Average Directional Movement Index Rating Backtest The Average Directional Movement Index Rating (ADXR) measures the strength
of the Average Directional Movement Index (ADX). It's calculated by taking
the average of the current ADX and the ADX from one time period before
(time periods can vary, but the most typical period used is 14 days).
Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening
and weakening trends. However, because it represents an average of ADX, values
don't fluctuate as dramatically and some analysts believe the indicator helps
better display trends in volatile markets.
You can change long to short in the Input Settings
WARNING:
- For purpose educate only
- This script to change bars colors.
חפש סקריפטים עבור "adx"
Average Directional Movement Index Rating Strategy The Average Directional Movement Index Rating (ADXR) measures the strength
of the Average Directional Movement Index (ADX). It's calculated by taking
the average of the current ADX and the ADX from one time period before
(time periods can vary, but the most typical period used is 14 days).
Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening
and weakening trends. However, because it represents an average of ADX, values
don't fluctuate as dramatically and some analysts believe the indicator helps
better display trends in volatile markets.
WARNING:
- This script to change bars colors.
Average Directional Movement Index Rating The Average Directional Movement Index Rating (ADXR) measures the strength
of the Average Directional Movement Index (ADX). It's calculated by taking
the average of the current ADX and the ADX from one time period before
(time periods can vary, but the most typical period used is 14 days).
Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening
and weakening trends. However, because it represents an average of ADX, values
don't fluctuate as dramatically and some analysts believe the indicator helps
better display trends in volatile markets.
The JewelThe Jewel is a comprehensive momentum and trend-based indicator designed to give traders clear insights into potential market shifts. By integrating RSI, Stochastic, and optional ADX filters with an EMA-based trend filter, this script helps identify high-conviction entry and exit zones for multiple trading styles, from momentum-based breakouts to mean-reversion setups.
Features
Momentum Integration:
Leverages RSI and Stochastic crossovers for real-time momentum checks, reducing noise and highlighting potential turning points.
Optional ADX Filter:
Analyzes market strength; only triggers signals when volatility and directional movement suggest strong follow-through.
EMA Trend Filter:
Identifies broad market bias (bullish vs. bearish), helping traders focus on higher-probability setups by aligning with the prevailing trend.
Caution Alerts:
Flags potentially overbought or oversold conditions when both RSI and Stochastic reach extreme zones, cautioning traders to manage risk or tighten stops.
Customizable Parameters:
Fine-tune RSI, Stochastic, ADX, and EMA settings to accommodate various assets, timeframes, and trading preferences.
How to Use
Momentum Breakouts: Watch for RSI cross above a set threshold and Stochastic cross up, confirmed by ADX strength and alignment with the EMA filter for potential breakout entries.
Mean Reversion: Look for caution signals (RSI & Stoch extremes) as early warnings for trend slowdown or reversal opportunities.
Trend Continuation: In trending markets, rely on the EMA filter to stay aligned with the primary direction. Use momentum crosses (RSI/Stochastic) to time add-on entries or exits.
Important Notes
Non-Investment Advice
The Jewel is a technical analysis tool and does not constitute financial advice. Always use proper risk management and consider multiple confirmations when making trading decisions.
No Warranty
This indicator is provided as-is, without warranty or guarantees of performance. Traders should backtest and verify its effectiveness on their specific instruments and timeframes.
Collaborate & Share
Feedback and suggestions are welcome! Engaging with fellow traders can help refine and adapt The Jewel for diverse market conditions, strengthening the TradingView community as a whole.
Happy Trading!
If you find this script valuable, please share your feedback, ideas, or enhancements. Collaboration fosters a more insightful trading experience for everyone.
TrigWave Suite [InvestorUnknown]The TrigWave Suite combines Sine-weighted, Cosine-weighted, and Hyperbolic Tangent moving averages (HTMA) with a Directional Movement System (DMS) and a Relative Strength System (RSS).
Hyperbolic Tangent Moving Average (HTMA)
The HTMA smooths the price by applying a hyperbolic tangent transformation to the difference between the price and a simple moving average. It also adjusts this value by multiplying it by a standard deviation to create a more stable signal.
// Function to calculate Hyperbolic Tangent
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
// Function to calculate Hyperbolic Tangent Moving Average
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Sine-Weighted Moving Average (SWMA)
The SWMA applies sine-based weights to historical prices. This gives more weight to the central data points, making it responsive yet less prone to noise.
