TechniTrend: Volatility and MACD Trend Highlighter🟦 Overview
The "Candle Volatility with Trend Prediction" indicator is a powerful tool designed to identify market volatility based on candle movement relative to average volume while also incorporating trend predictions using the MACD. This indicator is ideal for traders who want to detect volatile market conditions and anticipate potential price movements, leveraging both price changes and volume dynamics.
It not only highlights candles with significant price movements but also integrates a trend analysis based on the MACD (Moving Average Convergence Divergence), allowing traders to gauge whether the market momentum aligns with or diverges from the detected volatility.
🟦 Key Features
🔸Volatility Detection: Identifies candles that exceed normal price fluctuations based on average volume and recent price volatility.
🔸Trend Prediction: Uses the MACD indicator to overlay trend analysis, signaling potential market direction shifts.
🔸Volume-Based Analysis: Integrates customizable moving averages (SMA, EMA, WMA, etc.) of volume, providing a clear visualization of volume trends.
🔸Alert System: Automatically notifies traders of high-volatility situations, aiding in timely decision-making.
🔸Customizability: Includes multiple settings to tailor the indicator to different market conditions and timeframes.
🟦 How It Works
The indicator operates by evaluating the price volatility in relation to average volume and identifying when a candle's volatility surpasses a threshold defined by the user. The key calculations include:
🔸Average Volume Calculation: The user selects the type of moving average (SMA, EMA, etc.) to calculate the average volume over a set period.
🔸Volatility Measurement: The indicator measures the body change (difference between open and close) and the high-low range of each candle. It then calculates recent price volatility using a standard deviation over a user-defined length.
🔸Weighted Index: A unique index is created by dividing price change by average volume and recent volatility.
🔸Highlighting Volatility: If the weighted index exceeds a customizable threshold, the candle is highlighted, indicating potential trading opportunities.
🔸Trend Analysis with MACD: The MACD line and signal line are plotted and adjusted with a user-defined multiplier to visualize trends alongside the volatility signals.
🟦 Recommended Settings
🔸Volume MA Length: A default of 14 periods for the average volume calculation is recommended. Adjust to higher periods for long-term trends and shorter periods for quick trades.
🔸Volatility Threshold Multiplier: Set at 1.2 by default to capture moderately significant movements. Increase for fewer but stronger signals or decrease for more frequent signals.
🔸MACD Settings: Default MACD parameters (12, 26, 9) are suggested. Tweak based on your trading strategy and asset volatility.
🔸MACD Multiplier: Adjust based on how the MACD should visually compare to the average volume. A multiplier of 1 works well for most cases.
🟦 How to Use
🔸Volatile Market Detection:
Look for highlighted candles that suggest a deviation from typical price behavior. These candles often signify an entry point for short-term trades.
🔸Trend Confirmation:
Use the MACD trend analysis to verify if the highlighted volatile candles align with a bullish or bearish trend.
For example, a bullish MACD crossover combined with a highlighted candle suggests a potential uptrend, while a bearish crossover with volatility signals may indicate a downtrend.
🔸Volume-Driven Strategy:
Observe how volume changes impact candle volatility. When volume rises significantly and candles are highlighted, it can suggest strong market moves influenced by big players.
🟦 Best Use Cases
🔸Trend Reversals: Detect potential trend reversals early by spotting divergences between price and MACD within volatile conditions.
🔸Breakout Strategies: Use the indicator to confirm price breakouts with significant volume changes.
🔸Scalping or Day Trading: Customize the indicator for shorter timeframes to capture rapid market movements based on volatility spikes.
🔸Swing Trading: Combine volatility and trend insights to optimize entry and exit points over longer periods.
🟦 Customization Options
🔸Volume-Based Inputs: Choose from SMA, EMA, WMA, and more to define how average volume is calculated.
🔸Threshold Adjustments: Modify the volatility threshold multiplier to increase or decrease sensitivity based on your trading style.
🔸MACD Tuning: Adjust MACD settings and the multiplier for trend visualization tailored to different asset classes and market conditions.
🟦 Indicator Alerts
🔸High Volatility Alerts: Automatically triggered when candles exceed user-defined volatility levels.
🔸Bullish/Bearish Trend Alerts: Alerts are activated when highlighted volatile candles align with bullish or bearish MACD crossovers, making it easier to spot opportunities without constantly monitoring the chart.
🟦 Examples of Use
To better understand how this indicator works, consider the following scenarios:
🔸Example 1: In a strong uptrend, observe how volume surges and volatility highlight candles right before price consolidations, indicating optimal exit points.
🔸Example 2: During a downtrend, see how the MACD aligns with volume-driven volatility, signaling potential short-selling opportunities.
在脚本中搜索"crossover债券是什么"
Fibonacci ATR Fusion - Strategy [presentTrading]Open-script again! This time is also an ATR-related strategy. Enjoy! :)
If you have any questions, let me know, and I'll help make this as effective as possible.
█ Introduction and How It Is Different
The Fibonacci ATR Fusion Strategy is an advanced trading approach that uniquely integrates Fibonacci-based weighted averages with the Average True Range (ATR) to identify and capitalize on significant market trends.
Unlike traditional strategies that rely on single indicators or static parameters, this method combines multiple timeframes and dynamic volatility measurements to enhance precision and adaptability. Additionally, it features a 4-step Take Profit (TP) mechanism, allowing for systematic profit-taking at various levels, which optimizes both risk management and return potential in long and short market positions.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The Fibonacci ATR Fusion Strategy utilizes a combination of technical indicators and weighted averages to determine optimal entry and exit points. Below is a breakdown of its key components and operational logic.
🔶 1. Enhanced True Range Calculation
The strategy begins by calculating the True Range (TR) to measure market volatility accurately.
TR = max(High - Low, abs(High - Previous Close), abs(Low - Previous Close))
High and Low: Highest and lowest prices of the current trading period.
Previous Close: Closing price of the preceding trading period.
max: Selects the largest value among the three calculations to account for gaps and limit movements.
🔶 2. Buying Pressure (BP) Calculation
Buying Pressure (BP) quantifies the extent to which buyers are driving the price upwards within a period.
BP = Close - True Low
Close: Current period's closing price.
True Low: The lower boundary determined in the True Range calculation.
🔶 3. Ratio Calculation for Different Periods
To assess the strength of buying pressure relative to volatility, the strategy calculates a ratio over various Fibonacci-based timeframes.
Ratio = 100 * (Sum of BP over n periods) / (Sum of TR over n periods)
n: Length of the period (e.g., 8, 13, 21, 34, 55).
Sum of BP: Cumulative Buying Pressure over n periods.
Sum of TR: Cumulative True Range over n periods.
This ratio normalizes buying pressure, making it comparable across different timeframes.
🔶 4. Weighted Average Calculation
The strategy employs a weighted average of ratios from multiple Fibonacci-based periods to smooth out signals and enhance trend detection.
Weighted Avg = (w1 * Ratio_p1 + w2 * Ratio_p2 + w3 * Ratio_p3 + w4 * Ratio_p4 + Ratio_p5) / (w1 + w2 + w3 + w4 + 1)
w1, w2, w3, w4: Weights assigned to each ratio period.
Ratio_p1 to Ratio_p5: Ratios calculated for periods p1 to p5 (e.g., 8, 13, 21, 34, 55).
This weighted approach emphasizes shorter periods more heavily, capturing recent market dynamics while still considering longer-term trends.
🔶 5. Simple Moving Average (SMA) of Weighted Average
To further smooth the weighted average and reduce noise, a Simple Moving Average (SMA) is applied.
Weighted Avg SMA = SMA(Weighted Avg, m)
- m: SMA period (e.g., 3).
This smoothed line serves as the primary signal generator for trade entries and exits.
🔶 6. Trading Condition Thresholds
The strategy defines specific threshold values to determine optimal entry and exit points based on crossovers and crossunders of the SMA.
Long Condition = Crossover(Weighted Avg SMA, Long Entry Threshold)
Short Condition = Crossunder(Weighted Avg SMA, Short Entry Threshold)
Long Exit = Crossunder(Weighted Avg SMA, Long Exit Threshold)
Short Exit = Crossover(Weighted Avg SMA, Short Exit Threshold)
Long Entry Threshold (T_LE): Level at which a long position is triggered.
