MACD+RSI+BBDESCRIPTION
The MACD + RSI + Bollinger Bands Indicator is a comprehensive technical analysis tool designed for traders and investors to identify potential market trends and reversals. This script combines three indicators: the Moving Average Convergence Divergence (MACD), the Relative Strength Index (RSI), and Bollinger Bands. Each of these indicators provides unique insights into market behavior.
FEATURES
MACD (Moving Average Convergence Divergence)
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price.
The script calculates the MACD line, the signal line, and the histogram, which visually represents the difference between the MACD line and the signal line.
RSI (Relative Strength Index)
The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is typically used to identify overbought or oversold conditions.
The script allows users to set custom upper and lower thresholds for the RSI, with default values of 70 and 30, respectively.
Bollinger Bands
Bollinger Bands consist of a middle band (EMA) and two outer bands (standard deviations away from the EMA). They help traders identify volatility and potential price reversals.
The script allows users to customize the length of the Bollinger Bands and the multiplier for the standard deviation.
Color-Coding Logic
The histogram color changes based on the following conditions:
Black: If the RSI is above the upper threshold and the closing price is above the upper Bollinger Band, or if the RSI is below the lower threshold and the closing price is below the lower Bollinger Band.
Green (#4caf50): If the RSI is above the upper threshold but the closing price is not above the upper Bollinger Band.
Light Green (#a5d6a7): If the histogram is positive and the RSI is not above the upper threshold.
Red (#f23645): If the RSI is below the lower threshold but the closing price is not below the lower Bollinger Band.
Light Red (#faa1a4): If the histogram is negative and the RSI is not below the lower threshold.
Inputs
Bollinger Bands Settings
Length: The number of periods for the moving average.
Basis MA Type: The type of moving average (SMA, EMA, SMMA, WMA, VWMA).
Source: The price source for the Bollinger Bands calculation.
StdDev: The multiplier for the standard deviation.
RSI Settings
RSI Length: The number of periods for the RSI calculation.
RSI Upper: The upper threshold for the RSI.
RSI Lower: The lower threshold for the RSI.
Source: The price source for the RSI calculation.
MACD Settings
Fast Length: The length for the fast moving average.
Slow Length: The length for the slow moving average.
Signal Smoothing: The length for the signal line smoothing.
Oscillator MA Type: The type of moving average for the MACD calculation.
Signal Line MA Type: The type of moving average for the signal line.
Usage
This indicator is suitable for various trading strategies, including day trading, swing trading, and long-term investing.
Traders can use the MACD histogram to identify potential buy and sell signals, while the RSI can help confirm overbought or oversold conditions.
The Bollinger Bands provide context for price volatility and potential breakout or reversal points.
Example:
From the example, it can clearly see that the Selling Climax and Buying Climax, marked as orange circle when a black histogram occurs.
Conclusion
The MACD + RSI + Bollinger Bands Indicator is a versatile tool that combines multiple technical analysis methods to provide traders with a comprehensive view of market conditions. By utilizing this script, traders can enhance their analysis and improve their decision-making process.
Penunjuk dan strategi
Fractals CheckerBasically, this indicator helps to identify upper and lower fractals (red/green) of three candles.
This fractal checker marks all candles with a triangle below/above the candle that fall into this category and draws a line until the fractal is closed.
No Trade Zone Indicator [CHE]No Trade Zone Indicator
The "No Trade Zone Indicator " is a powerful tool designed to help traders identify periods when the market may not present favorable trading opportunities. By analyzing the percentage change in the 20-period Simple Moving Average (SMA20) relative to a dynamically adjusted threshold based on market volatility, this indicator highlights times when it's prudent to stay out of the market.
Why Knowing When Not to Trade Is Important
Understanding when not to trade is just as crucial as knowing when to enter or exit a position. Trading during periods of low volatility or uncertain market direction can lead to unnecessary risks and potential losses. By recognizing these "No Trade Zones," you can:
- Avoid Low-Probability Trades: Reduce the chances of entering trades with unfavorable risk-to-reward ratios.
- Preserve Capital: Protect your investment from unpredictable market movements.
- Enhance Focus: Concentrate on high-quality trading opportunities that align with your strategy.
How the Indicator Works
- SMA20 Calculation: Computes the 20-period Simple Moving Average of closing prices to identify the market's short-term trend.
- ATR Measurement: Calculates the Average True Range (ATR) over a user-defined period (default is 14) to assess market volatility.
- Dynamic Threshold: Determines an adjusted threshold by multiplying the ATR percentage by a Threshold Adjustment Factor (default is 0.05).
- Trend Analysis: Compares the percentage change of the SMA20 against the adjusted threshold to evaluate market momentum.
- Status Identification:
- Long: Indicates a rising SMA20 above the threshold—suggesting a potential upward trend.
- Short: Indicates a falling SMA20 above the threshold—suggesting a potential downward trend.
- No Trade: Signals when the SMA20 change is below the threshold, marking a period of low volatility or indecision.
Features
- Customizable Settings: Adjust the ATR period and Threshold Adjustment Factor to suit different trading styles and market conditions.
- Visual Indicators: Colored columns represent market status—green for "Long," red for "Short," and gray for "No Trade."
- On-Chart Table: An optional table displays the current market status directly on your chart for quick reference.
- Alerts: Set up alerts to receive notifications when the market enters a "No Trade Zone," helping you stay informed without constant monitoring.
How to Use the Indicator
1. Add to Chart: Apply the "No Trade Zone Indicator " to your preferred trading chart on TradingView.
2. Configure Settings: Customize the ATR period and Threshold Adjustment Factor based on your analysis and risk tolerance.
3. Interpret Signals:
- Green Columns: Consider looking for buying opportunities as the market shows upward momentum.
- Red Columns: Consider looking for selling opportunities as the market shows downward momentum.
- Gray Columns: Refrain from trading as the market lacks clear direction.
4. Monitor Alerts: Use the alert feature to get notified when the market status changes, allowing you to make timely decisions.
Conclusion
Incorporating the "No Trade Zone Indicator " into your trading toolkit can enhance your decision-making process by clearly indicating when the market may not be conducive to trading. By focusing on periods with favorable conditions and avoiding low-volatility times, you can improve your trading performance and achieve better results over the long term.