// Function to calculate the Sine-Weighted Moving Average
f_Sine_Weighted_MA(series float src, simple int length) =>
var float sine_weights = array.new_float(0)
array.clear(sine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights, weight)
// Normalize the weights
sum_weights = array.sum(sine_weights)
for i = 0 to length - 1
norm_weight = array.get(sine_weights, i) / sum_weights
array.set(sine_weights, i, norm_weight)
// Calculate Sine-Weighted Moving Average
swma = 0.0
if bar_index >= length
for i = 0 to length - 1
swma := swma + array.get(sine_weights, i) * src
swma
Cosine-Weighted Moving Average (CWMA)
The CWMA uses cosine-based weights for data points, which produces a more stable trend-following behavior, especially in low-volatility markets.
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * src
cwma
Directional Movement System (DMS)
DMS is used to identify trend direction and strength based on directional movement. It uses ADX to gauge trend strength and combines +DI and -DI for directional bias.
// Function to calculate Directional Movement System
f_DMS(simple int dmi_len, simple int adx_len) =>
up = ta.change(high)
down = -ta.change(low)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
trur = ta.rma(ta.tr, dmi_len)
plus = fixnan(100 * ta.rma(plusDM, dmi_len) / trur)
minus = fixnan(100 * ta.rma(minusDM, dmi_len) / trur)
sum = plus + minus
adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adx_len)
dms_up = plus > minus and adx > minus
dms_down = plus < minus and adx > plus
dms_neutral = not (dms_up or dms_down)
signal = dms_up ? 1 : dms_down ? -1 : 0
Relative Strength System (RSS)
RSS employs RSI and an adjustable moving average type (SMA, EMA, or HMA) to evaluate whether the market is in a bullish or bearish state.
// Function to calculate Relative Strength System
f_RSS(rsi_src, rsi_len, ma_type, ma_len) =>
rsi = ta.rsi(rsi_src, rsi_len)
ma = switch ma_type
"SMA" => ta.sma(rsi, ma_len)
"EMA" => ta.ema(rsi, ma_len)
"HMA" => ta.hma(rsi, ma_len)
signal = (rsi > ma and rsi > 50) ? 1 : (rsi < ma and rsi < 50) ? -1 : 0
ATR Adjustments
To minimize false signals, the HTMA, SWMA, and CWMA signals are adjusted with an Average True Range (ATR) filter:
// Calculate ATR adjusted components for HTMA, CWMA and SWMA
float atr = ta.atr(atr_len)
float htma_up = htma + (atr * atr_mult)
float htma_dn = htma - (atr * atr_mult)
float swma_up = swma + (atr * atr_mult)
float swma_dn = swma - (atr * atr_mult)
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
This adjustment allows for better adaptation to varying market volatility, making the signal more reliable.
Signals and Trend Calculation
The indicator generates a Trend Signal by aggregating the output from each component. Each component provides a directional signal that is combined to form a unified trend reading. The trend value is then converted into a long (1), short (-1), or neutral (0) state.
Backtesting Mode and Performance Metrics
The Backtesting Mode includes a performance metrics table that compares the Buy and Hold strategy with the TrigWave Suite strategy. Key statistics like Sharpe Ratio, Sortino Ratio, and Omega Ratio are displayed to help users assess performance. Note that due to labels and plotchar use, automatic scaling may not function ideally in backtest mode.
Alerts and Visualization
Trend Direction Alerts: Set up alerts for long and short signals
Color Bars and Gradient Option: Bars are colored based on the trend direction, with an optional gradient for smoother visual feedback.
Important Notes
Customization: Default settings are experimental and not intended for trading/investing purposes. Users are encouraged to adjust and calibrate the settings to optimize results according to their trading style.
Backtest Results Disclaimer: Please note that backtest results are not indicative of future performance, and no strategy guarantees success.
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.
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
Trend Start and Change and Signals by fekonomiTrend Change and Start Signals Indicator
This indicator combines multiple technical analysis tools to generate buy and sell signals based on trend changes and market conditions. It uses the following components:
MACD (Moving Average Convergence Divergence): Identifies trend direction and momentum.
RSI (Relative Strength Index): Measures the speed and change of price movements.
EMA (Exponential Moving Average): Tracks the average price over a specific period, giving more weight to recent prices.
ADX (Average Directional Index): Indicates the strength of a trend.