Short Entry Threshold (T_SE): Level at which a short position is triggered.
Long Exit Threshold (T_LX): Level at which a long position is exited.
Short Exit Threshold (T_SX): Level at which a short position is exited.
These conditions ensure that trades are only executed when clear trends are identified, enhancing the strategy's reliability.
Previous local performance
🔶 7. ATR-Based Take Profit Mechanism
When enabled, the strategy employs a 4-step Take Profit system to systematically secure profits as the trade moves in the desired direction.
TP Price_1 Long = Entry Price + (TP1ATR * ATR Value)
TP Price_2 Long = Entry Price + (TP2ATR * ATR Value)
TP Price_3 Long = Entry Price + (TP3ATR * ATR Value)
TP Price_1 Short = Entry Price - (TP1ATR * ATR Value)
TP Price_2 Short = Entry Price - (TP2ATR * ATR Value)
TP Price_3 Short = Entry Price - (TP3ATR * ATR Value)
- ATR Value: Calculated using ATR over a specified period (e.g., 14).
- TPxATR: User-defined multipliers for each take profit level.
- TPx_percent: Percentage of the position to exit at each TP level.
This multi-tiered exit strategy allows for partial position closures, optimizing profit capture while maintaining exposure to potential further gains.
█ Trade Direction
The Fibonacci ATR Fusion Strategy is designed to operate in both long and short market conditions, providing flexibility to traders in varying market environments.
Long Trades: Initiated when the SMA of the weighted average crosses above the Long Entry Threshold (T_LE), indicating strong upward momentum.
Short Trades: Initiated when the SMA of the weighted average crosses below the Short Entry Threshold (T_SE), signaling robust downward momentum.
Additionally, the strategy can be configured to trade exclusively in one direction—Long, Short, or Both—based on the trader’s preference and market analysis.
█ Usage
Implementing the Fibonacci ATR Fusion Strategy involves several steps to ensure it aligns with your trading objectives and market conditions.
1. Configure Strategy Parameters:
- Trading Direction: Choose between Long, Short, or Both based on your market outlook.
- Trading Condition Thresholds: Set the Long Entry, Short Entry, Long Exit, and Short Exit thresholds to define when to enter and exit trades.
2. Set Take Profit Levels (if enabled):
- ATR Multipliers: Define how many ATRs away from the entry price each take profit level is set.
- Take Profit Percentages: Allocate what percentage of the position to close at each TP level.
3. Apply to Desired Chart:
- Add the strategy to the chart of the asset you wish to trade.
- Observe the plotted Fibonacci ATR and SMA Fibonacci ATR indicators for visual confirmation.
4. Monitor and Adjust:
- Regularly review the strategy’s performance through backtesting.
- Adjust the input parameters based on historical performance and changing market dynamics.
5. Risk Management:
- Ensure that the sum of take profit percentages does not exceed 100% to avoid over-closing positions.
- Utilize the ATR-based TP levels to adapt to varying market volatilities, maintaining a balanced risk-reward ratio.
█ Default Settings
Understanding the default settings is crucial for optimizing the Fibonacci ATR Fusion Strategy's performance. Here's a precise and simple overview of the key parameters and their effects:
🔶 Key Parameters and Their Effects
1. Trading Direction (`tradingDirection`)
- Default: Both
- Effect: Determines whether the strategy takes both long and short positions or restricts to one direction. Selecting Both allows maximum flexibility, while Long or Short can be used for directional bias.
2. Trading Condition Thresholds
Long Entry (long_entry_threshold = 58.0): Higher values reduce false positives but may miss trades.
Short Entry (short_entry_threshold = 42.0): Lower values capture early short trends but may increase false signals.
Long Exit (long_exit_threshold = 42.0): Exits long positions early, securing profits but potentially cutting trends short.
Short Exit (short_exit_threshold = 58.0): Delays short exits to capture favorable movements, avoiding premature exits.
3. Take Profit Configuration (`useTakeProfit` = false)
- Effect: When enabled, the strategy employs a 4-step TP mechanism to secure profits at multiple levels. By default, it is disabled to allow users to opt-in based on their trading style.
4. ATR-Based Take Profit Multipliers
TP1 (tp1ATR = 3.0): Sets the first TP at 3 ATRs for initial profit capture.
TP2 (tp2ATR = 8.0): Targets larger trends, though less likely to be reached.
TP3 (tp3ATR = 14.0): Optimizes for extreme price moves, seldom triggered.
5. Take Profit Percentages
TP Level 1 (tp1_percent = 12%): Secures 12% at the first TP.
TP Level 2 (tp2_percent = 12%): Exits another 12% at the second TP.
TP Level 3 (tp3_percent = 12%): Closes an additional 12% at the third TP.
6. Weighted Average Parameters
Ratio Periods: Fibonacci-based intervals (8, 13, 21, 34, 55) balance responsiveness.
Weights: Emphasizes recent data for timely responses to market trends.
SMA Period (weighted_avg_sma_period = 3): Smoothens data with minimal lag, balancing noise reduction and responsiveness.
7. ATR Period (`atrPeriod` = 14)
Effect: Sets the ATR calculation length, impacting TP sensitivity to volatility.
🔶 Impact on Performance
- Sensitivity and Responsiveness:
- Shorter Ratio Periods and Higher Weights: Make the weighted average more responsive to recent price changes, allowing quicker trade entries and exits but increasing the likelihood of false signals.
- Longer Ratio Periods and Lower Weights: Provide smoother signals with fewer false positives but may delay trade entries, potentially missing out on significant price moves.
- Profit Taking:
- ATR Multipliers: Higher multipliers set take profit levels further away, targeting larger price movements but reducing the probability of reaching these levels.
- Fixed Percentages: Allocating equal percentages at each TP level ensures consistent profit realization and risk management, preventing overexposure.
- Trade Direction Control:
- Selecting Specific Directions: Restricting trades to Long or Short can align the strategy with market trends or personal biases, potentially enhancing performance in trending markets.
- Risk Management:
- Take Profit Percentages: Dividing the position into smaller percentages at multiple TP levels helps lock in profits progressively, reducing risk and allowing the remaining position to ride further trends.
- Market Adaptability:
- Weighted Averages and ATR: By combining multiple timeframes and adjusting to volatility, the strategy adapts to different market conditions, maintaining effectiveness across various asset classes and timeframes.
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If you want to know more about ATR, can also check "SuperATR 7-Step Profit".
Enjoy trading.
Price Movement Predictor (PMP)The Price Movement Predictor (PMP) is a versatile trading indicator designed to assist traders in identifying potential buy and sell opportunities in the market. This indicator utilizes a combination of technical analysis tools to generate signals based on the relative strength index (RSI) and moving averages, ensuring a robust and strategic approach to trading.
Key Features:
RSI-Based Signal Generation:
The indicator monitors the RSI to identify overbought and oversold conditions in the market.
A buy signal is generated when the RSI drops below a predefined oversold threshold, indicating potential upward price movement.
Conversely, a sell signal is triggered when the RSI exceeds a specified overbought level, suggesting a possible price decline.
Moving Average Confirmation:
The indicator employs two moving averages: a short-term and a long-term moving average.
Buy and sell signals are confirmed only after a crossover event occurs, ensuring that trades are entered in alignment with market trends.
The short moving average crossing above the long moving average confirms a buy signal, while a crossover below confirms a sell signal.
Take Profit and Stop Loss Management:
The PMP includes adjustable take profit and stop loss levels, which are automatically calculated based on user-defined percentages.
Labels indicating the take profit (TP) and stop loss (SL) levels are plotted on the chart, helping traders manage their risk effectively.
Alerts are available for both TP and SL conditions, allowing traders to stay informed about their trade outcomes.
User-Friendly Interface:
The indicator provides an intuitive setup with adjustable parameters for moving average lengths, RSI levels, and TP/SL ratios.