*Trade wisely, and remember—the best trade can sometimes be no trade at all.*
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
best regards
Chervolino
W.ARITAS™ Quantum RSIW.ARITAS™ Quantum RSI
Overview
The W.ARITAS™ Quantum RSI is an advanced take on the traditional Relative Strength Index (RSI) tailored for today’s fast-moving markets. This innovative indicator integrates quantum-inspired methodologies and adaptive volatility adjustments, making it a powerful tool for traders who seek to better capture both trend shifts and market reversals. The indicator is suitable for all asset classes and is optimized for dynamic, real-time trading environments.
Features
Volatility-Adaptive RSI: Dynamically adjusts the RSI length based on real-time market volatility, providing a more responsive and smooth RSI.
Quantum Phase Modulation: Adds an additional layer of signal refinement by incorporating wave-like behaviors, helping to capture cyclic market patterns.
Bollinger Bands Integration: Applies enhanced Bollinger Bands around the RSI, with dynamic boundaries that expand or contract based on volatility.
Probability-Based Ripple Effects: Employs gravity and ripple effects to modulate RSI movements, resulting in better identification of critical points.
Gradient Visuals for Clarity: Color gradients represent strength or weakness within RSI ranges, making it easy to spot potential overbought and oversold conditions.
Use Case
This indicator is perfect for traders looking to refine their entries and exits by identifying nuanced shifts in momentum. The enhanced smoothing and volatility sensitivity make it an excellent choice for intraday and swing trading strategies.
License
This indicator is provided under a public license for free use, with no warranty or liability by the developer. Users are advised to trade at their own risk and retain the copyright notice per the license agreement.
Direction finderA trend indicator is a tool used in technical analysis to help identify the direction and strength of a price movement in financial markets. It serves as a guide for traders and investors to understand whether an asset's price is likely to continue moving in a particular direction or if it may reverse. Trend indicators are typically based on historical price data, volume, and sometimes volatility, and they often use mathematical calculations or graphical representations to simplify trend analysis.
Common types of trend indicators include:
Moving Averages (MAs): Averages the asset price over a set period, creating a smooth line that helps identify the general direction of the trend. Popular moving averages include the Simple Moving Average (SMA) and Exponential Moving Average (EMA).
Moving Average Convergence Divergence (MACD): Measures the relationship between two moving averages of an asset’s price, often used to signal trend reversals or continuations based on line crossovers and the direction of the MACD line.
Average Directional Index (ADX): Indicates the strength of a trend rather than its direction. A high ADX value suggests a strong trend, while a low value suggests a weak trend or a range-bound market.
Bollinger Bands: This indicator includes a moving average with bands set at standard deviations above and below. It helps identify price volatility and potential trend reversals when prices move toward the outer bands.
Trend indicators can help identify entry and exit points by suggesting whether a trend is continuing or if the price may be about to reverse. However, they are often used in conjunction with other types of indicators, such as momentum or volume-based tools, to provide a fuller picture of market behavior and confirm trading signals.
Power Core MAThe Power Core MA indicator is a powerful tool designed to identify the most significant moving average (MA) in a given price chart. This indicator analyzes a wide range of moving averages, from 50 to 400 periods, to determine which one has the strongest influence on the current price action.
The blue line plotted on the chart represents the "Current Core MA," which is the moving average that is most closely aligned with other nearby moving averages. This line indicates the current trend and potential support or resistance levels.
The table displayed on the chart provides two important pieces of information. The "Current Core MA" value shows the length of the moving average that is currently most influential. The "Historical Core MA" value represents the average length of the most influential moving averages over time.
This indicator is particularly useful for traders and analysts who want to identify the most relevant moving average for their analysis. By focusing on the moving average that has the strongest historical significance, users can make more informed decisions about trend direction, support and resistance levels, and potential entry or exit points.
The Power Core MA is an excellent tool for those interested in finding the strongest moving average in the price history. It simplifies the process of analyzing multiple moving averages by automatically identifying the most influential one, saving time and providing valuable insights into market dynamics.
By combining current and historical data, this indicator offers a comprehensive view of the market's behavior, helping traders to adapt their strategies to the most relevant timeframes and trend strengths.
HTF Candle Projections and BoxesThe HTF Candle Projections with Labels indicator builds on the power of previous tools: HTF Candle Projections and HTF Candle Boxes for LTF Charts . This versatile indicator combines advanced features from both indicators into an improved version, allowing you to display multiple Higher Time Frame (HTF) candles directly on a Lower Time Frame (LTF) chart, with enhanced functionality for improved visualization and analysis.
Key Features
Multiple HTF Candle Projections
Project a customizable number of HTF candles to the right of the current time frame. Easily compare HTF and LTF data without constantly switching between charts.
Customizable Projection Types
Choose between traditional candles or Heikin Ashi for your projections, adapting to your preferred analysis method.
Real-Time Open/High/Low/Close Projections
Dynamic updates ensure you always have the most current levels visible. Includes optional lines for Open, High, Low, and Close values, with selectable styles (solid, dotted, dashed).
Enhanced Visualization
Display HTF candles in the background as shaded areas, with transparent color options for up and down candles—offering intuitive context for recent market movements.
OHLC Labels
View key OHLC values beside each projected candle for quick and easy reference.
Time Frame Display Table
Added visual labels to clearly indicate which HTF is being displayed—no more guessing.
Box Options for Candle Range and Body
Box the entire candle range (High to Low) or just the body (Open to Close), inspired by Kevin Rollo's HTF Candle Boxes.
Pip Range Labels
Label the pip range from High to Low or Open to Close, providing better insight into volatility and price movement within the HTF candle.
This indicator is perfect for traders seeking a combined high-level overview with detailed precision for better decision-making. HTF Candle Projections and Boxes keep the macro perspective in view while focusing on the finer details—all in one chart. Free, open-source, and community-inspired, this tool is a comprehensive solution for time frame analysis.
Released under TradingView's default license (Mozilla Public License 2.0).
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.
Exact Three Black Crows and Three White SoldiersExact Three Black Crows and Three White Soldiers
where you can find 3 red and 3 green candle bars
Through these pattern, we can identify the trend reversal
Rainbow by ChetuThis indicator, Rainbow by Chetu, is a comprehensive tool designed for trend analysis and strategic trade setups on TradingView. Here’s a breakdown of its core features and functionality for your TradingView description:
Multi-Length EMAs for Trend Detection: The Rainbow Indicator uses multiple Exponential Moving Averages (EMAs) of different lengths (from 9 to 60) to detect trend strength and direction. A unique color-coding system is applied to each EMA, with green for uptrends, red for downtrends, and black during crossovers. This helps traders visualize the current market trend across various timeframes quickly.