Ichimoku Cloud: Provides support and resistance levels, trend direction, and momentum.
Volume Increase: Checks for significant increases in trading volume.
How It Works
Buy Signal: Generated when at least three of the following conditions are met:
MACD line crosses above the signal line.
RSI is above 50.
Short EMA crosses above the long EMA and ADX indicates a strong trend.
Price is above the Ichimoku Cloud and volume is significantly higher than the average.
Sell Signal: Generated when at least three of the following conditions are met:
MACD line crosses below the signal line.
RSI is below 50.
Short EMA crosses below the long EMA and ADX indicates a strong trend.
Price is below the Ichimoku Cloud.
Visualization
Buy signals are marked with green "BUY" labels below the bars.
Sell signals are marked with red "SELL" labels above the bars.
The indicator also plots the short and long EMAs, and the Ichimoku Cloud for visual reference.
This indicator helps traders identify potential trend changes and entry/exit points based on a combination of reliable technical indicators.
Feel free to customize the settings to fit your trading strategy! If you have any questions or need further assistance, let me know. Happy trading! 📈
[MAD] Weighted Trend Detector--> Purpose
The Weighted Trend Detector evaluates market direction by combining multiple technical indicators (RSI, MACD, Moving Averages, ADX, and Volume) across up to three different timeframes.
It calculates an overall trend score to help visualize whether conditions are bullish, bearish, or neutral.
--> Scaling & Weightings
Each component indicator contributes a score between -1.0 and +1.0. User-defined weights (e.g., 0.2 for RSI, 0.3 for MACD) determine how much each indicator influences the final score. An adaptive scaling mechanism ensures extreme values remain in view by dynamically setting the minimum and maximum of the score range over a specified lookback period.
--> Basic Parameters of Individual Indicators
RSI Period: Number of bars for the Relative Strength Index calculation; higher values smooth out noise but may lag.
MACD Fast/Slow/Signal: EMA-based periods to identify momentum shifts. A shorter “Fast” length reacts quickly, while a longer “Slow” length is smoother.
Moving Averages (Short & Long Lengths): Simple Moving Averages used to gauge shorter- vs. longer-term price direction.
ADX Length: Defines how many bars are considered when measuring trend strength. Higher values produce smoother ADX lines.
Volume MA Length: Period over which the average volume is calculated to compare against current volume.
--> Colors & How They Are Mixed
The background color scales from a negative color (for lower scores) to a positive color (for higher scores).
Near the highest or lowest parts of the score range, additional blending occurs if the slope (change in score) reverses:
Turning Down: Mixes with a user-chosen “warning” color if the score is high but moving lower.
Turning Up: Mixes with a user-chosen “recovery” color if the score is low but moving higher.
All colors (including line and label text) can be adjusted in the script’s inputs to suit personal preferences.colors are customizable via inputs.
Have fun :-)
DIN: Dynamic Trend NavigatorDIN: Dynamic Trend Navigator
Overview
The Dynamic Trend Navigator script is designed to help traders identify and capitalize on market trends using a combination of Weighted Moving Averages (WMA), Volume Weighted Average Price (VWAP), and Anchored VWAP (AVWAP). The script provides customizable settings and flexible alerts for various crossover conditions, enhancing its utility for different trading strategies.
Key Features
- **1st and 2nd WMA**: Allows users to set and visualize two Weighted Moving Averages. These can be customized to any period, providing flexibility in trend identification.
- **VWAP and AVWAP**: Incorporates both VWAP and AVWAP, offering insights into price levels adjusted by volume.
- **ATR and ADX Indicators**: Includes the Average True Range (ATR) and Average Directional Index (ADX) to help assess market volatility and trend strength.
- **Flexible Alerts**: Configurable buy and sell alerts for any crossover condition, making it versatile for various trading strategies.
How to Use the Script
1. **Set the WMA Periods**: Customize the periods for the 1st and 2nd WMAs to suit your trading strategy.
2. **Enable VWAP and AVWAP**: Choose whether to include VWAP and AVWAP in your analysis by enabling the respective settings.
3. **Configure Alerts**: Set up alerts for the desired crossover conditions (WMA, VWAP, AVWAP) to receive notifications for potential trading opportunities.
4. **Monitor Signals**: Watch for buy and sell signals indicated by triangle shapes on the chart, which appear at the selected crossover points.