Clear buy and sell signals are displayed directly on the chart, making it easy for traders to act on potential opportunities.
Usage:
The Price Movement Predictor is ideal for traders who seek a systematic approach to identify trading opportunities and manage risk. By combining RSI signals with moving average crossovers, the indicator helps filter out false signals and enhances the accuracy of trade entries. It is suitable for various trading styles, including day trading, swing trading, and long-term investing.
Z-Score RSI StrategyOverview
The Z-Score RSI Indicator is an experimental take on momentum analysis. By applying the Relative Strength Index (RSI) to a Z-score of price data, it measures how far prices deviate from their mean, scaled by standard deviation. This isn’t your traditional use of RSI, which is typically based on price data alone. Nevertheless, this unconventional approach can yield unique insights into market trends and potential reversals.
Theory and Interpretation
The RSI calculates the balance between average gains and losses over a set period, outputting values from 0 to 100. Typically, people look at the overbought or oversold levels to identify momentum extremes that might be likely to lead to a reversal. However, I’ve often found that RSI can be effective for trend-following when observing the crossover of its moving average with the midline or the crossover of the RSI with its own moving average. These crossovers can provide useful trend signals in various market conditions.
By combining RSI with a Z-score of price, this indicator estimates the relative strength of the price’s distance from its mean. Positive Z-score trends may signal a potential for higher-than-average prices in the near future (scaled by the standard deviation), while negative trends suggest the opposite. Essentially, when the Z-Score RSI indicates a trend, it reflects that the Z-score (the distance between the average and current price) is likely to continue moving in the trend’s direction. Generally, this signals a potential price movement, though it’s important to note that this could also occur if there’s a shift in the mean or standard deviation, rather than a meaningful change in price itself.
While the Z-Score RSI could be an insightful addition to a comprehensive trading system, it should be interpreted carefully. Mean shifts may validate the indicator’s predictions without necessarily indicating any notable price change, meaning it’s best used in tandem with other indicators or strategies.
Recommendations
Before putting this indicator to use, conduct thorough backtesting and avoid overfitting. The added parameters allow fine-tuning to fit various assets, but be careful not to optimize purely for the highest historical returns. Doing so may create an overly tailored strategy that performs well in backtests but fails in live markets. Keep it balanced and look for robust performance across multiple scenarios, as overfitting is likely to lead to disappointing real-world results.
DSL Strategy [DailyPanda]
Overview
The DSL Strategy by DailyPanda is a trading strategy that synergistically combines the idea from indicators to create a more robust and reliable trading tool. By integrating these indicators, the strategy enhances signal accuracy and provides traders with a comprehensive view of market trends and momentum shifts. This combination allows for better entry and exit points, improved risk management, and adaptability to various market conditions.
Combining ideas from indicators adds value by:
Enhancing Signal Confirmation : The strategy requires alignment between trend and momentum before generating trade signals, reducing false entries.
Improving Accuracy : By integrating price action with momentum analysis, the strategy captures more reliable trading opportunities.
Providing Comprehensive Market Insight : The combination offers a better perspective on the market, considering both the direction (trend) and the strength (momentum) of price movements.
How the Components Work Together
1. Trend Identification with DSL Indicator
Dynamic Signal Lines : Calculates upper and lower DSL lines based on a moving average (SMA) and dynamic thresholds derived from recent highs and lows with a specified offset. These lines adapt to market conditions, providing real-time trend insights.
ATR-Based Bands : Adds bands around the DSL lines using the Average True Range (ATR) multiplied by a width factor. These bands account for market volatility and help identify potential stop-loss levels.
Trend Confirmation : The relationship between the price, DSL lines, and bands determines the current trend. For example, if the price consistently stays above the upper DSL line, it indicates a bullish trend.
2. Momentum Analysis
RSI Calculation : Computes the RSI over a specified period to measure the speed and change of price movements.
Zero-Lag EMA (ZLEMA) : Applies a ZLEMA to the RSI to minimize lag and produce a more responsive oscillator.
DSL Application on Oscillator : Implements the DSL concept on the oscillator by calculating dynamic upper and lower levels. This helps identify overbought or oversold conditions more accurately.
Signal Generation : Detects crossovers between the oscillator and its DSL lines. A crossover above the lower DSL line signals potential bullish momentum, while a crossover below the upper DSL line signals potential bearish momentum.
3. Integrated Signal Filtering
Confluence Requirement : A trade signal is generated only when both the DSL indicator and oscillator agree. For instance, a long entry requires both an uptrend confirmation from the DSL indicator and a bullish momentum signal from the oscillator.
Risk Management Integration : The strategy uses the DSL indicator's bands for setting stop-loss levels and calculates take-profit levels based on a user-defined risk-reward ratio. This ensures that every trade has a predefined risk management plan.
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Originality and Value Added to the Community
Unique Synergy : While both indicators are available individually, this strategy is original in how it combines them to enhance their strengths and mitigate their weaknesses, offering a novel approach not present in existing scripts.
Enhanced Reliability : By requiring confirmation from both trend and momentum indicators, the strategy reduces false signals and increases the likelihood of successful trades.
Versatility : The customizable parameters allow traders to adapt the strategy to different instruments, timeframes, and trading styles, making it a valuable tool for a wide range of trading scenarios.
Educational Contribution : The script demonstrates an effective method of combining indicators for improved trading performance, providing insights that other traders can learn from and apply to their own strategies.
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How to Use the Strategy
Adding the Strategy to Your Chart
Apply the DSL Strategy to your desired trading instrument and timeframe on TradingView.
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Configuring Parameters
DSL Indicator Settings :
Length (len) : Adjusts the sensitivity of the DSL lines (default is 34).
Offset : Determines the look-back period for threshold calculations (default is 30).
Bands Width (width) : Changes the distance of the ATR-based bands from the DSL lines (default is 1).
DSL-BELUGA Oscillator Settings :
Beluga Length (len_beluga) : Sets the period for the RSI calculation in the oscillator (default is 10).
DSL Lines Mode (dsl_mode) : Chooses between "Fast" (more responsive) and "Slow" (smoother) modes for the oscillator's DSL lines.
Risk Management :
Risk Reward (risk_reward) : Defines your desired risk-reward ratio for calculating take-profit levels (default is 1.5).
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Interpreting Signals
Long Entry Conditions :
Trend Confirmation : Price is above the upper DSL line and the upper DSL band (dsl_up1 > dsl_dn).
Price Behavior : The last three candles have both their opens and closes above the upper DSL line.
Momentum Signal : The DSL-BELUGA oscillator crosses above its lower DSL line (up_signal), indicating bullish momentum.
Short Entry Conditions :
Trend Confirmation : Price is below the lower DSL line and the lower DSL band (dsl_dn < dsl_up1).
Price Behavior : The last three candles have both their opens and closes below the lower DSL band.
Momentum Signal : The DSL-BELUGA oscillator crosses below its upper DSL line (dn_signal), indicating bearish momentum.
Exit Conditions :
Stop-Loss : Automatically set at the DSL indicator's band level (upper band for longs, lower band for shorts).
Take-Profit : Calculated based on the risk-reward ratio and the initial risk determined by the stop-loss distance.
Visual Aids
Signal Arrows : Upward green arrows for long entries and downward blue arrows for short entries appear on the chart when conditions are met.
Stop-Loss and Take-Profit Lines : Red and green lines display the calculated stop-loss and take-profit levels for active trades.
Background Highlighting : The chart background subtly changes color to indicate when a signal has been generated.
Backtesting and Optimization
Use TradingView's strategy tester to backtest the strategy over historical data.
Adjust parameters to optimize performance for different instruments or market conditions.
Regularly review backtesting results to ensure the strategy remains effective.
Cosine-Weighted MA ATR [InvestorUnknown]The Cosine-Weighted Moving Average (CWMA) ATR (Average True Range) indicator is designed to enhance the analysis of price movements in financial markets. By incorporating a cosine-based weighting mechanism , this indicator provides a unique approach to smoothing price data and measuring volatility, making it a valuable tool for traders and investors.