RSI and Volume Filters: To enhance accuracy, the indicator incorporates an RSI (Relative Strength Index) and volume filter. The RSI helps avoid overbought or oversold conditions, while the volume filter ensures signals are generated only in active trading conditions, reducing false signals.
Automated Buy and Sell Signals: The indicator identifies crossover points between fast and slow EMAs, generating Buy and Sell signals based on RSI conditions and volume levels. These signals are plotted directly on the chart with clear labels, making it easy to recognize potential entry points.
Risk Management with Stop Loss and Target Levels: To support risk management, the Rainbow Indicator includes automatic stop-loss and target levels, based on a customizable ATR (Average True Range) multiplier. A shaded box is drawn on the chart between these levels, providing visual guidance on potential risk and reward for each trade.
Trendline Break Detection: The indicator includes a customizable trendline break detection feature, which uses ATR, standard deviation, or linear regression to calculate slopes for trendlines. When a significant trendline is broken, the indicator plots an alert on the chart, signaling possible trend reversals or breakout opportunities.
Customizable Color and Style Options: Users can adjust the colors of trendlines, signal boxes, and EMAs, tailoring the look and feel of the indicator to their preferences. This customization enhances chart readability and aligns with users' unique trading setups.
This Rainbow Indicator offers a powerful, multi-faceted tool for traders looking to automate and refine their analysis, providing clear entry and exit signals, robust trend visualization, and dynamic risk management all in one.
Bolvoman by Dragon.3 Chiến lược giao dịch t là một hệ thống khá phức tạp, kết hợp nhiều chỉ báo và điều kiện khác nhau để xác định tín hiệu mua và bán. Dưới đây là phần giải thích chi tiết từng phần:
EMA (Exponential Moving Averages)
Mã sử dụng ba đường EMA:
Signal EMA là EMA chu kỳ ngắn, thường là 21 hoặc 10.
Trend EMA là EMA 55, dùng để xác định xu hướng chính.
Supper Trend EMA là EMA dùng để hỗ trợ xác định xu hướng, tương tự như trailing stop.
Màu sắc và Điều kiện xu hướng
Khi Signal EMA nằm trên Trend EMA, mã sẽ hiển thị màu xanh để báo hiệu xu hướng tăng.
Khi Signal EMA nằm dưới Trend EMA, mã sẽ hiển thị màu đỏ báo hiệu xu hướng giảm.
Keltner Channel
Keltner Channel được tạo bằng cách sử dụng ATR (Average True Range) làm độ rộng kênh, nhằm xác định các vùng mua và bán.
Kênh trên (upperKC) và kênh dưới (lowerKC) được hiển thị khi người dùng bật Show KC.
Phân tích Mô Hình Nến và Khối Lượng
Mã xác định các mô hình nến như Bullish Engulfing, Bearish Engulfing, Bullish Pinbar, và Bearish Pinbar.
Nếu một trong các mô hình này xuất hiện trong điều kiện xu hướng tăng/giảm (EMA cắt lên/xuống), và khối lượng lớn hơn khối lượng trung bình của 14 phiên trước đó, thì tín hiệu mua hoặc bán sẽ được đưa ra.
Dynamic Levels Breakout
Mã có thể xác định các mức kháng cự và hỗ trợ động dựa trên các điểm pivot, dùng Pivot Point Period và ATR Factor.
Các mức kháng cự và hỗ trợ động sẽ giúp xác định điểm vào lệnh tiềm năng khi giá phá vỡ các mức này.
SuperTrend AI Dựa Trên Machine Learning
Phần này của mã nhằm phân tích và phân loại các vùng biến động cao, trung bình, và thấp dựa trên ATR.
Dựa trên AI Supper Trend, mã tính toán các trung tâm cụm dữ liệu và tạo các dải SuperTrend để chỉ ra sự biến động, hỗ trợ trader trong việc nắm bắt cơ hội giao dịch trong các điều kiện thị trường khác nhau.
Đường Zigzag và Double Bottom/Double Top
Mã có tích hợp đường zigzag để hiển thị các đỉnh và đáy, từ đó giúp xác định các mô hình đảo chiều như Double Bottom hoặc Double Top.
Điều kiện Mua/Bán chính
Mua khi Signal EMA cắt lên Trend EMA, xuất hiện Bullish Engulfing hoặc Bullish Pinbar, và giá đóng cửa trên Signal EMA kèm khối lượng lớn hơn trung bình 14 phiên.
Bán khi Signal EMA cắt xuống Trend EMA, xuất hiện Bearish Engulfing hoặc Bearish Pinbar, và giá đóng cửa dưới Signal EMA kèm khối lượng lớn hơn trung bình 14 phiên.
Chiến lược này hướng đến việc kết hợp các chỉ báo kỹ thuật và mô hình nến để tăng độ chính xác cho tín hiệu giao dịch. Với các chỉ báo như EMA, Keltner Channel, SuperTrend AI, và phân tích khối lượng, mã cho phép các trader nhận diện các cơ hội giao dịch tốt trong xu hướng và các điểm phá vỡ quan trọng.
