com
RSI Shaded - MTF
Non-repainting multiple time frame RSI with shading of overbought and oversold levels.
Includes option for simple moving average smooth of the RSI (Larry Connors)
Includes option to plot the EMA of the RSI
Related to RSI Shaded .
For other multiple time frame indicators see:
Adaptive ATR-ADX Trend
Fisher Transform MTF
ADX-DI MTF
Laguerre RSI MTF
Target Lock Algo buy and Sell Signal by Amit NamdeoTarget Lock Algo: Professional Buy & Sell Signals
Target Lock Algo is a comprehensive, institutional-grade trading system designed to filter out market noise and provide high-probability entry signals with automated risk management. It combines Trend Flow, Market Structure (SMC), and Volatility Analysis into a single, clean interface.
Key Features
1. Precision Signal Engine
Trend-Following Logic: The core algorithm uses a smoothed Baseline to detect the dominant market flow. Signals are generated only when the trend flips (Green for Bullish, Red for Bearish).
"One-Shot" Execution: To prevent overtrading, the system never issues consecutive signals in the same direction. It forces a complete trend reversal before signaling again.
Whipsaw Protection: A built-in time filter (Min Bars) prevents signals from clustering together during choppy price action.
2. Institutional Filters (The "Safety Net")
200 EMA Major Trend Filter:
Buys are only enabled when price is ABOVE the 200 EMA.
Sells are only enabled when price is BELOW the 200 EMA.
This prevents catching falling knives or buying into a crash.
ADX Chop Filter:
The system actively monitors market strength using the Average Directional Index (ADX).
If the market enters a sideways "Chop Zone" (ADX < 20), all trading signals are hard-blocked.
Visual Aid: These zones can be highlighted with Gray Boxes to warn you to stay out.
3. Automated Risk Management (Target Lock)
When a signal is generated, the algorithm automatically calculates and draws the exact trade parameters on your chart:
⚡ ENTRY: The precise closing price of the signal candle.
🛑 STOP LOSS: Dynamic stop loss calculated using Market Volatility (ATR). If the market is volatile, the stop widens; if calm, it tightens.
🎯 TP 1, 💰 TP 2, 🚀 TP 3: Three take-profit levels calculated based on strict Risk-to-Reward ratios (1.5R, 2.5R, and 3.5R).
4. Premium Visual Interface
Glassmorphism Dashboard: A modern, transparent HUD in the top-right corner displays real-time data:
Current Trend: (Bullish 🟢 / Bearish 🔴)
Market State: (Active 🔥 / Ranging 💤)
Volatility: (Live ATR value)
SMC Overlay: Subtly plots pivot points and market structure breaks in the background to give you institutional context without cluttering the signals.
High-Contrast Design: Signals appear as modern "Neon Buttons," while TP/SL lines use rich, deep colors (Deep Emerald & Crimson) for professional visibility.
How to Trade with Target Lock Algo
Check the Dashboard: Ensure the Market State says "ACTIVE 🔥". If it says "RANGE 💤", be cautious.
Wait for the Button: Look for the "BUY NOW" (Neon Green) or "SELL NOW" (Neon Red) label.
Verify the Trend:
For BUY: Price should be above the white 200 EMA line.
For SELL: Price should be below the white 200 EMA line.
Execute: Enter the trade at the ⚡ ENTRY price.
Manage: Set your Stop Loss at the 🛑 SL line and take partial profits at TP 1 and TP 2. Leave a "runner" for TP 3 if the trend is strong.
Swing trend Pro Buy and Sell Alerts Bu AMit NamdeoThis script, "Swing Pro ", is a complete Trend Following system designed for Swing Trading. It moves away from the complexity of needing all 3 EMAs to align perfectly and instead uses a simpler, more robust logic that filters out noise using a "Base Support" concept.
Here is a breakdown of exactly how it works:
1. The Strategy Logic (The Core)
The script combines Momentum (Crossovers) with Location (Base Support) to generate high-probability signals.
The Trigger (Entry):
It watches for a crossover between the Fast EMA (20) and Medium EMA (50).
Buy Trigger: 20 EMA crosses Above 50 EMA.
Sell Trigger: 20 EMA crosses Below 50 EMA.
The Filter (Location):
Signals are only valid if they happen on the correct side of the Slow EMA (200) (The Blue Line).
For Buys: The price must be ABOVE the Blue 200 EMA. This ensures you are buying in a long-term uptrend where the 200 EMA acts as a floor/support.
For Sells: The price must be BELOW the Blue 200 EMA. This ensures you are selling in a downtrend where the 200 EMA acts as a ceiling/resistance.
ADX Filter:
It checks the ADX (Average Directional Index). If the ADX is below 20 (default), the market is considered "Choppy/Sideways," and the signal is ignored. This saves you from entering false breakouts.
2. Risk Management (Automated)
Once a trade is entered, the script automatically handles the risk math for you based on the ATR (Average True Range).
Stop Loss (SL):
Initial SL: Placed at 1.5x ATR away from the entry price.
Trailing SL: As the price moves in your favor, the Orange SL line automatically moves up (for buys) or down (for sells). It acts as a ratchet—it never moves backwards, locking in your profit.
Take Profits (TP):
TP1: 2.0x ATR (Conservative target).
TP2: 3.5x ATR (Standard swing target).
TP3: 5.0x ATR (Extended trend target).
3. Visuals & Layout
Modern Badges: Bright Green "BUY" and Red "SELL" buttons appear directly on the chart candles.
Dynamic Lines:
Orange Line: Your Trailing Stop Loss. It disappears when the trade is over.
Blue Dashed Lines: Your TP1, TP2, and TP3 targets.
EMA Colors:
Green Line: Fast EMA (20).
Orange Line: Medium EMA (50).
Thick Blue Line: Slow EMA (200 / Base Support).
Bar Coloring: The candles turn bright Green or Red during an active trade to help you instantly see the trend state.
4. How to Trade with It
The Buy Setup:
Wait for the price to be floating above the Thick Blue Line (200 EMA).