Cosine-Weighted Moving Average (CWMA)
The CWMA is calculated using weights derived from the cosine function, which emphasizes different data points in a distinctive manner. Unlike traditional moving averages that assign equal weight to all data points, the cosine weighting allocates more significance to values at the edges of the data window. This can help capture significant price movements while mitigating the impact of outlier values.
The weights are shifted to ensure they remain non-negative, which helps in maintaining a stable calculation throughout the data series. The normalization of these weights ensures they sum to one, providing a proportional contribution to the average.
// Function to calculate the Cosine-Weighted Moving Average with shifted weights
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) * close
cwma
Cosine-Weighted ATR Calculation
The ATR is an essential measure of volatility, reflecting the average range of price movement over a specified period. The Cosine-Weighted ATR uses a similar weighting scheme to that of the CWMA, allowing for a more nuanced understanding of volatility. By emphasizing more recent price movements while retaining sensitivity to broader trends, this ATR variant offers traders enhanced insight into potential price fluctuations.
// Function to calculate the Cosine-Weighted ATR with shifted weights
f_Cosine_Weighted_ATR(simple int length) =>
var float cosine_weights_atr = array.new_float(0)
array.clear(cosine_weights_atr)
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(cosine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(cosine_weights_atr, i) / sum_weights_atr
array.set(cosine_weights_atr, i, norm_weight_atr)
// Calculate Cosine-Weighted ATR using true ranges
cwatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
cwatr := cwatr + array.get(cosine_weights_atr, i) * tr
cwatr
Signal Generation
The indicator generates long and short signals based on the relationship between the price (user input) and the calculated upper and lower bands, derived from the CWMA and the Cosine-Weighted ATR. Crossover conditions are used to identify potential entry points, providing a systematic approach to trading decisions.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(cwma_src)
float cwma = f_Cosine_Weighted_MA(src, ma_length)
// Use normal ATR or Cosine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Cosine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
float src_l = b.calc_src(src_long)
float src_s = b.calc_src(src_short)
// Signal logic for crossovers and crossunders
var int signal = 0
if ta.crossover(src_l, cwma_up)
signal := 1
if ta.crossunder(src_s, cwma_dn)
signal := -1
//}
Backtest Mode and Equity Calculation
To evaluate its effectiveness, the indicator includes a backtest mode, allowing users to test its performance on historical data:
Backtest Equity: A detailed equity curve is calculated based on the generated signals over a user-defined period (startDate to endDate).
Buy and Hold Comparison: Alongside the strategy’s equity, a Buy-and-Hold equity curve is plotted for performance comparison.
Visualization and Alerts
The indicator features customizable plots, allowing users to visualize the CWMA, ATR bands, and signals effectively. The colors change dynamically based on market conditions, with clear distinctions between long and short signals.
Alerts can be configured to notify users of crossover events, providing timely information for potential trading opportunities.
market slayerInput Parameters:
Various input parameters allow customization of the strategy, including options to show trend confirmation, specify trend timeframes and values, set SMA lengths, enable take profit and stop loss, and define their respective values.
Calculations:
Simple Moving Averages (SMAs) are calculated based on the specified lengths.
Buy and sell signals are generated based on the crossover and crossunder of the short and long SMAs.
Confirmation Bars:
Functions are defined to determine bullish or bearish confirmation bars based on certain conditions.
These confirmation bars are used to confirm trend direction and generate additional signals.
Plotting:
SMAs are plotted on the chart.
Trend labels and signal markers are plotted based on the calculated conditions.
Trade Signals:
Buy and sell conditions are defined based on the crossover/crossunder of SMAs and confirmation of trend direction.
Strategy entries and exits are executed accordingly.
Take Profit and Stop Loss:
Optional take profit and stop loss functionality is included.
Trades are automatically closed when profit or loss thresholds are reached.
Closing Trades:
Trades are also closed based on changes in trend confirmation bars to ensure alignment with the overall market direction.
Alerts:
Alert conditions are defined for opening and closing trades, providing notifications when certain conditions are met.
Overall, this script aims to provide a systematic approach to trading by combining moving average crossovers with trend confirmation bars, along with options for risk management through take profit and stop loss orders. Users can customize various parameters to adapt the strategy to different market conditions and trading preferences.
The script uses the request.security() function with the lookahead parameter set to barmerge.lookahead_on to access data from a higher timeframe within the Pine Script on TradingView. Let's break down why it's used:
Higher Timeframe Analysis:
By default, Pine Script operates on the timeframe of the chart it's applied to. However, in trading strategies, it's common to incorporate signals or data from higher timeframes to confirm or validate signals generated on lower timeframes. This helps traders to align their trades with the broader market trend.
Trend Confirmation:
In this script, the confirmationTrendTimeframe parameter allows users to specify a higher timeframe for trend confirmation. The request.security() function fetches the data from this higher timeframe and applies the defined conditions to confirm the trend direction.
Lookahead Behavior:
The lookahead parameter set to barmerge.lookahead_on ensures that the script considers the most up-to-date information available on the higher timeframe when making trading decisions on the lower timeframe. This prevents the script from lagging behind or using outdated data, enhancing the accuracy of trend confirmation.
Usage in confirmationTrendBullish and confirmationTrendBearish:
These variables are assigned the values returned by the request.security() function, which represents the bullish or bearish trend confirmation based on the conditions applied to the data from the higher timeframe.
Multi SMI Ergodic OscillatorThe Multi SMI Ergodic Oscillator (Multi SMIEO) indicator can be used to identify potential buy and sell signals based on the relationship between the TSI and EMA lines.
The script is creating an indicator that plots multiple (3) sets of Time Series Indicator (TSI-Indicator) and Exponential Moving Average (EMA-Signal) lines as a single indicator.
The TSI is a momentum oscillator that helps identify overbought and oversold conditions. It is calculated using the close prices of an asset, a short-term moving average, and a long-term moving average. The script uses three different pairs of input values for the short-term and long-term periods, which can be adjusted by the user.
The EMA is a type of moving average that gives more weight to recent prices. It is calculated by applying a weighting factor to the most recent price, and then adding that weighted value to the previous EMA value. The script uses three different input values for the length of the EMA, which can also be adjusted by the user.
After calculating the TSI and EMA for each set, the script plots them on the same graph, with different colors and widths to differentiate them. The three sets of TSI and EMA lines are plotted to allow the user to compare the results of different periods. The script also plots a horizontal line at zero, which is used as a reference point for the oscillations of the indicator lines.
One way to use this indicator is to look for crossovers between the TSI and the EMA lines. A bullish crossover occurs when the TSI crosses above the EMA. This suggests that the buying pressure is increasing and a potential buy signal is generated. A bearish crossover occurs when the TSI crosses below the EMA. This suggests that the selling pressure is increasing and a potential sell signal is generated.
Some other ways that the indicator can be used include:
1. Identifying trends: The TSI and EMA lines can be used to identify the direction of the trend. An uptrend is present when the TSI and EMA lines are both trending upwards, while a downtrend is present when the TSI and EMA lines are both trending downwards.
2. Overbought and oversold conditions: The TSI can be used to identify overbought and oversold conditions. When the TSI is above the upper limit of the range, the asset is considered overbought and may be due for a price correction. Conversely, when the TSI is below the lower limit of the range, the asset is considered oversold and may be due for a price rebound.
3. Confirming price action: The Multi SMIEO indicator can be used to confirm price action. If a bullish divergence is present, it confirms a potential bullish reversal. If a bearish divergence is present, it confirms a potential bearish reversal.
4. Multiple time frame analysis: By using different periods for the TSI and EMA lines, the indicator can be used to analyze the asset on multiple time frames. It can be useful to compare the results of different periods to get a better understanding of the asset's price movements.
5. Risk management: This indicator can be used as an element of risk management strategy, it can help traders to identify overbought and oversold conditions to set stop loss or take profit levels.
The Multi SMI Ergodic Oscillator (Multi SMIEO) is a versatile indicator that can be used in a number of ways to analyze the price movements of an asset. It can be used to identify potential buy and sell signals, trends, overbought and oversold conditions, and to confirm price action. By using different periods for the TSI and EMA lines, the indicator can also be used to analyze the asset on multiple time frames. However, it is important to remember that indicators are based on historical data, and past performance does not guarantee future results.