When to Use
- **Best Time to Use**: The script is most effective in trending markets where price movements are well-defined. It helps traders stay on the right side of the trend and avoid false signals during periods of low volatility.
- **When Not to Use**: Avoid using the script in choppy or sideways markets where price action lacks direction. The script may generate false signals in such conditions, leading to potential losses.
Benefits of VWAP and AVWAP
- **VWAP**: The Volume Weighted Average Price provides a price benchmark that adjusts for volume, helping traders identify fair value levels. It is particularly useful for intraday trading and gauging market sentiment.
- **AVWAP**: The Anchored VWAP allows traders to set a starting point for VWAP calculations, providing flexibility in analyzing price levels over specific periods or events. This helps in identifying key support and resistance levels based on volume.
Unique Aspects
- **Customizability**: The script offers extensive customization options for WMA periods, VWAP, AVWAP, and alert conditions, making it adaptable to various trading strategies.
- **Combining Indicators**: By integrating WMAs, VWAP, AVWAP, ATR, and ADX, the script provides a comprehensive view of market conditions, enhancing decision-making.
- **Real-Time Alerts**: The flexible alert system ensures traders receive timely notifications for potential trade setups, improving responsiveness to market changes.
Examples
- **Example 1**: A trader sets the 1st WMA to 8 and the 2nd WMA to 100, enabling the VWAP. When the 1st WMA crosses above the 2nd WMA or VWAP, a buy signal is triggered, indicating a potential long entry.
- **Example 2**: A trader sets the AVWAP to start 30 bars ago and monitors for crossovers with the 1st WMA. When the 1st WMA crosses below the AVWAP, a sell signal is triggered, suggesting a potential short entry.
Final Notes
The Dynamic Trend Navigator script is a powerful tool for traders looking to enhance their market analysis and trading decisions. Its unique combination of customizable indicators and flexible alert system sets it apart from other scripts, making it a valuable addition to any trader's toolkit.
Disclaimer: Never any financial advice. Just ThisGirl loving experimenting with indicators to help myself, as well as others.
KaracaticaKaracatica Indicator - Dynamic Trend Following.
The Karacatica Indicator is designed for traders looking for a comprehensive approach to trend trading by combining directional movements and Average True Range (ATR).
Key Features: ATR-Based Trend Detection: The indicator uses Average True Range (ATR) to measure market volatility and integrates with price action to capture strong trend movements.
Directional Indicators (DI's): Calculates DI's (Positive Directional Index Di+ and Negative Directional Index Di-) to compare buying and selling pressure. This allows for more accurate trend identification, highlighting when buyers or sellers dominate.
Signal Generation: Buy Signal: Generated when price action is bullish (close is above the previous period's close) and DI+ exceeds DI-, indicating that buyers are in control.
Sell Signal: Triggered when price action is bearish (close is below the previous period’s close) and DI- exceeds DI+, showing that sellers dominate the market.
Visual Signals: Green triangle (▲) indicating a buy opportunity, plotted below the bar.
Fuchsia triangle (▼) signaling a sell opportunity, plotted above the bar.
Customizable Inputs: The indicator allows users to adjust the ATR period, DI length, and ADX smoothing parameters, giving it the flexibility to suit different trading styles and timeframes.
Why should you use it?
This indicator simplifies the process of analyzing the combination market direction and trend strength. It is especially useful for traders who like strong directional movements and want clear, visually represented entry signals. The Karacatica Indicator can generate good buy or sell signals in trading and can be used on multiple assets and timeframes, making it adaptable to different market conditions.
Settings Overview: ATR Period: Sets the period for calculating ATR, used to determine market volatility.
DI Length: The length of the lookback period for DI+ and DI- calculations.
ADX Smoothing: Smooths the ADX (Average Directional Index) to reduce noise.
Feel free to experiment with this indicator, share feedback, and adapt it to your trading strategy. Good trading!
ZERO LAG TRADE SIGNALS by BootcampZeroThe ZERO LAG TRADE SIGNALS by BootcampZero indicator is a versatile tool designed to help traders identify optimal entry and exit points for both short-term scalping and long-term trading across multiple time frames. It combines several well-known technical analysis methods, including moving averages, trend analysis, directional indicators, and adaptive trend calculations, to deliver reliable buy and sell signals.