sangram RSI Candlesticks//@version=5
indicator('sangram RSI Candlesticks', shorttitle='sangram RSI', overlay=false)
// RSI Settings
rsiPeriod = input.int(40, title='RSI Period', minval=1)
rsiSource = close
rsiValue = ta.rsi(rsiSource, rsiPeriod)
// Toggle Visibility
showRSILine = input(true, title='Make the RSI Glow')
showAllMA = input(true, title="Show ALL Moving Averages")
showMA1 = input(true, title='Show Moving Average 1')
showMA2 = input(true, title='Show Moving Average 2')
showMA3 = input(true, title='Show Moving Average 3')
showMA4 = input(true, title='Show Moving Average 4')
showBars = input(true, title='Show RSI OHLC Bars')
maLength1 = input.int(9, title='MA Length 1')
maLength2 = input.int(15, title='MA Length 2')
maLength3 = input.int(30, title='MA Length 3')
maLength4 = input.int(50, title='MA Length 4')
// Calculate OHLC Values for RSI
rsiOpen = na(rsiValue ) ? rsiValue : rsiValue
rsiHigh = ta.highest(rsiValue, rsiPeriod)
rsiLow = ta.lowest(rsiValue, rsiPeriod)
// Define Colors
barUpColor = color.new(color.green, 0)
barDownColor = color.new(color.red, 0)
barColor = rsiOpen < rsiValue ? barUpColor : barDownColor
// Plot RSI OHLC Bars
plotcandle(showBars ? rsiOpen : na, rsiHigh, rsiLow, rsiValue, title="RSI OHLC", color=barColor, wickcolor=color.new(color.white, 100), bordercolor=barColor)
// Horizontal Lines
hline(70, "Oversold", color.new(color.red, 80), linewidth = 2, linestyle = hline.style_solid)
hline(70, "Oversold", color.new(color.red, 85), linewidth = 12, linestyle = hline.style_solid)
hline(70, "Oversold", color.new(color.red, 90), linewidth = 24, linestyle = hline.style_solid)
hline(70, "Oversold", color.new(color.red, 95), linewidth = 36, linestyle = hline.style_solid)
hline(50, "Mid", color=color.gray)
hline(30, "Oversold", color.new(color.green, 80), linewidth = 2, linestyle = hline.style_solid)
hline(30, "Oversold", color.new(color.green, 85), linewidth = 12, linestyle = hline.style_solid)
hline(30, "Oversold", color.new(color.green, 90), linewidth = 24, linestyle = hline.style_solid)
hline(30, "Oversold", color.new(color.green, 95), linewidth = 36, linestyle = hline.style_solid)
// Plot RSI Line
rsiColor1 = color.new(color.blue, 30)
rsiColor2 = color.new(color.blue, 80)
rsiColor3 = color.new(color.blue, 85)
plot(showRSILine ? rsiValue : na, title='RSI', color=rsiColor1, linewidth=2)
plot(showRSILine ? rsiValue : na, title='RSI', color=rsiColor2, linewidth=10)
plot(showRSILine ? rsiValue : na, title='RSI', color=rsiColor3, linewidth=16)
// Moving Average
maValue1 = ta.sma(rsiValue, maLength1)
maValue2 = ta.sma(rsiValue, maLength2)
maValue3 = ta.sma(rsiValue, maLength3)
maValue4 = ta.sma(rsiValue, maLength4)
plot(showAllMA and showMA1 ? maValue1 : na, title='MA 1', color=color.green)
plot(showAllMA and showMA2 ? maValue2 : na, title='MA 2', color=color.fuchsia)
plot(showAllMA and showMA3 ? maValue3 : na, title='MA 3', color=color.red)
plot(showAllMA and showMA4 ? maValue4 : na, title='MA 4', color=color.red)
My System Tradding . Dragon.R3 StrategyChiến luojc following, với sonic R với tỷ lệ lợi nhuận trên 50%
50MA ATR BANDSDescription: This indicator plots ATR bands around a 50-period EMA across multiple timeframes (15-minute, hourly, daily, weekly, and monthly). It offers traders a visual guide to potential price ranges using volatility-based calculations:
1.ATR Calculations: Based on selected timeframes for finer analysis.
2.EMA Calculations: 50-period EMA to track trend direction.
3.Customization: Line width, display mode (Auto/User-defined), and plot styles.
Usage: This tool helps identify potential support and resistance levels with ATR-based bands, making it a valuable addition to trend-following and volatility strategies.
Auto Fibonacci LevelsPurpose of the Code:
This Pine Script™ code designed to automatically plot Fibonacci levels on a price chart based on a user-defined lookback period and other customizable settings. By identifying key Fibonacci levels within a specified lookback range, this indicator assists traders in determining potential support and resistance areas. It also allows for flexibility in reversing the trend direction, adding custom levels, and displaying labels for easy reference on the chart.
Key Components and Functionalities:
1. Inputs:
- `lookback` (Lookback): The number of bars to look back when calculating the highest and lowest prices for Fibonacci levels.
- `reverse`: Reverses the trend direction for calculating Fibonacci levels, useful when identifying retracements in both upward and downward trends.
- `lb` (Line Back): A secondary lookback parameter for adjusting the position of lines.
- Color and Label Settings: Options for customizing colors, labels, and whether to display prices at each Fibonacci level.
2. Fibonacci Levels:
- Sixteen Fibonacci levels are defined as inputs (`l1` to `l16`) with each having a customizable value (e.g., 0.236, 0.5, 1.618). This allows traders to select standard or custom Fibonacci levels.
- The calculated levels are dynamically adjusted based on the highest and lowest prices within the lookback period.
3. Price Range Calculation:
- `highest_price` and `lowest_price` are determined within the specified lookback range. These values form the range used to calculate Fibonacci retracement and extension levels.
4. Fibonacci Level Calculation:
- The script calculates the Fibonacci levels as a percentage of the range between the highest and lowest prices.
- Levels are adjusted for upward or downward trends based on user input (e.g., the `reverse` option) and Zigzag indicator direction.
5. Plotting Fibonacci Levels:
- Lines are drawn at each Fibonacci level with customizable colors that can form a gradient from one color to another (e.g., from lime to red).
- Labels with price and level values are also plotted beside each Fibonacci line, with options to toggle visibility and position.
6. Additional Lines:
- Lines representing the highest and lowest prices within the lookback range can be displayed as support and resistance levels for added reference.
Usage:
The Auto Fibonacci Levels indicator is designed for traders who utilize Fibonacci retracement and extension levels to identify potential support and resistance zones, reversal points, or trend continuations. This indicator enables:
- Quick visualization of Fibonacci levels without manual drawing.
- Customization of the levels and the ability to add unique Fibonacci levels.
- Identification of key support and resistance levels based on recent price action.
This tool is beneficial for traders focused on technical analysis and Fibonacci-based trading strategies.
Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
moshak adel//@version=5
indicator("2 indicator", precision=0, timeframe='', timeframe_gaps = true)
PhiSmoother(series float source, simple int length, simple float phase=3.7)=>
var array coefs = na
var int length_1 = length - 1
var float W = 0.0
if na(coefs)
coefs := array.new()
const float SQRT_PIx2 = math.sqrt(2.0 * math.pi)
const float MULTIPLIER = -0.5 / 0.93
var float length_2 = length * 0.52353
for int i=0 to length_1
float alpha = (i + phase - length_2) * MULTIPLIER
float beta = 1.0 / (0.2316419 * math.abs(alpha) + 1.0)
float phi = (math.exp(math.pow(alpha, 2) * -0.5)
*-0.398942280) * beta *
( 0.319381530 + beta *
(-0.356563782 + beta *
( 1.781477937 + beta *
(-1.821255978 + beta
* 1.330274429)))) + 1.011
if alpha < 0.0
phi := 1.0 - phi
float weight = phi / SQRT_PIx2
coefs.push(weight)
W += weight
float sma2 = math.avg(source, nz(source , source))
float E = 0.0
for int i=0 to length_1
E += coefs.get(i) * sma2
E / W
ema(series float source, simple float length)=>
float alpha = 2.0 / (length + 1)
var float smoothed = na
smoothed := alpha * source + (1.0 - alpha) * nz(smoothed , source)
dema(series float source, simple float length)=>
float ema1 = ema(source, length)
float ema2 = ema( ema1, length)
2.0 * ema1 - ema2
tema(series float source, simple float length)=>
float ema1 = ema(source, length)
float ema2 = ema( ema1, length)
float ema3 = ema( ema2, length)
(ema1 - ema2) * 3.0 + ema3
wma(series float source, simple int length)=>
float weight_sum = length * 0.5 * (length + 1)
float sum = 0.0
for int i=0 to length - 1
sum += source * (length - i)
sum / weight_sum
sma(series float source, simple int length)=>
float sum = ta.cum(source)
if bar_index < length - 1
sum / (bar_index + 1)
else
(sum - sum ) / length
filter(series float source,
simple int length,
simple float phase,
simple string style)=>
if length > 1
switch style
"PhiSmoother" => PhiSmoother(source, length, phase)
"EMA" => ema(source, length)
"DEMA" => dema(source, length)
"TEMA" => tema(source, length)
"WMA" => wma(source, length)
=> sma(source, length) // "SMA"
else
source
method get_score(series array source)=>
array scores = array.new()
for int i=0 to source.size() - 1
float current = source.get(i)
int score_sum = 0
for j = 0 to source.size() - 1
float check = source.get(j)
int polarity = i < j ? 1 : -1
if i != j
if current > check
score_sum += polarity
else
score_sum -= polarity
scores.push(score_sum)
scores
method net_score(series array scores)=>
int value = scores.size() - 1
float netScore = ((scores.avg() + value) / (value * 2.0) - 0.5) * 200.0
netScore
method get_color(series float score,
simple float transition_easing,
simple bool volatility_mode,
simple color rising_bullish,
simple color falling_bullish,
simple color falling_bearish,
simple color rising_bearish,
simple color rising_transition,
simple color falling_transition)=>
var color grad = na
float delta = score - nz(score , score)
color bullish = delta >= 0.0 ? rising_bullish : falling_bullish
color bearish = delta > 0.0 ? rising_bearish : falling_bearish
color transit = score > 0.0 ? (delta >= 0.0 ? rising_transition : falling_transition)
: (delta >= 0.0 ? falling_transition : rising_transition)
if volatility_mode
float easing = 0.01 * transition_easing
float crms = easing * math.sqrt(ta.cum(math.pow(math.abs(score), 2)) / (bar_index + 1))
grad := if score > 0.0
transition_easing > 0.0 ? color.from_gradient(score, 0.0, crms, transit, bullish) : bullish
else
transition_easing > 0.0 ? color.from_gradient(score, -crms, 0.0, bearish, transit) : bearish
else
grad := if score > 0.0
transition_easing > 0.0 ? color.from_gradient(score, 0.0, transition_easing, transit, bullish) : bullish
else
transition_easing > 0.0 ? color.from_gradient(score, -transition_easing, 0.0, bearish, transit) : bearish
grad
string common = "Common Controls"
float source = input.source( close, "Source", group=common)
string mode = input.string("Trend Strength", "Composite Cluster Mode", group=common, options= , tooltip="Trend Strength visualizes the directionality of the filter cluster. Volatility weights the score to the bandwidth of the cluster.")
string filter = input.string( "PhiSmoother", "Cluster Filter", group=common, options= , tooltip="Choose a filter to build the moving average cluster with.")
float phase = input.float ( 3.7, "PhiSmoother Phase", group=common, minval=0.0, step=0.1, tooltip="This allows for subtle adjustment (tweaking) of the phase/lag for PhiSmoother")
string cluster = "Cluster Options"
int spacing = input.int(3, "Cluster Dispersion", group=cluster, minval=1, maxval=10, tooltip="Choose the separation between the moving averages in the cluster.")
int upper_trim = input.int(0, "Cluster Trim - Upper:", group=cluster, inline="trim", minval=0, maxval=31)
int lower_trim = input.int(0, "Lower:", group=cluster, inline="trim", minval=0, maxval=31, tooltip="The 'Upper' parameter modifies the shortest period of the moving averages, whereas 'Lower' parameter adjusts the longest period. Increasing the upper value reduces sensitivity, while increasing the lower value heightens sensitivity.")
string output = "Composite Post Smoothing"
string post_smooth_filt = input.string("PhiSmoother", "PostSmooth - Filter:", group=output, inline="post", options= )
int post_smooth_len = input.int ( 1, "Length:", group=output, inline="post", minval=1, tooltip="Period of the cluster's post smoothing.")
string signal = "Composite Signal Settings"
string signal_filter = input.string("PhiSmoother", "Signal - Filter:", group=signal, inline="signal", options= )
int signal_length = input.int ( 20, "Length:", group=signal, inline="signal", minval=1, tooltip="Period of the momentum signal plot.")
color signal_color = input.color ( color.white, "Filter Color", group=signal)
string threshold = "Threshold Levels"
float upperLevel = input.float( 75.00, "Levels - Upper:", group=threshold, inline="level", minval= 1.0, maxval=99.0, step=2.0)
float lowerLevel = input.float(-75.00, "Lower:", group=threshold, inline="level", minval=-99.0, maxval=-1.0, step=2.0, tooltip="Fine-tune the thresholds to your liking")
string colors = "Coloring Preferences"
//bool candle_color = input.bool ( false, "Candle Coloring", group=colors)
float transition_easing = input.float( 50.0, "Transition Easing", group=colors, maxval= 100.0, minval=0.0, step=5.0, tooltip="Adjust the sensitivity to ranging conditions.")