It is important to use the indicator as part of a comprehensive trading strategy that includes risk management and other analysis techniques, such as fundamental and technical analysis. It is also important to keep in mind that indicators are not a standalone solution for trading, they should be used in conjunction with other market analysis and research techniques to generate better results.
Lastly, it is important to keep in mind that trading in financial markets comes with a certain level of risk and it is crucial to always have a proper risk management plan in place. Never invest more than you can afford to lose.
Modified RSI Multi-Time Frame (HM)Effective RSI with Multi-Timeframe with Hilema - Milega(HM) concept (HM=WMA -EMA). RSI Script is included with WMA and EMA band for RSI1 and it works very simple
i) When the RSI band turns to Green its a Buy signal. Normally whenever Bearish strength weakens and move towards the Bullish area, the WMA and EMA cross each other and that tends to provide a possible trend change. A trade at crossover normally provides a very good trading oppertunity. One can combine with some other Price action if needed for double confirmation.
ii)When RSI band turns to RED its a Sell signal. As explained in the point 1 , its a vice-versa where a crossover of WMA and EMA is perfect entry to get a good swing trade. Once can combine this tool with Price action for double confirmation.
iii) Using the Multi timeframe user could able to find the trend at higher timeframe to take double confirm on the trend strength and take a perfect oppertunity to take the trade.
By default, script uses the RSI with length 14, WMA 21 and EMA 3 which perfectly working for Index in NSE. Please change as per your requirement.
Apart from the above band, RSI is not have the different levels like 20/ 40 /50/60/80
Multi-timeframes currently set as
RSI1 - Same as Chart
RSI2 - 15 Min
RSI3 - 60 Min
RSI4 - Daily
Script has enabled the option to change the values for these timeframes as per the user requirement.
These ranges can be interpreted and acts as a probable swing points based on the trend and momentum.
40-60 - Neutral Range or Sideways
20 - 60 Bearish range
40 - 70 - Bullish range
Below 20 -- Over Sold Zone
Above 80 - over Bought zone
Also, the crossovers of the WMA and EMA on the RSI gives a very good momentum towards that trend.
Simple Harmonic Oscillator (SHO)The indicator is based on Akram El Sherbini's article "Time Cycle Oscillators" published in IFTA journal 2018 (pages 78-80) (www.ftaa.org.hk)
The SHO is a bounded oscillator for the simple harmonic index that calculates the period of the market’s cycle. The oscillator is used for short and intermediate terms and moves within a range of -100 to 100 percent. The SHO has overbought and oversold levels at +40 and -40, respectively. At extreme periods, the oscillator may reach the levels of +60 and -60. The zero level demonstrates an equilibrium between the periods of bulls and bears. The SHO oscillates between +40 and -40. The crossover at those levels creates buy and sell signals. In an uptrend, the SHO fluctuates between 0 and +40 where the bulls are controlling the market. On the contrary, the SHO fluctuates between 0 and -40 during downtrends where the bears control the market. Reaching the extreme level -60 in an uptrend is a sign of weakness. Mostly, the oscillator will retrace from its centerline rather than the upper boundary +40. On the other hand, reaching +60 in a downtrend is a sign of strength and the oscillator will not be able to reach its lower boundary -40.
Centerline Crossover Tactic
This tactic is tested during uptrends. The buy signals are generated when the WPO/SHI cross their centerlines to the upside. The sell signals are generated when the WPO/SHI cross down their centerlines. To define the uptrend in the system, stocks closing above their 50-day EMA are considered while the ADX is above 18.
Uptrend Tactic
During uptrends, the bulls control the markets, and the oscillators will move above their centerline with an increase in the period of cycles. The lower boundaries and equilibrium line crossovers generate buy signals, while crossing the upper boundaries will generate sell signals. The “Re-entry” and “Exit at weakness” tactics are combined with the uptrend tactic. Consequently, we will have three buy signals and two sell signals.
Sideways Tactic
During sideways, the oscillators fluctuate between their upper and lower boundaries. Crossing the lower boundary to the upside will generate a buy signal. On the other hand, crossing the upper boundary to the downside will generate a sell signal. When the bears take control, the oscillators will cross down the lower boundaries, triggering exit signals. Therefore, this tactic will consist of one buy signal and two sell signals. The sideway tactic is defined when stocks close above their 50-day EMA and the ADX is below 18
Relative Volume RVOL AlertsRelative Volume or RVOL is an indicator used to help determine the amount of volume change over a given period of time.
It is often used to help traders determine how in-play a ticker is.
General rule of thumb is the higher the RVOL, the more in play a stock is.
I myself like to use it as a substitute of the volume indicator itself.
Basic Calculation:
Relative Volume = Current Volume / Average Volume
Crossover Signals:
Any time there is a volume spike which causes a crossover of the user set 'Smoothed Moving Average' or 'Threshold' a green/red dot will appear at the top. The color of the dot is dependent on closing of the candle. Therefore it does not necessarily mean price will continue in that direction since volume spikes often happen in peaks or valleys.
Threshold:
The level at which custom alerts and signal can be set. The higher the value, the more volume required to trigger.
Built in Alerts:
You can set custom alerts for the crossovers of the adjustable threshold, or the average RVOL band.
[davidev] EMA/MA with projection# EMA/MA with projection
## What it is
A lightweight overlay that plots up to three EMAs and one MA (default: 5/21/55 EMAs and 200 MA) and draws a forward projection from the current bar. The projection extrapolates the latest per-bar change (slope) to visualize where each average *could* be in the next N bars—useful for planning entries, dynamic support/resistance, and anticipating crossovers.
Note: The projection is a simple linear extrapolation of the most recent change. It is not a prediction or signal.
## How it works
Computes EMA1, EMA2, EMA3 and MA (SMA) on your chosen sources.
On the last bar only, it draws a short line segment ahead by `Bars Ahead`, using the most recent change (`ta.change()`) × number of bars to project the line.
Lines are **reused** and updated each tick (no clutter), and deleted on historical bars to avoid artifacts.
## Good for
Visualizing **dynamic levels** slightly ahead of price.
Quickly gauging **momentum** and **slope** of your moving averages.
Sketching possible **crossover timing** (e.g., 5 vs 21 EMA) without changing timeframe.
Cleaner charting: projection only renders on the last bar, so historical candles stay uncluttered.
## Tips
Combine with your market structure/volume tools; the projection helps **plan**, not predict.
Shorter EMAs react faster and will show more pronounced projected moves; longer MAs remain steadier.
Increase `Bars Ahead` on higher timeframes; keep it small on scalping charts to avoid overreach.
Artharjan ADXArtharjan ADX (AADX) by Rrahul Desai @Artharjan
📌 Overview
The Artharjan ADX (AADX) is an advanced implementation of the Average Directional Index (ADX) with customizable moving averages, momentum thresholds, and visually intuitive grading of bullish and bearish strength.
Unlike the standard ADX indicator that only shows trend strength, AADX adds graded bullish/bearish conditions, alerts, smoothed DI signals, histogram visualizations, and background color fills to help traders quickly interpret market conditions.
It is designed for traders who want early detection of trend strength, clean visual cues, and automated alert triggers for both bullish and bearish momentum setups.
⚙️ Key Features
🔹 Customizable Calculations
DI Length (default 13) – controls sensitivity of directional indicators.
+/- DI Smoothing – smooths DI signals with user-selected MA.
Multiple Moving Average Types – SMA, EMA, WMA, RMA, VWMA, ALMA, Hull, SWMA, SMMA, TMA.
ADX Smoothing – define how smooth/fast the ADX reacts.
🔹 Flexible Display
Toggle between line plots or histogram view.
Adjustable plot thickness.
Option to plot averages of ADX, +DI, -DI for confirmation.
Configurable background fills:
ADX above/below momentum threshold.
ADX rising/falling color shading.
Trend-grade based color intensity.
🔹 Momentum & Thresholds
Momentum Level (default 25) → defines “strong trend” zone.