Short-Term Scalping (Under 5-Minute Time Frames)
For short-term traders who prefer quick trades on lower time frames, such as under 5 minutes, this indicator uses a combination of the EMA (Exponential Moving Average) and SMA (Simple Moving Average) to spot fast trend reversals. The indicator is particularly useful for scalpers because it focuses on detecting short-term price momentum by comparing the faster-moving averages with slower ones, triggering signals based on their crossover.
Buy Signals are generated when a fast-moving EMA crosses above a slower-moving SMA, indicating upward momentum.
Sell Signals are triggered when the fast-moving EMA crosses below the slower-moving SMA, signaling potential downward price movement.
In addition, the Adaptive Trend Finder feature dynamically adjusts to recent price deviations and volatility, making it easier for scalpers to spot the prevailing short-term trend with high confidence. The indicator also uses ADX (Average Directional Index) for momentum confirmation, ensuring that signals are only generated during strong price trends, reducing false positives in sideways markets.
Long-Term Trading (Above 1-Day Charts)
When applied to higher time frames such as daily charts or above, this indicator excels in generating reliable long-term buy and sell signals, perfect for swing traders and long-term investors. The Kaufman Adaptive Moving Average (KAMA) and the Ichimoku Cloud are used to assess long-term trends by filtering out market noise and focusing on sustainable price direction.
KAMA helps to adapt the moving average based on market volatility, providing smoother signals that minimize whipsawing in longer-term trades.
Ichimoku Cloud provides additional trend confirmation by identifying whether the market is bullish or bearish based on the relationship between key lines like the Tenkan-Sen (Conversion Line) and Kijun-Sen (Base Line), and how the current price interacts with the Ichimoku Cloud itself.
The indicator also integrates PPO (Percentage Price Oscillator) to capture divergences between price and momentum, further supporting traders in holding positions for extended periods when the signal strength is robust.
Key Technical Values and Factors for Signals
EMA and SMA Crossover: Fast EMA vs. Slow SMA to detect short-term trend reversals.
ADX: Helps gauge the strength of the trend; signals are only generated in trending markets.
KAMA: Filters noise in long-term trends, providing smooth signals based on market volatility.
Ichimoku Cloud: Offers insight into long-term trends and momentum by analyzing price relative to the cloud.
PPO: Detects divergences between price and momentum for trend continuation or reversal signals.
How It Works
Buy signals are generated when bullish conditions are met, and the indicator confirms momentum with ADX, crossover of the EMAs, or a bullish breakout from the Ichimoku Cloud.
Sell signals are triggered when bearish conditions prevail, confirmed by the same factors in reverse, such as a bearish EMA crossover or weakness in ADX.
By combining these powerful tools, ZERO LAG TRADE SIGNALS by BootcampZero offers traders a comprehensive system for both quick scalping trades and more conservative long-term positioning, providing reliable and adaptive signals across different market conditions.
Six PillarsGeneral Overview
The "Six Pillars" indicator is a comprehensive trading tool that combines six different technical analysis methods to provide a holistic view of market conditions.
These six pillars are:
Trend
Momentum
Directional Movement (DM)
Stochastic
Fractal
On-Balance Volume (OBV)
The indicator calculates the state of each pillar and presents them in an easy-to-read table format. It also compares the current timeframe with a user-defined comparison timeframe to offer a multi-timeframe analysis.
A key feature of this indicator is the Confluence Strength meter. This unique metric quantifies the overall agreement between the six pillars across both timeframes, providing a score out of 100. A higher score indicates stronger agreement among the pillars, suggesting a more reliable trading signal.
I also included a visual cue in the form of candle coloring. When all six pillars agree on a bullish or bearish direction, the candle is colored green or red, respectively. This feature allows traders to quickly identify potential high-probability trade setups.
The Six Pillars indicator is designed to work across multiple timeframes, offering a comparison between the current timeframe and a user-defined comparison timeframe. This multi-timeframe analysis provides traders with a more comprehensive understanding of market dynamics.
Origin and Inspiration
The Six Pillars indicator was inspired by the work of Dr. Barry Burns, author of "Trend Trading for Dummies" and his concept of "5 energies." (Trend, Momentum, Cycle, Support/Resistance, Scale) I was intrigued by Dr. Burns' approach to analyzing market dynamics and decided to put my own twist upon his ideas.
Comparing the Six Pillars to Dr. Burns' 5 energies, you'll notice I kept Trend and Momentum, but I swapped out Cycle, Support/Resistance, and Scale for Directional Movement, Stochastic, Fractal, and On-Balance Volume. These changes give you a more dynamic view of market strength, potential reversals, and volume confirmation all in one package.