Wait for the Green Line (20) to cross up through the Orange Line (50).
A "BUY" badge appears.
Action: Enter the trade. Set your physical Stop Loss at the price shown by the Orange SL line.
The Sell Setup:
Wait for the price to be below the Thick Blue Line (200 EMA).
Wait for the Green Line (20) to cross down through the Orange Line (50).
A "SELL" badge appears.
Action: Enter Short. Follow the Orange SL line down as price drops.
5. Settings Menu
You can customize almost everything in the indicator settings:
Lengths: Change the EMA lengths (e.g., to 9/21/200 if you prefer faster scalping).
Risk: Change the ATR multipliers to make the Stop Loss tighter (e.g., 1.0) or wider (e.g., 2.0).
Visuals: Change the badge sizes (Small/Normal/Large) and colors to fit your dark/light theme.
Alpha Hunter System [MTF + Risk Manager] by Amit NamdeoThis is a comprehensive, "Institutional-Grade" Trend Following System. It is designed not just to give signals, but to filter out bad trades, manage risk automatically, and help you exit at the right time.
Here is a breakdown of exactly how your script works:
1. The Core Engine (High/Low Channel)
The Foundation: Instead of a single line, the script creates a Channel using two Exponential Moving Averages (EMAs).
Green Line: 50 EMA calculated on the Highs of the candles.
Red Line: 50 EMA calculated on the Lows of the candles.
The Logic: This creates a "No-Trade Zone" in the middle.
BUY Signal: Generated when price forcefully breaks above the Green High band.
SELL Signal: Generated when price forcefully breaks below the Red Low band.
2. The "Smart Filters" (Safety Mechanisms)
To prevent false signals (whipsaws), the script checks three separate conditions before showing a Buy or Sell label:
A. Sensitivity Filter (ATR): The price must not just touch the line; it must break it by a specific margin (based on Volatility/ATR). This filters out small wicks.
B. Volume Filter: A breakout is ignored if the Volume is low. The script requires the breakout candle's volume to be higher than the recent average. This ensures "Smart Money" supports the move.
C. Sideways Filter (ADX): Uses the Average Directional Index (ADX). If the trend is weak (ADX < 20), the channel turns Gray and blocks all signals. This saves you from trading in choppy, flat markets.
D. Multi-Timeframe (MTF) Consensus: This is the "60% Rule." The script secretly checks the trend on the 5m, 15m, 1H, 4H, and Daily charts. It only allows a signal if the majority of these timeframes agree with the direction.
3. Automatic Risk Management
This feature automates the math that professional traders usually do in Excel:
Dynamic Stop Loss (SL):
On a Buy, the SL is set to the Red (Low) Band.
On a Sell, the SL is set to the Green (High) Band.
Why? This adapts the SL to the current market volatility.
Take Profit Targets (TP):
It calculates your Risk (Entry - SL).
TP1: 1.5x Risk.
TP2: 2.5x Risk.
TP3: 4.0x Risk.
Visuals: It draws these lines on the chart immediately when a signal appears, so you know exactly where to place your orders.
4. Trailing Stop (The Purple Line)
What it is: A dynamic Purple Line that appears behind the candles.
How it works: It acts like a "Chandelier Exit."
As price moves in your favor, the line moves up to lock in profit.
It never moves backward.
Exit Rule: If a candle closes across this purple line, the trend is likely over, and you should exit.
Live Label: A label follows the line showing the exact price (e.g., "Trail SL: 1950.2") so you can update your order easily.
5. Alerts & Dashboard
Dashboard (Top Right): A live status panel showing:
Current Trend (Bullish/Bearish/Sideways).
MTF Consensus (Are the other timeframes agreeing?).
Volume Status (Pass/Fail).
Alerts: You can set phone/desktop notifications for:
Entries: Buy/Sell.
Targets: TP1, TP2, TP3 Hit.
Safety: Trailing Stop Hit (Exit trade).
Summary of Visual Colors
🟢 Green Channel: Bullish Trend (Look for Buys).
🔴 Red Channel: Bearish Trend (Look for Sells).
⚪ Gray Channel: Sideways Market (Do Not Trade).
🟣 Purple Line: Your Trailing Stop Loss.
Filtered Percentile OscillatorThe Filtered Percentile Oscillator is a new trend following tool that uses trend strength for filtering. Noisy at times - but do not underrate it, this tool has great potential. :)
Benefits:
- Very high speed
- Adaptive behaviour filtering excess noise
- High performance on CRYPTO:SUIUSD
- Plotting for better visualization
The Idea
Get a simple indicator that is combined with trend strength for filtering. The best for this was the Percentile. I used it on the classic source to keep it simple, but if anybody wants feel free to change it with/without ChatGPT.
How it works:
Calculate the Percentile of the source.
Calculate the ADX & the Percentile of ADX.
Then we have two filter conditions:
If ADX Percentile+ Absolute Percentile of source > Sum Filter Treshhold is not true, both the Long & Short conditions are automaticly false.
If ADX Percentile > Filter Treshhold it will make the treshholds for the Percentile lower, while if it is below the filter treshhold, it will put the treshholds higher to filter excess noise further.
Enjoy Gs!
EDUVEST Lorentzian ClassificationEDUVEST Lorentzian Classification - Machine Learning Signal Detection
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█ ORIGINALITY
This indicator enhances the original Lorentzian Classification concept by jdehorty with EduVest's visual modifications and alert system integration. The core innovation is using Lorentzian distance instead of Euclidean distance for k-NN classification, providing more robust pattern recognition in financial markets.
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█ WHAT IT DOES
- Generates BUY/SELL signals using machine learning classification
- Displays kernel regression estimate for trend visualization
- Shows prediction values on each bar
- Provides trade statistics (Win Rate, W/L Ratio)
- Includes multiple filter options (Volatility, Regime, ADX, EMA, SMA)
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█ HOW IT WORKS
【Lorentzian Distance Calculation】
Unlike Euclidean distance, Lorentzian distance uses logarithmic transformation:
d = Σ log(1 + |xi - yi|)
This provides:
- Better handling of outliers
- More stable distance measurements
- Reduced sensitivity to extreme values
【Feature Engineering】
The classifier uses up to 5 configurable features:
- RSI (Relative Strength Index)
- WT (WaveTrend)
- CCI (Commodity Channel Index)
- ADX (Average Directional Index)
Each feature is normalized using the n_rsi, n_wt, n_cci, or n_adx functions.