bool fill_bg = input.bool ( true, "Fill Background", group=colors, inline= "fill")
int fill_alpha = input.int ( 85, "", group=colors, inline= "fill", minval=0, maxval=100)
color rising_bullish = input.color(#FFCC00, "Bullish Color", group=colors, inline= "bull")
color rising_transition = input.color(#9598A1, "Transition Color", group=colors, inline="range")
color falling_bearish = input.color(#5500CC, "Bearish Color", group=colors, inline= "bear")
var bool VOLATILITY_MODE_ON = mode == "Volatility"
price = input(title='Source', defval=close)
alpha = input.int(title='Combined Smoothness', defval=15, minval=1)
array filter_cluster = array.new(34)
filter_cluster.set( 0, source)
filter_cluster.set( 1, filter(source, spacing, phase, filter))
filter_cluster.set( 2, filter(source, 2 * spacing, phase, filter))
filter_cluster.set( 3, filter(source, 3 * spacing, phase, filter))
filter_cluster.set( 4, filter(source, 4 * spacing, phase, filter))
filter_cluster.set( 6, filter(source, 5 * spacing, phase, filter))
filter_cluster.set( 7, filter(source, 6 * spacing, phase, filter))
filter_cluster.set( 8, filter(source, 7 * spacing, phase, filter))
filter_cluster.set( 9, filter(source, 8 * spacing, phase, filter))
filter_cluster.set(10, filter(source, 9 * spacing, phase, filter))
filter_cluster.set(11, filter(source, 10 * spacing, phase, filter))
filter_cluster.set(12, filter(source, 11 * spacing, phase, filter))
filter_cluster.set(13, filter(source, 12 * spacing, phase, filter))
filter_cluster.set(14, filter(source, 13 * spacing, phase, filter))
filter_cluster.set(15, filter(source, 14 * spacing, phase, filter))
filter_cluster.set(16, filter(source, 15 * spacing, phase, filter))
filter_cluster.set(17, filter(source, 16 * spacing, phase, filter))
filter_cluster.set(18, filter(source, 17 * spacing, phase, filter))
filter_cluster.set(19, filter(source, 18 * spacing, phase, filter))
filter_cluster.set(20, filter(source, 19 * spacing, phase, filter))
filter_cluster.set(21, filter(source, 20 * spacing, phase, filter))
filter_cluster.set(22, filter(source, 21 * spacing, phase, filter))
filter_cluster.set(23, filter(source, 22 * spacing, phase, filter))
filter_cluster.set(24, filter(source, 23 * spacing, phase, filter))
filter_cluster.set(25, filter(source, 24 * spacing, phase, filter))
filter_cluster.set(26, filter(source, 25 * spacing, phase, filter))
filter_cluster.set(27, filter(source, 26 * spacing, phase, filter))
filter_cluster.set(28, filter(source, 27 * spacing, phase, filter))
filter_cluster.set(29, filter(source, 28 * spacing, phase, filter))
filter_cluster.set(30, filter(source, 29 * spacing, phase, filter))
filter_cluster.set(31, filter(source, 30 * spacing, phase, filter))
filter_cluster.set(32, filter(source, 31 * spacing, phase, filter))
filter_cluster.set(33, filter(source, 32 * spacing, phase, filter))
if upper_trim > 0
for int i=0 to math.min(upper_trim - 1, filter_cluster.size() - 1)
if filter_cluster.size() > 2
filter_cluster.shift()
else
break
if lower_trim > 0
for int i=0 to math.min(lower_trim - 1, filter_cluster.size() - 1)
if filter_cluster.size() > 2
filter_cluster.pop()
else
break
float ribbon_max = filter_cluster.max()
float ribbon_min = filter_cluster.min()
float ribbon_width = ribbon_max - ribbon_min
float ribbon_rank = VOLATILITY_MODE_ON ? nz(ribbon_width / math.avg(ribbon_max, ribbon_min)) : 1
array score = filter_cluster.get_score()
float net_score = filter(score.net_score() * ribbon_rank, post_smooth_len, 3.7, post_smooth_filt)
float signal_value = signal_length < 2 ? na : filter(ta.sma(net_score, 2), signal_length, 3.7, signal_filter)
top = hline(VOLATILITY_MODE_ON ? na : 100.0, "Top", #FF0000)
upper = hline(VOLATILITY_MODE_ON ? na : upperLevel, "+Level", rising_bullish, hline.style_dotted, 2)
center = hline( 0.0, "Center", #CCCCCC)
lower = hline(VOLATILITY_MODE_ON ? na : lowerLevel, "+Level", falling_bearish, hline.style_dotted, 2)
bottom = hline(VOLATILITY_MODE_ON ? na : -100.0, "Bottom", #00FF00)
const color invisible = #00000000
fill( top, upper, 100.0, upperLevel, #800000, invisible)
fill(center, upper, upperLevel, 0.0, color.new( rising_bullish, 100), color.new(rising_bullish, fill_bg ? fill_alpha : 100))
fill(center, lower, 0.0, lowerLevel, color.new(falling_bearish, fill_bg ? fill_alpha : 100), color.new(falling_bearish, 100))
fill(bottom, lower, lowerLevel, -100.0, invisible, #008000)
//barcolor(candle_color ? main_color : na)
color1 = net_score>signal_value ? #00FF00 : #ff0000
net = plot(net_score, "Score", color1, 3)
zero = plot( 0.0, "", invisible)
plot(signal_value, "Signal", signal_color, 1)
fill(net, zero, net_score > 0.0 ? net_score : 0.0,
net_score > 0.0 ? 0.0 : net_score,
net_score > 0.0 ? color.new(rising_bullish, fill_bg and VOLATILITY_MODE_ON ? fill_alpha : 100) : color.new(falling_bearish, 100),
net_score > 0.0 ? color.new(rising_bullish, 100) : color.new(falling_bearish, fill_bg and VOLATILITY_MODE_ON ? fill_alpha : 100))
//===============================================
f_LazyLine(_data, _length) =>
w1 = 0
w2 = 0
w3 = 0
L1 = 0.0
L2 = 0.0
L3 = 0.0
w = _length / 3
if _length > 2
w2 := math.round(w)
w1 := math.round((_length - w2) / 2)
w3 := int((_length - w2) / 2)
L1 := ta.wma(_data, w1)
L2 := ta.wma(L1, w2)
L3 := ta.wma(L2, w3)
L3
else
L3 := _data
L3
L3
//====================================
LL = f_LazyLine(price, alpha)
c_up = color.new(#33ff00, 0)
c_dn = color.new(#ff1111, 0)
uptrend = LL > LL
plot(LL, 'SS_WMA Line', color=uptrend ? c_up : c_dn, linewidth=3,force_overlay=true)
plot(ta.wma(price, alpha), 'WMA', color=color.new(color.purple, 0), display=display.none,force_overlay=true)
// ========================================================================================================================
// v2: add optional up/dn arrow signal on change of direction (swing)
ShowSig = input(title='Up/Dn Swing Signal?', defval=false)
SigMulti = input.float(title='Signal Locator %', defval=1.0, step=0.2, minval=0, maxval=20)