Crossover Threshold (default 15) → helps detect early DI crossovers.
Color-coded histogram bars for +DI vs -DI difference:
Above/below zero.
Rising/falling momentum.
🔹 Bullish & Bearish Grading System
The indicator assigns grades from 1 to 5 for both bullish and bearish setups, based on DI and ADX conditions:
Bullish Grades
Grade 1 → Very Weak Bullish
Grade 2 → Weak Bullish
Grade 3 → Moderate Bullish
Grade 4 → Strong Bullish
Grade 5 → Very Strong Bullish
Bearish Grades
Grade 1 → Very Weak Bearish
Grade 2 → Weak Bearish
Grade 3 → Moderate Bearish
Grade 4 → Strong Bearish
Grade 5 → Very Strong Bearish
Labels are automatically plotted above bars to indicate the active grade.
🔹 Alerts
Bullish Alert → when +DI crosses above its average below the threshold OR bullish conditions are met.
Bearish Alert → when -DI crosses above its average below the threshold OR bearish conditions are met.
These alerts make it possible to automate trading signals for scalping, intraday, and swing trading.
📊 Use Cases
Trend Strength Measurement
Spot when markets shift from range-bound to trending.
Confirm the reliability of breakouts with strong ADX readings.
Bullish vs Bearish Control
Compare +DI vs -DI strength to gauge trend direction.
Identify trend reversals early with DI slope changes.
Momentum Confirmation
Use ADX rising + DI grades to validate trade entries.
Filter false breakouts with weak ADX.
Trade Grading System
Enter aggressively on Grade 4–5 signals.
Stay cautious on Grade 1–2 signals.
Automated Alerts & Screening
Combine AADX alerts with strategy rules.
Build scanners to highlight strong ADX setups across multiple stocks.
🎯 Trader’s Advantage
More powerful than standard ADX → Adds slope, grading, alerts, and visualization.
Adaptable to any style → Works for intraday scalping, swing trading, and positional analysis.
Visual clarity → Color fills, histograms, and labels simplify decision-making.
Customizable smoothing → Adjusts to fast or slow markets.
✅ Closing Note
The Artharjan ADX (AADX) transforms the traditional ADX into a complete trend and momentum analyzer. It helps traders detect, confirm, and act on directional strength with clarity and confidence.
With Thanks,
Rrahul Desai
@Artharjan
Range FinderRange Finder Strategy for TradingView
Overview
The Range Finder Strategy is a sophisticated trading system designed for forex and cryptocurrency markets, leveraging dynamic range detection, wick-based rejection patterns, and EMA confluence to execute high-probability trades. This strategy identifies key price ranges using pivot points and triggers trades when price rejects from these boundaries with significant wick formations, aligning with the broader market trend as confirmed by EMA crossovers. It incorporates robust risk management, customizable parameters, and visual aids for clear trade visualization, making it suitable for both manual and automated trading on platforms like Bitget via webhook alerts.
Strategy Components
1. Dynamic Range Detection
Pivot Points: The strategy identifies range boundaries using pivot highs and lows, calculated with a user-defined Pivot Length (default: 5 bars left/right). These pivots mark significant swing points, defining the upper (range high) and lower (range low) boundaries of the price range.
Visualization: The range high is plotted as an orange line, and the range low as a purple line, using a broken line style (plot.style_linebr) to show only confirmed pivot levels, providing a clear visual of the trading range.
2. Wick-Based Rejection Pattern
Wick Detection: The strategy looks for rejection candles at the range boundaries, characterized by significant wicks. A wick is considered valid if its size is at least the user-defined Wick to Body Ratio (default: 1.1, or 10% larger than the candle body).
Sell Signal: Triggered when the high exceeds the range high, the candle closes bearish (close < open), and the upper wick meets the ratio requirement.
Buy Signal: Triggered when the low falls below the range low, the candle closes bullish (close > open), and the lower wick meets the ratio requirement.
Purpose: These wicks indicate strong rejection at key levels, often signaling a reversal back into the range, providing high-probability entry points.
3. EMA Trend Confirmation
EMA Calculation: Uses two Exponential Moving Averages (EMAs) calculated on a user-selectable timeframe (default: 5-minute):
EMA 200: Long-term trend indicator (plotted in red).
EMA 50: Short-term trend indicator (plotted in green).
Crossover Logic:
A bullish trend is confirmed when the EMA 50 crosses above the EMA 200 (ema_trend_up = true).
A bearish trend is confirmed when the EMA 50 crosses below the EMA 200 (ema_trend_down = true).
Confluence Requirement: Trades are only executed when the wick rejection aligns with the EMA trend (e.g., sell signals require close < ema200 and bearish trend; buy signals require close > ema200 and bullish trend).
4. Risk Management
Position Sizing: Calculated based on the user-defined Account Balance (default: $10,000) and Risk Per Trade (default: 2%). The position size is determined as risk_amount / stop_distance, where stop_distance is derived from the Average True Range (ATR, default period: 14).
Stop Loss (SL): Set using an ATR-based multiplier (SL Multiplier, default: 9.0). For sells, SL is placed above the high; for buys, below the low.
Take Profit (TP): Set using an ATR-based multiplier (TP Multiplier, default: 6.0) scaled by the Risk:Reward Ratio (default: 6.0), ensuring a favorable reward-to-risk profile.
Example: For a $10,000 account with 2% risk, if ATR is 0.5, the position size is 400 units, with SL and TP dynamically adjusted to market volatility.
5. Trade Execution
Sell Entry: Triggered on a wick rejection above the range high, with bearish EMA confluence (ema_trend_down and close < ema200). Enters a short position with calculated SL and TP.
Buy Entry: Triggered on a wick rejection below the range low, with bullish EMA confluence (ema_trend_up and close > ema200). Enters a long position with calculated SL and TP.
Exit Logic: Uses strategy.exit to set SL and TP levels, closing trades when either is hit.
6. Visual Feedback
Lines and Labels: Upon trade entry, the strategy plots:
Red SL line and label (e.g., "SL: 123.45").
Green TP line and label (e.g., "TP: 120.00").
Entry line (red for sell, green for buy) labeled with "Sell (Range Rejection)" or "Buy (Range Rejection)".
Customization: Users can adjust the Line Length (default: 25 bars) for how long lines persist and Label Position (left or right) for optimal chart visibility.
7. Alert Conditions
Webhook Integration: Generates alerts for Bitget webhook integration, providing JSON-formatted messages with trade details (action, contracts, market position, size, price, symbol, and timestamp).
Usage: Traders can set up automated trading by connecting these alerts to trading bots or platforms supporting webhooks.
FluidFlow OscillatorFluidFlow Oscillator: Study Material for Traders
Overview
The FluidFlow Oscillator is a custom technical indicator designed to measure price momentum and market flow dynamics by simulating fluid motion concepts such as velocity, viscosity, and turbulence. It helps traders identify potential buy and sell signals along with trend strength, momentum direction, and volatility conditions.
This study explains the underlying calculation concepts, signal logic, visual cues, and how to interpret the professional dashboard table that summarizes key indicator readings.
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How the FluidFlow Oscillator Works
Core Mechanisms
1. Price Flow Velocity
o Measures the rate of change of price over a specified flow length (default 40 bars).
o Calculated as a percentage change of closing price: roc=close−closelen_flowcloselen_flow×100\text{roc} = \frac{\text{close} - \text{close}_{len\_flow}}{\text{close}_{len\_flow}} \times 100roc=closelen_flowclose−closelen_flow×100
o Smoothed by an EMA (Exponential Moving Average) to reduce noise, generating a "flow velocity" value.
2. Viscosity Factor
o Analogous to fluid viscosity, it adjusts the flow velocity based on recent price volatility.
o Volatility is computed as the standard deviation of close prices over the flow length.
o The viscosity acts as a damping factor to slow down the flow velocity in highly volatile conditions.
o This results in a "flow with viscosity" value, that smooths out the velocity considering market turbulence.