What Makes This Indicator Unique
The standout feature of the Six Pillars indicator is its Confluence Strength meter. This feature calculates the overall agreement between the six pillars, providing traders with a clear, numerical representation of signal strength.
The strength is calculated by considering the state of each pillar in both the current and comparison timeframes, resulting in a score out of 100.
Here's how it calculates the strength:
It considers the state of each pillar in both the current timeframe and the comparison timeframe.
For each pillar, the absolute value of its state is taken. This means that both strongly bullish (2) and strongly bearish (-2) states contribute equally to the strength.
The absolute values for all six pillars are summed up for both timeframes, resulting in two sums: current_sum and alternate_sum.
These sums are then added together to get a total_sum.
The total_sum is divided by 24 (the maximum possible sum if all pillars were at their strongest states in both timeframes) and multiplied by 100 to get a percentage.
The result is rounded to the nearest integer and capped at a minimum of 1.
This calculation method ensures that the Confluence Strength meter takes into account not only the current timeframe but also the comparison timeframe, providing a more robust measure of overall market sentiment. The resulting score, ranging from 1 to 100, gives traders a clear and intuitive measure of how strongly the pillars agree, with higher scores indicating stronger potential signals.
This approach to measuring signal strength is unique in that it doesn't just rely on a single aspect of price action or volume. Instead, it takes into account multiple factors, providing a more robust and reliable indication of potential market moves. The higher the Confluence Strength score, the more confident traders can be in the signal.
The Confluence Strength meter helps traders in several ways:
It provides a quick and easy way to gauge the overall market sentiment.
It helps prioritize potential trades by identifying the strongest signals.
It can be used as a filter to avoid weaker setups and focus on high-probability trades.
It offers an additional layer of confirmation for other trading strategies or indicators.
By combining the Six Pillars analysis with the Confluence Strength meter, I've created a powerful tool that not only identifies potential trading opportunities but also quantifies their strength, giving traders a significant edge in their decision-making process.
How the Pillars Work (What Determines Bullish or Bearish)
While developing this indicator, I selected and configured six key components that work together to provide a comprehensive view of market conditions. Each pillar is set up to complement the others, creating a synergistic effect that offers traders a more nuanced understanding of price action and volume.
Trend Pillar: Based on two Exponential Moving Averages (EMAs) - a fast EMA (8 period) and a slow EMA (21 period). It determines the trend by comparing these EMAs, with stronger trends indicated when the fast EMA is significantly above or below the slow EMA.
Directional Movement (DM) Pillar: Utilizes the Average Directional Index (ADX) with a default period of 14. It measures trend strength, with values above 25 indicating a strong trend. It also considers the Positive and Negative Directional Indicators (DI+ and DI-) to determine trend direction.
Momentum Pillar: Uses the Moving Average Convergence Divergence (MACD) with customizable fast (12), slow (26), and signal (9) lengths. It compares the MACD line to the signal line to determine momentum strength and direction.
Stochastic Pillar: Employs the Stochastic oscillator with a default period of 13. It identifies overbought conditions (above 80) and oversold conditions (below 20), with intermediate zones between 60-80 and 20-40.
Fractal Pillar: Uses Williams' Fractal indicator with a default period of 3. It identifies potential reversal points by looking for specific high and low patterns over the given period.
On-Balance Volume (OBV) Pillar: Incorporates On-Balance Volume with three EMAs - short (3), medium (13), and long (21) periods. It assesses volume trends by comparing these EMAs.
Each pillar outputs a state ranging from -2 (strongly bearish) to 2 (strongly bullish), with 0 indicating a neutral state. This standardized output allows for easy comparison and aggregation of signals across all pillars.
Users can customize various parameters for each pillar, allowing them to fine-tune the indicator to their specific trading style and market conditions. The multi-timeframe comparison feature also allows users to compare pillar states between the current timeframe and a user-defined comparison timeframe, providing additional context for decision-making.
Design
From a design standpoint, I've put considerable effort into making the Six Pillars indicator visually appealing and user-friendly. The clean and minimalistic design is a key feature that sets this indicator apart.
I've implemented a sleek table layout that displays all the essential information in a compact and organized manner. The use of a dark background (#030712) for the table creates a sleek look that's easy on the eyes, especially during extended trading sessions.