【k-Nearest Neighbors Classification】
1. Calculate Lorentzian distance between current bar and historical bars
2. Find k nearest neighbors (default: 8)
3. Sum predictions from neighbors
4. Generate signal based on prediction sum (>0 = Long, <0 = Short)
【Kernel Regression】
Uses Rational Quadratic kernel for smooth trend estimation:
- Lookback Window: 8
- Relative Weighting: 8
- Regression Level: 25
【Filters】
- Volatility Filter: Filters signals during extreme volatility
- Regime Filter: Identifies market regime using threshold
- ADX Filter: Confirms trend strength
- EMA/SMA Filter: Trend direction confirmation
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 15M, 1H, 4H, Daily
- Neighbors Count: 8 (default)
- Feature Count: 5 for comprehensive analysis
【Signal Interpretation】
- Green BUY label: Long entry signal
- Red SELL label: Short entry signal
- Bar colors: Green (bullish) / Red (bearish) prediction strength
【Trade Statistics Panel】
- Winrate: Historical win percentage
- Trades: Total (Wins|Losses)
- WL Ratio: Win/Loss ratio
- Early Signal Flips: Premature signal changes
【Filter Recommendations】
- Enable Volatility Filter for ranging markets
- Enable Regime Filter for trend confirmation
- Use EMA Filter (200) for higher timeframes
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█ CREDITS
Original Lorentzian Classification concept and MLExtensions library by jdehorty.
Enhanced with visual modifications and alert integration by EduVest.
License: Mozilla Public License 2.0
WoAlgo Premium v3.0
WoAlgo Premium v3.0 - Smart Money Analysis
Overview
** WoAlgo Premium v3.0 ** is an advanced technical analysis indicator designed for educational purposes. This tool combines Smart Money Concepts with multi-factor confluence analysis to help traders identify potential market opportunities across multiple timeframes.
The indicator integrates market structure analysis, order flow concepts, and technical momentum indicators into a comprehensive dashboard system. It is designed to assist traders in understanding institutional trading patterns and market dynamics through visual analysis tools.
### What It Does
This indicator provides:
**1. Smart Money Concepts Analysis**
- Market structure identification (Break of Structure and Change of Character patterns)
- Order block detection with volume confirmation
- Fair value gap recognition
- Liquidity zone mapping (equal highs and lows)
- Premium and discount zone calculations
**2. Multi-Factor Confluence Scoring**
The indicator calculates a proprietary confluence score (0-100) based on five key components:
- Price action analysis (30% weight)
- Volume confirmation (20% weight)
- Momentum indicators (25% weight)
- Trend strength measurement (15% weight)
- Money flow analysis (10% weight)
**3. Multi-Timeframe Analysis**
- Scans 5 different timeframes (5M, 15M, 1H, 4H, Daily)
- Calculates alignment percentage across timeframes
- Displays trend and structure status for each period
**4. Visual Dashboard System**
- Comprehensive main dashboard with 13 metrics
- Real-time screener table with 10 data columns
- Multi-timeframe scanner
- Performance tracking panel
### How It Works
**Market Structure Detection**
The indicator identifies key structural changes in price action:
- **BOS (Break of Structure)**: Indicates trend continuation when price breaks previous swing points
- **CHoCH (Change of Character)**: Signals potential trend reversal when market structure shifts
**Order Block Identification**
Order blocks are detected when:
- Significant volume appears at swing points
- Price shows strong directional movement from these levels
- Enhanced detection with extreme volume confirmation (OB++ markers)
**Fair Value Gap Recognition**
Gaps between candles are identified when:
- Price leaves inefficiencies in the market
- Three consecutive candles create a gap pattern
- Gap size exceeds minimum threshold based on ATR
**Confluence Calculation**
The system evaluates multiple technical factors:
1. **Price Position**: Relative to moving averages (EMA 20, 50, 200)
2. **Volume Analysis**: Standard deviation-based volume spikes
3. **Momentum**: RSI, MACD, Stochastic indicators
4. **Trend Strength**: ADX measurements
5. **Money Flow**: MFI indicator readings
Each factor contributes weighted points to create an overall confluence score that helps assess signal strength.