SignalOn = ShowSig and barstate.isconfirmed // ensure the signal plots *only* after "the bar closes" :) -- insert jokes :)
SwingDn = uptrend and not uptrend
SwingUp = uptrend and not uptrend
d = SigMulti / 100 * LL //we'll use this to tweak a good location for the signal (that is not tied to price-specific parameters)
plotshape(SignalOn and SwingDn ? LL + d : na, title='Swing Down', style=shape.triangledown, location=location.absolute, size=size.small, color=c_dn,force_overlay=true)
plotshape(SignalOn and SwingUp ? LL - d : na, title='Swing Up', style=shape.triangleup, location=location.absolute, size=size.small, color=c_up,force_overlay=true)
// ========================================================================================================================
// v3: enable alerts
// need to use alertcondition() to support variable resolution
alertcondition(SwingUp, 'Swing Up', 'Swing Up Detected!') // explicit swing up
alertcondition(SwingDn, 'Swing Down', 'Swing Down Detected!') // explicit swing down
alertcondition(SwingUp or SwingDn, 'Swing', 'Up/Down Swing Detected!') // either swings
Volume Flow ConfluenceVolume Flow Confluence (CMF-KVO Integration)
Core Function:
The Volume Flow Confluence Indicator combines two volume-analysis methods: Chaikin Money Flow (CMF) and the Klinger Volume Oscillator (KVO). It displays a histogram only when both indicators align in their respective signals.
Signal States:
• Green Bars: CMF is positive (> 0) and KVO is above its signal line
• Red Bars: CMF is negative (< 0) and KVO is below its signal line
• No Bars: When indicators disagree
Technical Components:
Chaikin Money Flow (CMF):
Measures the relationship between volume and price location within the trading range:
• Calculates money flow volume using close position relative to high/low range
• Aggregates and normalizes over specified period
• Default period: 20
Klinger Volume Oscillator (KVO):
Evaluates volume in relation to price movement:
• Tracks trend changes using HLC3
• Applies volume force calculation
• Uses two EMAs (34/55) with a signal line (13)
Practical Applications:
1. Signal Identification
- New colored bars after blank periods show new agreement between indicators
- Color intensity differentiates new signals from continuations
- Blank spaces indicate lack of agreement
2. Trend Analysis
- Consecutive colored bars show continued indicator agreement
- Transitions between colors or to blank spaces show changing conditions
- Can be used alongside other technical analysis tools
3. Risk Considerations
- Signals are not predictive of future price movement
- Should be used as one of multiple analysis tools
- Effectiveness may vary across different markets and timeframes
Technical Specifications:
Core Algorithm
CMF = Σ(((C - L) - (H - C))/(H - L) × V)n / Σ(V)n
KVO = EMA(VF, 34) - EMA(VF, 55)
Where VF = V × |2(dm/cm) - 1| × sign(Δhlc3)
Signal Line = EMA(KVO, 13)
Signal Logic
Long: CMF > 0 AND KVO > Signal
Short: CMF < 0 AND KVO < Signal
Neutral: All other conditions
Parameters
CMF Length = 20
KVO Fast = 34
KVO Slow = 55
KVO Signal = 13
Volume = Regular/Actual Volume
Data Requirements
Price Data: OHLC
Volume Data: Required
Minimum History: 55 bars
Recommended Timeframe: ≥ 1H
Credits:
• Marc Chaikin - Original CMF development
• Stephen Klinger - Original KVO development
• Alex Orekhov (everget) - CMF script implementation
• nj_guy72 - KVO script implementation
Rikki's DikFat Bull/Bear OscillatorRikki's DikFat Bull/Bear Oscillator - Trend Identification & Candle Colorization
Rikki's DikFat Bull/Bear Oscillator is a powerful visual tool designed to help traders easily identify bullish and bearish trends on the chart. By analyzing market momentum using specific elements of the Commodity Channel Index (CCI) , this indicator highlights key trend reversals and continuations with color-coded candles, allowing you to quickly spot areas of opportunity.
How It Works
At the heart of this indicator is the Commodity Channel Index (CCI) , a popular momentum-based oscillator. The CCI measures the deviation of price from its average over a specified period (default is 30 bars). This helps identify whether the market is overbought, oversold, or trending.
Here's how the indicator interprets the CCI:
Bullish Trend (Green Candles) : When the market is showing signs of continued upward momentum, the candles turn green. This happens when the current CCI is less than 200 and moves from a value greater than 100 with velocity, signaling that the upward trend is still strong, and the market is likely to continue rising. Green candles indicate bullish price action , suggesting it might be a good time to look for buying opportunities or hold your current long position.
Bearish Trend (Red Candles) : Conversely, when the CCI shows signs of downward momentum (both the current and previous CCI readings are negative), the candles turn red. This signals that the market is likely in a bearish trend , with downward price action expected to continue. Red candles are a visual cue to consider selling opportunities or to stay out of the market if you're risk-averse.
How to Use It
Bullish Market : When you see green candles, the market is in a bullish phase. This suggests that prices are moving upward, and you may want to focus on buying signals . Green candles are your visual confirmation of a strong upward trend.
Bearish Market : When red candles appear, the market is in a bearish phase. This indicates that prices are moving downward, and you may want to consider selling or staying out of long positions. Red candles signal that downward pressure is likely to continue.
Why It Works
This indicator uses momentum to identify shifts in trend. By tracking the movement of the CCI , the oscillator detects whether the market is trending strongly or simply moving in a sideways range. The color changes in the candles help you quickly visualize where the market momentum is headed, giving you an edge in determining potential buy or sell opportunities.