3. Turbulence Burst
o Captures sudden changes or bursts in the flow by measuring changes between successive viscosity-adjusted flows.
o The turbulence value is a smoothed absolute change in flow.
o A burst boost factor is added to the oscillator to incorporate this rapid change component, amplifying signals during sudden shifts.
4. Oscillator Calculation
o The raw oscillator value is the sum of flow with viscosity plus burst boost, scaled by 10.
o Clamped between -100 and +100 to limit extremes.
o Finally, smoothed again by EMA for cleaner visualization.
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Signal Logic
The oscillator works with complementary components to produce actionable signals:
• Signal Line: An EMA-smoothed version of the oscillator for generating crossover-based signals.
• Momentum: The rate of change of the oscillator itself, smoothed by EMA.
• Trend: Uses fast (21-period EMA) and slow (50-period EMA) moving averages of price to identify market trend direction (uptrend, downtrend, or sideways).
Signal Conditions
• Bullish Signal (Buy): Oscillator crosses above the oversold threshold with positive momentum.
• Bearish Signal (Sell): Oscillator crosses below the overbought threshold with negative momentum.
Statuses
The oscillator provides descriptive market states based on level and momentum:
• Overbought
• Oversold
• Buy Signal
• Sell Signal
• Bullish / Bearish (momentum-driven)
• Neutral (no clear trend)
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Color System and Visualization
The oscillator uses a sophisticated HSV color model adapting hues according to:
• Oscillator value magnitude and sign (positive or negative)
• Acceleration of oscillator changes
• Smooth color gradients to facilitate intuitive understanding of trend strength and momentum shifts
Background colors highlight overbought (red tint) and oversold (green tint) zones with transparency.
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How to Understand the Professional Dashboard Table
The FluidFlow Oscillator offers an integrated table at the bottom center of the chart. This dashboard summarizes critical indicator readings in 8 columns across 3 rows:
Column Description
SIGNAL Current signal status (e.g., Buy, Sell, Overbought) with color coding
OSCILLATOR Current oscillator value (-100 to +100) with color reflecting intensity and direction
MOMENTUM Momentum bias indicating strength/direction of oscillator changes (Strong Up, Up, Sideways, Down, Strong Down)
TREND Current trend status based on EMAs (Strong Uptrend, Uptrend, Sideways, Downtrend, Strong Downtrend)
VOLATILITY Volatility percentage relative to average, indicating market activity level
FLOW Flow velocity value describing price momentum magnitude and direction
TURBULENCE Turbulence level indicating sudden bursts or spikes in price movement
PROGRESS Oscillator's position mapped as a percentage (0% to 100%) showing proximity to extreme levels
Rows Explained
• Row 1 (Header): Labels for each metric.
• Row 2 (Values): Current numerical or descriptive values color-coded along a professional scheme:
o Green or lime tones indicate positive or bullish conditions.
o Red or orange tones indicate caution, sell signals, or bearish conditions.
o Blue tones indicate neutral or stable conditions.
• Row 3 (Status Indicators): Emoji-like icons and bars provide a quick visual gauge of each metric's intensity or signal strength:
o For example, "🟢🟢🟢" suggests very strong bullish momentum, while "🔴🔴🔴" suggests strong bearish momentum.
o Progress bar visually demonstrates oscillator movement toward oversold or overbought extremes.
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Practical Interpretation Tips
• A Buy signal with green colors and strong momentum usually precedes upward price moves.
• An Overbought status with red background and red table colors warns of potential price corrections or reversals.
• Watch the Turbulence to gauge market instability; spikes may precede price shocks or volatility bursts.
• Confirm signals with the Trend and Momentum columns to avoid false entries.
• Use the Progress bar to anticipate oscillations approaching key threshold levels for timing trades.
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Alerts
The oscillator supports alerts for:
• Buy and sell signals based on oscillator crossovers.
• Overbought and oversold levels reached.
These help traders automate awareness of important market conditions.
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Disclaimer
The FluidFlow Oscillator and its signals are for educational and informational purposes only. They do not guarantee profits and should not be considered as financial advice. Always conduct your own research and use proper risk management when trading. Past performance is not indicative of future results.
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This detailed explanation should help you understand the workings of the FluidFlow Oscillator, its components, signal logic, and how to analyze its professional dashboard for informed trading decisions.
Regression Slope ShiftNormalized Regression Slope Shift + Dynamic Histogram
This indicator detects subtle shifts in price momentum using a rolling linear regression approach. It calculates the slope of a linear regression line for each bar over a specified lookback period, then measures how that slope changes from bar to bar.
Both the slope and its change (delta) are normalized to a -1 to 1 scale for consistent visual interpretation across assets and timeframes. A signal line (EMA) is applied to the slope delta to help identify turning points and crossovers.
Key features:
- Normalized slope and slope change lines
- Dynamic histogram of slope delta with transparency based on magnitude
- Customizable colors for all visual elements
- Signal line for crossover-based momentum shifts
This tool helps traders anticipate trend acceleration or weakening before traditional momentum indicators react, making it useful for early trend detection, divergence spotting, and confirmation signals.
Enhanced HHLL Time Confirmation with EMAStrong recommendation , remove the green and red circle , or leave it how it is ;)
To be used on 1 minute chart MSTR , Stock
other time frames are good , ;)
How to Use
HHLL Signals: Look for green triangles (buy) below bars or red triangles (sell) above bars to identify confirmed HH/LL setups with trend alignment.
EMA Signals: Watch for lime circles (buy) below bars or maroon circles (sell) above bars when price crosses the EMA 400 in a trending market.
Trend Context: Use the EMA 400 as a dynamic support/resistance level and the SMA trend filter to gauge market direction.
Enable alerts to get notified of signals in real-time.
Best Practices
Adjust the Lookback Period and Confirmation Minutes to suit your timeframe (e.g., shorter for scalping, longer for swing trading).
Combine with other indicators (e.g., volume, RSI) for additional confirmation.
Test on your preferred market and timeframe to optimize settings.
Indicator Description: Enhanced HHLL Time Confirmation with EMA
Overview
The "Enhanced HHLL Time Confirmation with EMA" is a versatile trading indicator designed to identify key reversal and continuation signals based on Higher Highs (HH), Lower Lows (LL), and a 400-period Exponential Moving Average (EMA). It incorporates time-based confirmation and trend filters to reduce noise and improve signal reliability. This indicator is ideal for traders looking to spot trend shifts or confirm momentum with a combination of price structure and moving average crossovers.
Key Features
Higher High / Lower Low Detection:
Identifies HH and LL based on a customizable lookback period (default: 30 bars).
Signals are confirmed only after a user-defined time period (in minutes, default: 60) has passed since the last HH or LL, ensuring stability.
Trend Filter:
Uses a fast (10-period) and slow (30-period) Simple Moving Average (SMA) crossover to confirm bullish or bearish trends.
Buy signals require a bullish trend (Fast SMA > Slow SMA), and sell signals require a bearish trend (Fast SMA < Slow SMA).
EMA 400 Integration:
Plots a 400-period EMA (customizable) as a long-term trend reference.
Generates additional buy/sell signals when price crosses above (buy) or below (sell) the EMA 400, filtered by trend direction.
Visualizations:
Optional dashed lines for HH and LL levels (toggleable).
Debug markers (diamonds) to visualize HH/LL detection points.
Distinct signal shapes: triangles for HHLL signals (green/red) and circles for EMA signals (lime/maroon).
Alerts:
Built-in alert conditions for HHLL Buy/Sell and EMA Buy/Sell signals, making it easy to stay informed of key events.
Input Parameters
Lookback Period (default: 30): Number of bars to look back for HH/LL detection.
Confirmation Minutes (default: 60): Time (in minutes) required to confirm HH/LL signals.
High/Low Source: Select the price source for HH (default: high) and LL (default: low).
Show HH/LL Lines (default: true): Toggle visibility of HH/LL dashed lines.
Show Debug Markers (default: true): Toggle HH/LL detection markers.
EMA Period (default: 400): Adjust the EMA length.
MACD Highs and Lows - Dynamic Support & ResistanceDescription:
Enhance your trading strategy with the MACD Highs and Lows indicator, designed to identify dynamic support and resistance levels based on MACD crossovers. This tool plots key price levels triggered by shifts in MACD momentum, helping traders spot potential reversal zones, breakout points, and trend confirmation signals.