### Signal Types
**Confirmation Signals (▲ / ▼)**
Generated when:
- EMA crossovers occur (20/50 cross)
- Volume confirmation is present
- RSI is in appropriate zone
- Confluence score exceeds 50%
**Strong Signals (▲+ / ▼+)**
Higher-confidence signals requiring:
- Confluence score above 70%
- Extreme volume confirmation
- Alignment with 200 EMA trend
- MACD confirmation
- Bullish or bearish market structure
**Contrarian Signals (⚡)**
Reversal indicators appearing when:
- RSI reaches extreme levels (<30 or >70)
- Stochastic shows oversold/overbought conditions
- Price touches Bollinger Band extremes
- Potential divergence patterns emerge
**Reversal Zones**
Visual boxes highlighting areas where:
- Market structure conflicts with momentum
- High probability of directional change
- Key support/resistance levels interact
**Smart Trail**
Dynamic stop-loss indicator that:
- Adjusts based on ATR (Average True Range)
- Follows trend direction
- Updates automatically as price moves
- Provides risk management reference points
### Dashboard Components
**Main Dashboard (13 Metrics)**
1. **Confluence Score**: Current bull/bear percentage (0-100)
2. **Market Regime**: Trend classification (Strong Up/Down, Range, Squeeze)
3. **Signal Status**: Active buy/sell signal indication
4. **Structure State**: Current market structure (Bullish/Bearish/Neutral)
5. **Trend Strength**: ADX-based measurement
6. **RSI Level**: Momentum indicator with overbought/oversold zones
7. **MACD Direction**: Trend momentum confirmation
8. **Money Flow Index**: Smart money sentiment
9. **Volume Status**: Current volume relative to average
10. **Volatility Rating**: ATR percentage measurement
11. **ATR Value**: Average true range for position sizing
12. **MTF Alignment**: Multi-timeframe agreement percentage
**Screener Table (10 Columns)**
- Current symbol and timeframe
- Real-time price and percentage change
- Quality rating (star system)
- Active signal type
- Smart trail status
- Market structure state
- MACD direction
- Trend strength percentage
- Bollinger Band squeeze detection
**MTF Scanner (5 Timeframes)**
Displays for each timeframe:
- Trend direction indicator
- Market structure classification
- Visual confirmation with color coding
**Performance Metrics**
- Win rate percentage (simplified calculation)
- Total signals generated
- Current confluence score
- MTF alignment status
- Volatility level
### Settings and Customization
**Preset Styles**
Choose from predefined configurations:
- **Conservative**: Fewer, higher-quality signals
- **Moderate**: Balanced approach (recommended)
- **Aggressive**: More frequent signals
- **Scalper**: Short-term focused
- **Swing**: Longer-term oriented
- **Custom**: Full manual control
**Smart Money Concepts Controls**
- Toggle each feature independently
- Adjust swing length (3-50 periods)
- Enable/disable internal structure
- Control order block display
- Manage breaker block visibility
- Show/hide fair value gaps
- Display liquidity zones
- Premium/discount zone visualization
**Signal Configuration**
- Enable/disable confirmation signals
- Toggle strong signal markers
- Control contrarian signal display
- Show/hide reversal zones
- Smart trail activation
- Sensitivity adjustment (5-50)
**Visual Customization**
- Moving average display options
- MA period adjustments (Fast: 20, Slow: 50, Trend: 200)
- Support/resistance line toggle
- Dynamic S/R lookback period
- Candle coloring based on trend
- Color scheme customization
- Dashboard size options (Small/Normal/Large)
- Position placement (4 corners)
### How to Use
**Step 1: Initial Setup**
1. Add indicator to chart
2. Select appropriate preset or use Custom
3. Adjust timeframe to match trading style
4. Configure dashboard visibility preferences
**Step 2: Analysis Workflow**
1. Check MTF Scanner for timeframe alignment
2. Review Main Dashboard confluence score
3. Observe Market Regime classification
4. Identify active signals on chart
5. Confirm with Smart Money Concepts (order blocks, FVG, structure)
**Step 3: Trade Consideration**
Strong signals (▲+ / ▼+) require:
- Confluence score >70%
- MTF alignment >60%
- Confirmation from multiple dashboard metrics
- Support from Smart Money Concepts
- Appropriate volume levels
**Step 4: Risk Management**
- Use Smart Trail as dynamic stop-loss reference
- Consider ATR for position sizing
- Monitor volatility rating
- Respect support/resistance levels
- Combine with personal risk parameters
### Best Practices
**For Scalping (1M-5M timeframes)**
- Use Scalper preset
- Reduce swing length to 5-7
- Focus on strong signals only
- Monitor MTF alignment closely
- Quick entries near order blocks
**For Intraday Trading (15M-1H timeframes)**
- Use Moderate preset (recommended)
- Default swing length (10)
- Combine confirmation and strong signals
- Check MTF scanner before entry
- Use fair value gaps for entries
**For Swing Trading (4H-D timeframes)**
- Use Swing preset
- Increase swing length to 15-20
- Focus on strong signals
- Require high MTF alignment
- Patient approach with major structure levels
### Technical Specifications
**Indicators Used**
- Exponential Moving Averages (20, 50, 200)
- Hull Moving Average
- Relative Strength Index (14)
- MACD (12, 26, 9)
- Money Flow Index (14)
- Stochastic Oscillator (14, 3)
- ADX / DMI (14)
- Bollinger Bands (20, 2)
- ATR (14)
- Volume Analysis (SMA 20 with standard deviation)
**Calculation Methods**
- Swing detection using pivot high/low functions
- Volume confirmation via statistical analysis
- Multi-factor scoring with weighted components
- Dynamic support/resistance using highest/lowest functions
- Real-time MTF data via security() function
### Limitations and Considerations
**Important Notes**
1. This indicator is designed for educational and analytical purposes only
2. Historical performance does not guarantee future results
3. Signals should be confirmed with additional analysis
4. Market conditions vary and affect indicator performance
5. Not all signals will be profitable
6. Risk management is essential for all trading
**Known Limitations**
- Confluence scoring is algorithmic and not predictive
- MTF analysis requires sufficient historical data
- Effectiveness varies across different market conditions
- Sideways markets may produce conflicting signals
- High volatility can affect signal reliability
- Backtesting results shown are simplified calculations
**Not Suitable For**
- Automated trading without human oversight
- Sole basis for trading decisions
- Guaranteed profit expectations
- Inexperienced traders without proper education
- Trading without risk management plans
### Market Applicability
**Effective On**
- Trending markets (any direction)
- Clear structure formation periods
- Liquid instruments with consistent volume
- Multiple asset classes (forex, stocks, crypto, commodities)