The overall design philosophy focuses on presenting complex information in a simple, intuitive format, allowing traders to make informed decisions quickly and efficiently.
The color scheme is carefully chosen to provide clear visual cues:
White text for headers ensures readability
Green (#22C55E) for bullish signals
Blue (#3B82F6) for neutral states
Red (#EF4444) for bearish signals
This color coding extends to the candle coloring, making it easy to spot when all pillars agree on a bullish or bearish outlook.
I've also incorporated intuitive symbols (↑↑, ↑, →, ↓, ↓↓) to represent the different states of each pillar, allowing for quick interpretation at a glance.
The table layout is thoughtfully organized, with clear sections for the current and comparison timeframes. The Confluence Strength meter is prominently displayed, providing traders with an immediate sense of signal strength.
To enhance usability, I've added tooltips to various elements, offering additional information and explanations when users hover over different parts of the indicator.
How to Use This Indicator
The Six Pillars indicator is a versatile tool that can be used for various trading strategies. Here are some general usage guidelines and specific scenarios:
General Usage Guidelines:
Pay attention to the Confluence Strength meter. Higher values indicate stronger agreement among the pillars and potentially more reliable signals.
Use the multi-timeframe comparison to confirm signals across different time horizons.
Look for alignment between the current timeframe and comparison timeframe pillars for stronger signals.
One of the strengths of this indicator is it can let you know when markets are sideways – so in general you can know to avoid entering when the Confluence Strength is low, indicating disagreement among the pillars.
Customization Options
The Six Pillars indicator offers a wide range of customization options, allowing traders to tailor the tool to their specific needs and trading style. Here are the key customizable elements:
Comparison Timeframe:
Users can select any timeframe for comparison with the current timeframe, providing flexibility in multi-timeframe analysis.
Trend Pillar:
Fast EMA Period: Adjustable for quicker or slower trend identification
Slow EMA Period: Can be modified to capture longer-term trends
Momentum Pillar:
MACD Fast Length
MACD Slow Length
MACD Signal Length These can be adjusted to fine-tune momentum sensitivity
DM Pillar:
ADX Period: Customizable to change the lookback period for trend strength measurement
ADX Threshold: Adjustable to define what constitutes a strong trend
Stochastic Pillar:
Stochastic Period: Can be modified to change the sensitivity of overbought/oversold readings
Fractal Pillar:
Fractal Period: Adjustable to identify potential reversal points over different timeframes
OBV Pillar:
Short OBV EMA
Medium OBV EMA
Long OBV EMA These periods can be customized to analyze volume trends over different timeframes
These customization options allow traders to experiment with different settings to find the optimal configuration for their trading strategy and market conditions. The flexibility of the Six Pillars indicator makes it adaptable to various trading styles and market environments.
DynamicFunctionsLibrary "DynamicFunctions"
Custom Dynamic functions that allow an adaptive calculation beginning from the first bar
RoC(src, period)
Dynamic RoC
Parameters:
src (float) : and period
Custom function to calculate the actual period considering non-na source values
period (int)
dynamicMedian(src, length)
Dynamic Median
Parameters:
src (float) : and length
length (int)
kernelRegression(src, bandwidth, kernel_type)
Dynamic Kernel Regression Calculation \n Uses either of the following inputs for kernel_type:\nEpanechnikov\nLogistic\nWave
Parameters:
src (float)
bandwidth (int)
kernel_type (string)
waveCalculation(source, bandwidth, width)
Use together with kernelRegression function to get chart applicable band
Parameters:
source (float)
bandwidth (int)
width (float)
Rsi(src, length)
Dynamic RSI function
Parameters:
src (float)
length (int)
dynamicStdev(src, period)
Dynamic SD function
Parameters:
src (float)
period (int)
stdv_bands(src, length, mult)
Dynamic SD Bands
Parameters:
src (float)
length (int)
mult (float)
Returns: Basis, Positive SD, Negative SD
Adx(dilen, adxlen)
Dynamic ADX
Parameters:
dilen (int)
adxlen (int)
Returns: adx
Atr(length)
Dynamic ATR
Parameters:
length (int)
Returns: ATR
Macd(source, fastLength, slowLength, signalSmoothing)
Dynamic MACD
Parameters:
source (float)
fastLength (int)
slowLength (int)
signalSmoothing (int)
Returns: macdLine, signalLine, histogram