Clear Visual Signals : The green and red candles make it easy to follow market trends, even for beginners.
Identifying Trend Continuations : The oscillator helps spot ongoing trends, whether bullish or bearish, so you can align your trades with the prevailing market direction.
Quick Decision-Making : By using color-coded candles, you can instantly know whether to consider entering a long (buy) or short (sell) position without needing to dive into complex indicators.
NOTES This indicator draws and colors it's own candles bodies, wicks and borders. In order to have the completed visualization of red and green trends, you may need to adjust your TradingView chart settings to turn off or otherwise modify chart candles.
Conclusion
With Rikki's DikFat Bull/Bear Oscillator , you have an intuitive and easy-to-read tool that helps identify bullish and bearish trends based on proven momentum indicators. Whether you’re a novice or an experienced trader, this oscillator allows you to stay in tune with the market’s direction and make more informed, confident trading decisions.
Make sure to use this indicator in conjunction with your own trading strategy and risk management plan to maximize your trading potential and limit your risks.
Directional Volatility and Volume with Three ATR Bandsadded some effects on @PuguForex indiactor " Directional Volatility and Volume "using chatgpt
would like some help crating exiting stuff since am lazy on these kind of stuff but consider of having of some what some brain
long/short price hits red
high win-rate or breakeven low losses (AT YOUR OWN COST)
small percentage add up
play with yellow on your cost
better using DCA on reds to see better result to avoid extreme case seniors multiplying it
exept if your going oppisite of the narritive / cycle / market / flow than your a ignorrant / cursed / stupid (sorry)
(maybe some updated edits coming on the way)
THANK ALLAH ALL TIME AND ASK FOR HIS FORGIVNESS AS YOUR A LIVE NO TIME LEFT
WORSHIP HIM ALONE WITH NO CAMPANIONS
PEACE AND MERCY AND BLESSING TO YOU
Trade Mavrix: Elite Trade NavigatorYour ultimate trading companion that helps you spot profitable breakouts, perfect pullbacks, and crucial support & resistance levels. Ready to take your trading to the next level? Let's dive in!
PRADEEP Scalping Buy/Sell TIME FRAME : 5MIN ONLY
BUY : Only above EMA 50 ( Higher Probabilities above VWAP and EMA 50)
SELl : Only below EMA 50 ( Higher Probabilities below VWAP and EMA 50)
Confluence Indicator with Buy/Sell Crosses### Explicação do Funcionamento do Indicador "Confluence Indicator with Buy/Sell Crosses": Este indicador combina múltiplos fatores de análise técnica para gerar sinais de compra e venda com base em condições específicas de sobrecompra/sobrevenda, resistência e suporte, além da confluência com uma média móvel, o **DonForex T2**. Aqui está uma explicação de como ele funciona: #### 1. **RSI (Índice de Força Relativa)**: - O **RSI** é usado para medir a força do movimento de preços e identificar condições de sobrecompra e sobrevenda. Ele varia de 0 a 100, com: - **RSI > 70**: O mercado está **sobrecomprado**, o que sugere uma possível reversão para baixo. - **RSI < 30**: O mercado está **sobrevendido**, o que sugere uma possível reversão para cima. O indicador gera um sinal de venda quando o **RSI** está acima de 70 (sobrecompra) e um sinal de compra quando o **RSI** está abaixo de 30 (sobrevenda). #### 2. **Suporte e Resistência**: - **Resistência**: O nível de preço mais alto observado nos últimos **30 candles** é considerado uma resistência. Quando o preço atinge ou ultrapassa esse nível, isso sugere que pode haver uma reversão de preço para baixo. - **Suporte**: O nível de preço mais baixo observado nos últimos **30 candles** é considerado um suporte. Quando o preço atinge ou ultrapassa esse nível para cima, isso sugere que pode haver uma reversão de preço para cima. O indicador gera um sinal de **venda** quando o preço atinge ou ultrapassa o nível de **resistência**, e um sinal de **compra** quando o preço atinge ou ultrapassa o nível de **suporte**. #### 3. **Confluência com DonForex T2 (Média Móvel Exponencial)**: - O **DonForex T2** é um indicador simulado baseado em uma **Média Móvel Exponencial (EMA)** de 14 períodos. Essa média ajuda a suavizar as flutuações do preço e servir como uma referência adicional para a tendência. - O sinal de **venda** ocorre quando o preço está **acima da resistência** e também **acima** da linha DonForex T2 (indicando uma tendência de alta). - O sinal de **compra** ocorre quando o preço está **abaixo do suporte** e também **abaixo** da linha DonForex T2 (indicando uma tendência de baixa). #### 4. **Geração de Sinais**: - **Sinal de Compra (Buy)**: - O preço está **abaixo do suporte**. - O **RSI** está **abaixo de 30** (indicando sobrevenda). - O preço também está **abaixo do DonForex T2**, o que pode sugerir que o preço está em uma fase de retração e pronto para uma reversão para cima. Se essas condições forem atendidas, o indicador gerará um **sinal de compra** com uma **cruz verde** abaixo da vela, indicando uma possível oportunidade de compra. - **Sinal de Venda (Sell)**: - O preço está **acima da resistência**. - O **RSI** está **acima de 70** (indicando sobrecompra). - O preço também está **acima do DonForex T2**, o que pode sugerir que o preço está em uma fase de expansão e pronto para uma reversão para baixo. Se essas condições forem atendidas, o indicador gerará um **sinal de venda** com uma **cruz vermelha** acima da vela, indicando uma possível oportunidade de venda. #### 5. **Visualização no Gráfico**: - **Cruz Verde**: Aparece **abaixo da vela** quando há um sinal de **compra**. - **Cruz Vermelha**: Aparece **acima da vela** quando há um sinal de **venda**. - Além disso, **marcas de RSI** sobrevendido (verde) e sobrecomprado (vermelho) também são desenhadas para ajudar na visualização e entender melhor o comportamento do mercado. #### 6. **Objetivo do Indicador**: O objetivo do indicador é **identificar pontos de reversão** no gráfico baseados na confluência de múltiplos fatores: - O **RSI** ajuda a capturar condições de sobrecompra e sobrevenda. - O **suporte e resistência** ajudam a identificar zonas de reversão de preço. - A **média móvel DonForex T2** atua como um filtro adicional para confirmar a direção da ten