- Various timeframes with appropriate settings
**Less Effective During**
- Extended ranging/choppy conditions
- Extremely low volume periods
- Major news events causing gaps
- Early market open with high spread
- Illiquid instruments with erratic price action
### Risk Disclaimer
**⚠️ IMPORTANT NOTICE**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment recommendations, or trading signals.
**Key Risk Factors:**
- Trading financial instruments involves substantial risk of loss
- Past performance does not indicate future results
- No indicator can predict market movements with certainty
- Users should conduct independent research and analysis
- Professional financial advice should be sought when appropriate
- Risk management and position sizing are critical to successful trading
- Users are solely responsible for their trading decisions
**Responsible Usage:**
- Combine with comprehensive market analysis
- Use appropriate stop-loss orders
- Never risk more than you can afford to lose
- Maintain realistic expectations
- Continue education on technical analysis principles
- Test thoroughly on demo accounts before live trading
- Understand all indicator features before using
### Educational Resources
**Understanding Smart Money Concepts**
Smart Money Concepts analyze how institutional traders and large market participants operate. Key principles include:
- Institutional order flow patterns
- Market structure changes
- Liquidity manipulation
- Supply and demand imbalances
- Order block formations
**Multi-Timeframe Analysis Theory**
Analyzing multiple timeframes helps:
- Identify overall market direction
- Improve entry timing
- Confirm trend strength
- Recognize consolidation periods
- Reduce conflicting signals
**Confluence Trading Approach**
Using multiple confirming factors:
- Increases signal reliability
- Reduces false signals
- Provides conviction for trades
- Helps with position sizing
- Improves risk-reward ratios
### Version History
**v3.0 (Current)**
- Multi-factor confluence scoring system
- Complete Smart Money Concepts implementation
- Real-time multi-timeframe analysis
- Four professional dashboard panels
- Enhanced order block detection
- Breaker block identification
- Premium/discount zone calculations
- Smart trail stop-loss system
- Customizable preset configurations
- Performance tracking metrics
**Development Philosophy**
This indicator was developed with focus on:
- Educational value for traders
- Transparent methodology
- Comprehensive feature set
- User-friendly interface
- Flexible customization options
### Technical Support
**For Questions About:**
- Indicator functionality
- Parameter optimization
- Signal interpretation
- Dashboard metrics
- Best practice recommendations
Please use TradingView's comment section below. The developer monitors comments and provides assistance to users learning to use the indicator effectively.
### Acknowledgments
This indicator implements concepts from:
- Smart Money Concepts trading methodology
- Multi-timeframe analysis techniques
- Technical indicator theory
- Market structure analysis principles
- Institutional order flow concepts
All implementations are original code and calculations based on established technical analysis principles.
---
## ADDITIONAL INFORMATION SECTION
**Category**: Indicators
**Type**: Market Structure / Multi-Timeframe Analysis
**Complexity**: Intermediate to Advanced
**Open Source**: Code visible for transparency and education
**Pine Script Version**: v6
**Chart Overlay**: Yes
**Maximum Objects**: 500 boxes, 500 lines, 500 labels
Adaptive Kinetic Trend [AKT] Pure MathTitolo: Adaptive Kinetic Trend - Pure Math
Descrizione:
Overview The Adaptive Kinetic Trend is a custom-built trend following system designed to filter noise and adapt to changing market volatility. Unlike standard indicators that rely on a static calculation, the AKT introduces a "Kinetic" component that adjusts the trend baseline according to price velocity (Momentum) and market intensity (ADX).
The "Pure Math" Implementation To ensure maximum stability and prevent potential discrepancies associated with data gaps or library updates, this script features a 100% manual mathematical library. It does not use TradingView's native ta.* functions for its core logic. Every calculation—including Wilder's Smoothing (RMA), Weighted Moving Averages (WMA), and True Range (TR)—is computed explicitly within the code from raw price data. This provides a transparent look at how the signals are derived.
Key Features
1. Kinetic Center Line The backbone of the indicator is an adaptive moving average that shifts its sensitivity based on a manually calculated RSI (Velocity).
High Velocity: The line reacts faster to capture breakout momentum.
Low Velocity: The line smooths out to prevent whipsaws during corrections.
2. Dynamic Volatility Expansion Using a custom ADX calculation (Intensity), the bands automatically expand during high-volatility events. This helps keep positions open during strong trends where standard ATR stops might be triggered prematurely.
3. Visual Filters (Color Logic) The script uses a strict color-coding system to guide analysis:
🟢 Green / 🔴 Red (Trend): The market is in a validated trend phase with sufficient intensity.
⚪ Gray (Choppy Filter): When Intensity falls below the threshold (default 20), the bars turn gray and signals are suppressed. This filters out low-probability ranging markets.
🟡 Yellow (Proximity Zone): When price trades within 0.5 ATR of the trend line, bars turn yellow. This indicates price is testing the trend structure.
4. Smart Pullback Signals (PB) Small triangles labeled "PB" appear when the price retraces to test the trend line.
Visual Intensity: The signals feature adaptive transparency. They appear bright during strong trends (High Probability) and faded/transparent during choppy conditions (Lower Probability), helping users filter signal quality visually.
5. Live Dashboard A data panel provides real-time metrics:
Trend Status: BULL, BEAR, or RANGE.
Intensity: Raw ADX value to gauge trend strength.
Dist ATR: The precise distance from the close price to the stop-loss line, measured in ATR multiples.
How to Use
Trend Analysis: Identify the main direction via Green/Red candles.
Filtering: Use the Gray bars to identify periods of low volatility/consolidation where trend strategies typically fail.
Re-entries: Use PB triangles to identify potential continuation points within an existing trend.
Risk Monitoring: Use Yellow bars (Proximity) to monitor price action near the invalidation level.
Disclaimer This script is intended for technical analysis and educational purposes only. It provides a visual representation of market trends based on historical data and does not guarantee future performance.
varenleongv1🔑 Core Features
1️⃣ Higher Timeframe Trend Bias
The indicator uses a higher-timeframe EMA to define the overall market direction.
This helps filter out lower-timeframe noise and keeps trades aligned with the bigger picture.
2️⃣ Local Trend Confirmation
Two EMAs (Fast & Mid) with slope analysis confirm short-term momentum.
Trades are only considered when price structure and momentum agree with the higher-timeframe bias.
3️⃣ Market Structure Detection
The indicator automatically identifies:
Higher Highs & Higher Lows (uptrend)
Lower Highs & Lower Lows (downtrend)
This structure-based logic avoids lag and provides realistic trend confirmation instead of reacting to every candle.
4️⃣ Automatic Trendline Drawing
Confirmed swing highs and lows are used to draw:
Rising support lines in uptrends
Falling resistance lines in downtrends
Trendlines are based on confirmed pivots, meaning they do not repaint once formed.
5️⃣ ADX Chop Filter (Optional)
An optional ADX filter helps identify sideways or low-momentum markets.
When ADX is below the chosen threshold, the indicator will classify conditions as chop / no-trend, helping prevent forced trades.
6️⃣ Clear Visual Feedback
Background color highlights the current market state:
Green = Uptrend
Red = Downtrend
Grey = No Trend / Chop
EMAs and trendlines are plotted directly on price for clarity.
MLExtensionsLibrary "MLExtensions"
A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space.
normalizeDeriv(src, quadraticMeanLength)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the first-order derivative for price).
quadraticMeanLength (int) : The length of the quadratic mean (RMS).
Returns: nDeriv The normalized derivative of the input series.
normalize(src, min, max)
Rescales a source value with an unbounded range to a target range.
Parameters:
src (float) : The input series
min (float) : The minimum value of the unbounded range
max (float) : The maximum value of the unbounded range
Returns: The normalized series
rescale(src, oldMin, oldMax, newMin, newMax)
Rescales a source value with a bounded range to anther bounded range
Parameters:
src (float) : The input series
oldMin (float) : The minimum value of the range to rescale from
oldMax (float) : The maximum value of the range to rescale from
newMin (float) : The minimum value of the range to rescale to
newMax (float) : The maximum value of the range to rescale to
Returns: The rescaled series
getColorShades(color)
Creates an array of colors with varying shades of the input color
Parameters:
color (color) : The color to create shades of
Returns: An array of colors with varying shades of the input color
getPredictionColor(prediction, neighborsCount, shadesArr)
Determines the color shade based on prediction percentile
Parameters:
prediction (float) : Value of the prediction
neighborsCount (int) : The number of neighbors used in a nearest neighbors classification
shadesArr (array) : An array of colors with varying shades of the input color
Returns: shade Color shade based on prediction percentile
color_green(prediction)
Assigns varying shades of the color green based on the KNN classification
Parameters:
prediction (float) : Value (int|float) of the prediction
Returns: color
color_red(prediction)
Assigns varying shades of the color red based on the KNN classification
Parameters:
prediction (float) : Value of the prediction
Returns: color
tanh(src)
Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.
Parameters:
src (float) : The input series (i.e., the normalized derivative).
Returns: tanh The hyperbolic tangent of the input series.
dualPoleFilter(src, lookback)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the hyperbolic tangent).
lookback (int) : The lookback window for the smoothing.
Returns: filter The smoothed hyperbolic tangent of the input series.
tanhTransform(src, smoothingFrequency, quadraticMeanLength)
Returns the tanh transform of the input series.
Parameters:
src (float) : The input series (i.e., the result of the tanh calculation).
smoothingFrequency (int)
quadraticMeanLength (int)
Returns: signal The smoothed hyperbolic tangent transform of the input series.
n_rsi(src, n1, n2)
Returns the normalized RSI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the RSI calculation).
n1 (simple int) : The length of the RSI.
n2 (simple int) : The smoothing length of the RSI.
Returns: signal The normalized RSI.
n_cci(src, n1, n2)
Returns the normalized CCI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the CCI calculation).
n1 (simple int) : The length of the CCI.
n2 (simple int) : The smoothing length of the CCI.
Returns: signal The normalized CCI.
n_wt(src, n1, n2)
Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).
n1 (simple int)
n2 (simple int)
Returns: signal The normalized WaveTrend Classic series.
n_adx(highSrc, lowSrc, closeSrc, n1)
Returns the normalized ADX ideal for use in ML algorithms.
Parameters:
highSrc (float) : The input series for the high price.
lowSrc (float) : The input series for the low price.
closeSrc (float) : The input series for the close price.
n1 (simple int) : The length of the ADX.
regime_filter(src, threshold, useRegimeFilter)
Parameters:
src (float)
threshold (float)
useRegimeFilter (bool)
filter_adx(src, length, adxThreshold, useAdxFilter)
filter_adx
Parameters:
src (float) : The source series.
length (simple int) : The length of the ADX.
adxThreshold (int) : The ADX threshold.
useAdxFilter (bool) : Whether to use the ADX filter.
Returns: The ADX.
filter_volatility(minLength, maxLength, useVolatilityFilter)
filter_volatility
Parameters:
minLength (simple int) : The minimum length of the ATR.
maxLength (simple int) : The maximum length of the ATR.
useVolatilityFilter (bool) : Whether to use the volatility filter.
Returns: Boolean indicating whether or not to let the signal pass through the filter.
backtest(high, low, open, startLongTrade, endLongTrade, startShortTrade, endShortTrade, isEarlySignalFlip, maxBarsBackIndex, thisBarIndex, src, useWorstCase)
Performs a basic backtest using the specified parameters and conditions.
Parameters:
high (float) : The input series for the high price.
low (float) : The input series for the low price.
open (float) : The input series for the open price.
startLongTrade (bool) : The series of conditions that indicate the start of a long trade.
endLongTrade (bool) : The series of conditions that indicate the end of a long trade.
startShortTrade (bool) : The series of conditions that indicate the start of a short trade.
endShortTrade (bool) : The series of conditions that indicate the end of a short trade.
isEarlySignalFlip (bool) : Whether or not the signal flip is early.
maxBarsBackIndex (int) : The maximum number of bars to go back in the backtest.
thisBarIndex (int) : The current bar index.
src (float) : The source series.
useWorstCase (bool) : Whether to use the worst case scenario for the backtest.
Returns: A tuple containing backtest values
init_table()
init_table()
Returns: tbl The backtest results.
update_table(tbl, tradeStatsHeader, totalTrades, totalWins, totalLosses, winLossRatio, winrate, earlySignalFlips)
update_table(tbl, tradeStats)
Parameters:
tbl (table) : The backtest results table.
tradeStatsHeader (string) : The trade stats header.
totalTrades (float) : The total number of trades.
totalWins (float) : The total number of wins.
totalLosses (float) : The total number of losses.
winLossRatio (float) : The win loss ratio.
winrate (float) : The winrate.
earlySignalFlips (float) : The total number of early signal flips.
Returns: Updated backtest results table.
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
FCPO MASTER v6 – Sideway + Breakout + OB + FVG (TUPLE SAFE)TL;DR cepat
1. Gunakan M5 untuk entry & OB/FVG confirmation.
2. Gunakan M15 untuk confirm trend/false breakout.
3. Gunakan H1 untuk bias arah (overall market).
4. Entry hanya bila signal + OB/FVG/candle rejection (script buatkan).
5. SL 5–8 tick, TP 10–25 tick ikut setup (sideway vs breakout).
6. Follow checklist setiap trade — jangan lompat.
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Setup awal (1–2 min)
1. Pasang script FCPO Sideway MASTER – OB + Imbalance + Confirmation di TradingView.
2. Timeframes: buka M5, M15, H1 (susun 3 chart atau 1 chart multi-timeframe).
3. Input default: ATR14, Breakout Buffer 5 tick, RangeLen 20, ADX14, TP12, SL8. (Kau boleh tweak nanti).
4. Aktifkan alerts pada BUY Confirm / SELL Confirm / Sideway Buy / Sideway Sell.
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Step-by-step trading process
1) Mulakan dengan H1 — tentukan bias HTF
• Lihat H1 untuk jawapan: Trend Up / Down / Sideway.
• Rule ringkas:
o ADX H1 > 20 + price above H1 EMA → bias Bull
o ADX H1 > 20 + price below H1 EMA → bias Bear
o ADX H1 < 20 → market HTF sideway (no strong bias)
Kenapa: H1 bagi kau idea “kalau breakout pada M5, patut follow atau tolak”.
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2) Pergi ke M15 — confirm trend & valid breakout
• M15 kena setuju dengan idea breakout.
o Untuk strong breakout: M15 kena tunjuk candle close di atas/bawah range + volume naik.
o Kalau M5 breakout tapi M15 tak setuju (M15 masih sideway) → treat as fakeout. Jangan masuk.
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3) M5 — cari entry & confirmation (OB/FVG + candle)
• M5 adalah tempat kau buat keputusan masuk.
• Tunggu script keluarkan Sideway Buy/Sell atau Breakout Buy/Sell.
• CONFIRM entry mesti ada sekurang-kurangnya 1 dari:
o Bull/Bear Order Block searah signal (script detect).
o FVG / Imbalance zone dipenuhi & price retest.
o Candle rejection (pinbar / bearish/bullish engulfing) pada zone.
Jika tiada confirmation → no trade.
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4) Checklist sebelum tekan Buy/Sell (MUST)
• H1 bias tidak melawan trade (prefer sama arah).
• M15 confirm breakout / trend or neutral.
• Script keluarkan signal (sideway or breakout).
• OB or FVG atau candle rejection ada.
• ATR kenaikan jika breakout (untuk breakout trade).
• Volume spike jika breakout.
• Risk:SL <= 2% akaun (position sizing).
Kalau semua ticked → boleh entry.
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5) Setting SL / TP & position sizing
• Sideway (scalp): SL = 5–8 tick, TP = 8–12 tick.
• Breakout (trend): SL = 8–12 tick, TP = 15–25+ tick (trail later).
• Position sizing: Risk per trade 1–2%.
o Lot size = (Account Risk RM × 1 tick value) / (SL ticks × tickValue) — (kalau kau gunakan fixed tick value, adjust ikut lot).
(Script tunjuk SL & TP label — follow itu.)
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6) Entry types
• A. Sideway Reversal (M5)
o Signal: Sideway Buy / Sideway Sell
o Confirm: OB/FVG or rejection candle at range bottom/top
o Trade: scalp target 8–12 tick, tight SL 5–8 tick
• B. Breakout (M5 entry, M15 confirm)
o Signal: Breakout Buy/Sell (Strong)
o Confirm: ATR expanding + volume spike + M15 alignment
o Trade: trend follow, TP 15–25 tick, trailing stop active
• C. Retest Entry
o Breakout happens, price returns to retest range / OB / FVG → wait for rejection candle then enter. Safer.
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7) Trailing & exit rules
• Jika useTrail = true script plots trailing stop (ATR × multiplier).
• Exit rules:
1. Hit TP → close.
2. Hit SL → close.
3. If trailing stop hit → close.
4. If opposing confirmed signal muncul (e.g., SELL confirm while long) → consider close early.
5. If H1 bias flips strongly vs trade → tighten stop or close.
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8) Multiple signals & scaling
• Never add to losing position (no averaging down).
• If want scale-in on confirmed trend: add 1 partial size after price moves +10–12 tick in favor and shows continuation candle + no bearish OB/FVG.
• Keep aggregated risk within your max (2–3%).
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9) Example trade walkthrough (concrete)
• RangeHigh = 4065, RangeLow = 4035 (contoh).
• Market sideway M5.
Case A — Sideway Sell:
1. Price touches 4064–4065, script shows sidewaySell.
2. Lihat OB: ada bear OB zone di 4062–4066 → confirm.
3. Candle rejection (bearish pinbar) muncul → enter SELL M5.
4. Set SL = 5 tick above rangeHigh = 4070, TP = 10 tick → 4055.
5. Trail jika price turun > 8 tick: aktifkan trailing.
6. Close at TP or trail/SL.
Case B — Breakout Buy:
1. Price closes above 4065 + 5 tick buffer = 4070 on M5. Script shows trueBreakUp.
2. M15 shows candle close above M15 resistance + volume spike → confirm.
3. Enter BUY, SL = 8 tick below entry, TP initial 20 tick, trail with ATR×1.5.
4. Move stop to breakeven after +10 tick, scale out half at +12 tick, leave rest to trail.
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10) Journal & review
• Semua trade: record entry time, TF, reason (which confirmations), SL/TP, result, lesson.
• Weekly review: check which confirmation worked best (OB vs FVG vs candle) and tweak settings.
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11) Tweaks / optimisations cepat
• Jika terlalu banyak false sideway signals → kurangkan touchDist ke 2 tick.
• Kalau fakeout breakout banyak → tambah tickBuf ke 6–8.
• Nak lebih konservatif → cuma trade breakout yang juga setuju M15.
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12) Alerts & execution (practical)
• Pasang alert pada BUY Confirm / SELL Confirm (script).
• Kalau kau guna broker yang support one-click order, siap sediakan template order (SL/TP default).
• Kalau manual, bila alert masuk: buka M5, cepat confirm OB/FVG & candle rejection → entry.
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Quick reference table (handy)
• TF utama entry: M5
• Confirm mid-TF: M15
• Bias HTF: H1
• Sideway SL/TP: SL 5–8, TP 8–12
• Breakout SL/TP: SL 8–12, TP 15–25+
• Mandatory confirmation: (Script signal) + (OB or FVG or candle)
DarkPool FlowDarkPool Flow is a professional-grade technical analysis tool designed to align retail traders with the dominant "smart money" flow. Unlike standard moving average crossovers that often generate false signals during consolidation, this script employs a multi-layered filtering engine to isolate high-probability trends.
The core philosophy of this indicator is that Trends are fractal. A sustainable move on a lower timeframe must be supported by momentum on a higher timeframe. By comparing a "Fast Signal Trend" against a "Slow Anchor Trend" (e.g., Daily vs. Weekly), the script identifies the market bias used by institutional algorithms.
This edition features a Smart Recovery Engine, ensuring that valid trends are not missed simply because momentum started slowly, and a Dynamic Cloud that visually represents the strength of the trend spread.
Key Features
1. Auto-Adaptive Timeframe Logic
The script eliminates the guesswork of Multi-Timeframe (MTF) selection. By enabling "Auto-Adapt," the indicator detects your current chart timeframe and automatically maps it to the mathematically correct institutional pairings:
Scalping (<15m): Uses 15-Minute Trend vs. 1-Hour Anchor.
Day Trading (15m - 1H): Uses 4-Hour Trend vs. Daily Anchor.
Swing Trading (4H - Daily): Uses Daily Trend vs. Weekly Anchor (The classic "Golden" setup).
Investing (Weekly): Uses 21-Week EMA vs. 50-Week SMA (Bull Market Support Band logic).
2. Smart Recovery Signal Engine
Standard crossover scripts often miss major moves if the specific breakout candle has low volume or weak ADX. This script utilizes a state-machine logic that "remembers" the trend direction. If a trend begins during low volatility (gray candles), the script waits. The moment volatility and momentum confirm the move, a Smart Recovery Signal is triggered, allowing you to enter an existing trend safely.
3. Chop Protection (Gray Candles)
Preservation of capital is the priority. The script analyzes the Average Directional Index (ADX) and Volatility (ATR).
Colored Candles (Green/Red): The market is trending with sufficient strength. Trading is permitted.
Gray Candles: The market is in a low-energy chop or consolidation (ADX < 20). Trading is discouraged.
4. Dynamic Trend Cloud
The space between the Fast and Slow trends is filled with a dynamic cloud.
Darker/Opaque Cloud: Indicates a widening spread, suggesting accelerating momentum.
Lighter/Transparent Cloud: Indicates a narrowing spread, suggesting the trend may be weakening or consolidating.
5. Pullback & Retest Signals (+)
While triangles mark the start of a trend, the Plus (+) signs mark low-risk opportunities to add to a position. These appear when price dips into the cloud, finds support at the "Fair Value" zone, and closes back in the direction of the trend with confirmed momentum.
User Guide & Strategy
Setup
Add the indicator to your chart.
For Beginners: Enable "Auto-Adaptive Timeframes" in the settings.
For Advanced Users: Disable Auto-Adapt and manually configure your Fast/Slow pairings (Default is Daily 50 EMA / Weekly 50 EMA).
Signal Mode: Choose "First Breakout Only" for a cleaner chart, or "All Signals" if you wish to see re-entry points during choppy starts.
Long Entry Criteria (Buy)
Trend: The Cloud must be Green (Fast Trend > Slow Trend).
Signal: A Green Triangle appears below the bar.
Confirmation: The signal candle must not be Gray.
Re-Entry: A small Green (+) sign appears, indicating a successful test of the cloud support.
Short Entry Criteria (Sell)
Trend: The Cloud must be Red (Fast Trend < Slow Trend).
Signal: A Red Triangle appears above the bar.
Confirmation: The signal candle must not be Gray.
Re-Entry: A small Red (+) sign appears, indicating a successful test of the cloud resistance.
Stop Loss & Risk Management
Stop Loss: A standard institutional stop loss is placed just beyond the Slow Trend Line (the outer edge of the cloud). If price closes beyond the Slow Trend, the macro thesis is invalid.
Take Profit: Target liquidity pools or use a trailing stop based on the Fast Trend line.
Settings Overview
Mode Selection: Toggle between Auto-Adaptive logic or Manual control.
Manual Configuration: Define the specific Timeframe, Length, and Type (EMA, SMA, WMA) for both Fast and Slow trends.
Signal Logic: Toggle "Show Pullback Signals" on/off. Switch between "First Breakout" or "All Signals."
Quality Filters: Toggle individual filters (ATR, RSI, ADX) to adjust sensitivity. Turning these off makes the script more responsive but increases false signals.
Visual Style: Customize colors for Bullish, Bearish, and Neutral (Gray) states. Adjust cloud transparency.
Disclaimer
Risk Warning: Trading financial markets involves a high degree of risk and is not suitable for all investors. You could lose some or all of your initial investment.
Educational Use Only: This script and the information provided herein are for educational and informational purposes only. They do not constitute financial advice, investment advice, trading advice, or any other recommendation.
No Guarantee: Past performance of any trading system or methodology is not necessarily indicative of future results. The "Institutional Trend" indicator is a tool to assist in technical analysis, not a crystal ball. The creators of this script assume no responsibility or liability for any trading losses or damages incurred as a result of using this tool. Always perform your own due diligence and consult with a qualified financial advisor before making investment decisions.