Key Features
Dynamic Levels: Automatically plots recent highs/lows when MACD crosses above/below the zero line.
Customizable MACD Parameters:
Adjustable fast/slow lengths (default: 12/26).
Choose between SMA or EMA for oscillator/signal line.
Flexible signal smoothing (1-50 periods).
Visual Clarity:
Clear green/red lines for highs and lows.
Tracks both price extremes and adjacent candle levels (e.g., high-of-low-bar, low-of-high-bar).
Multi-Timeframe Utility: Works across charts for swing trading, scalping, or trend analysis.
How It Works
Bullish Signal: When MACD crosses above zero, the indicator marks the recent lowest low (support) and its corresponding high.
Bearish Signal: When MACD crosses below zero, it plots the recent highest high (resistance) and its corresponding low.
Levels persist until the next crossover, creating actionable reference zones.
Use Cases
Trend Confirmation: Validate breakouts when price closes above/below plotted levels.
Stop Loss Placement: Set stops beyond recent dynamic highs/lows.
Divergence Detection: Spot discrepancies between MACD momentum and price action.
Settings Tips:
Increase Fast Length for responsiveness or Slow Length for smoother signals.
Use EMA for faster reactions, SMA for reduced noise.
Trade Quality Rating: signal rating from 1 to 5 starsOverview
The indicator is built to generate trading signals based on a combination of technical indicators and then assign each signal a quality rating from 1 to 5 stars. The idea is that the more filters that are met, the stronger (or higher quality) the signal is assumed to be. You can then use these quality ratings to decide which signals to act upon, keeping in mind that a higher-rated signal has more confirming factors.
Components of the Indicator
Simple Moving Averages (SMAs):
SMA9 and SMA20:
These two moving averages are used to detect short-term trend changes via crossovers. A bullish signal is generated when the SMA9 crosses above the SMA20, and a bearish signal when it crosses below.
SMA200 (on the current timeframe) & Daily SMA200:
The SMA200 on your current chart helps smooth out the price action.
The Daily SMA200 serves as a long-term trend filter. For a valid long signal, the price must be above the Daily SMA200, and vice versa for a short signal.
MACD (Moving Average Convergence Divergence):
The MACD is calculated using standard parameters (12, 26, 9).
It adds momentum confirmation to the signal. For a long trade, the MACD line should be above its signal line, and for a short trade, below.
RSI (Relative Strength Index):
Calculated with a 14-period setting.
For long signals, the RSI must be above 50 (indicating upward momentum), while for short signals, it should be below 50.
This filter is one of the additional conditions that add to the quality rating.
Volume Filter:
A 20-period moving average of volume is computed.
The current volume must exceed this average, suggesting that there is enough market participation backing the move.
This is another extra filter that adds to the overall quality score.
ADX (Average Directional Index):
The ADX is manually calculated in the script (using a 14-period setting) to gauge the strength of the trend.
A value above 25 is considered to confirm that a strong trend is in place, making the signal more reliable.
VWAP (Volume Weighted Average Price):
The session VWAP is computed on a daily basis.
For long trades, the price should be above the VWAP, and for short trades, below.
This serves as a confirmation that the current price is moving in the right direction relative to the volume-weighted average.
Signal Generation and Quality Rating
Base Signal (1 Star):
The fundamental trade signal is generated when the SMA9/SMA20 crossover occurs, in combination with the MACD confirmation and the condition that the price is on the correct side of the Daily SMA200. This base signal provides a 1-star quality rating.
Additional Filters (Adding Extra Stars):
RSI Filter: Adds 1 extra star if the RSI condition is met (RSI > 50 for long or RSI < 50 for short).
Volume Filter: Adds 1 extra star if the current volume exceeds its 20-period moving average.
ADX Filter: Adds 1 extra star if the ADX value is above 25, confirming a strong trend.
VWAP Filter: Adds 1 extra star if the price is above the VWAP for long trades (or below for short trades).
When all filters are met, you get a 5-star rating (1 star base + 4 extra stars).
Display and Alerts:
The indicator plots your SMAs on the chart.
When a signal occurs, it places a label on the chart showing the trade direction ("BUY" or "SELL") along with the quality rating in stars.
Additionally, alert conditions are set up so that you can receive notifications when a valid signal (based on the base criteria) is generated.
How to Use This Indicator
Filtering Trades:
Use the quality rating as a visual guide. For instance, if you want to only act on the most reliable setups, you might decide to trade only signals that are rated 4 or 5 stars.
Manual Confirmation:
Even with a high star rating, you can perform your own final checks (e.g., checking price action or additional chart patterns) before entering a trade.
Backtesting and Adjustment:
Because market conditions differ, it’s advisable to backtest the indicator on your instrument of choice and adjust the parameters (such as the ADX threshold or the period for volume averaging) to better suit your trading style.
Conclusion
This 5-star system indicator is designed to provide a comprehensive overview of trade quality by integrating multiple technical filters into one visual signal. It helps filter out noise by ensuring that a trade signal not only meets a basic SMA and MACD condition but also aligns with volume, trend strength (ADX), and VWAP criteria. This multi-layered approach can lead to fewer but higher quality trades, allowing you to focus on setups that have more confluence.
Happy trading!
Trend with ADX/EMA - Buy & Sell SignalsThis script is designed to help traders make buy and sell decisions based on trend analysis using two key methods: ADX (Average Directional Index) and EMA (Exponential Moving Averages). Here's a breakdown in simple terms:
What Does It Do?
Identifies the Trend's Strength and Direction:
Uses the ADX indicator to determine how strong the trend is.
Compares two lines (DI+ and DI−) to identify whether the trend is moving up or down.
Generates Buy and Sell Signals:
Uses two EMAs (a fast one and a slow one) to check when the price crosses key levels, signaling a possible buy or sell opportunity.
Plots visual indicators (arrows and labels) for easy interpretation.
Color-Codes the Chart:
Highlights the background in green when the trend is bullish (uptrend).
Highlights the background in red when the trend is bearish (downtrend).
Alerts the User:
Creates alerts when specific conditions for buying or selling are met.
Key Components:
1. ADX (Trend Strength & Direction)
What is ADX?
ADX measures how strong the trend is (not the direction). Higher ADX means a stronger trend.
It also calculates two lines:
DI+: Measures upward movement strength.
DI−: Measures downward movement strength.
How It Works in the Script:
If DI+ is greater than DI−, it’s a bullish trend (upward).
If DI− is greater than DI+, it’s a bearish trend (downward).
The background turns green for an uptrend and red for a downtrend.
2. EMA (Buy and Sell Decisions)
What is EMA?
EMA is a moving average that gives more weight to recent prices. It’s used to smooth out price fluctuations.
How It Works in the Script:
The script calculates two EMAs:
Fast EMA (short-term average): Reacts quickly to price changes.
Slow EMA (long-term average): Reacts slower and shows overall trends.
When the Fast EMA crosses above the Slow EMA, it’s a signal to Buy.
When the Fast EMA crosses below the Slow EMA, it’s a signal to Sell.
These signals are marked on the chart as "Buy" and "Sell" labels.
3. Buy and Sell Alerts
The script sets up alerts for the user:
Buy Alert: When a crossover indicates a bullish signal.
Sell Alert: When a crossunder indicates a bearish signal.
Visual Elements on the Chart:
Background Colors:
Green: When the DI+ line indicates an uptrend.
Red: When the DI− line indicates a downtrend.
EMA Lines:
Green Line: Fast EMA.
Red Line: Slow EMA.
Buy/Sell Labels:
"Buy" label: Shown when the Fast EMA crosses above the Slow EMA.
"Sell" label: Shown when the Fast EMA crosses below the Slow EMA.
Why Use This Script?
Trend Analysis: Helps you quickly identify the strength and direction of the market trend.
Buy/Sell Signals: Gives clear signals to enter or exit trades based on trend and EMA crossovers.
Custom Alerts: Ensures you never miss a trading opportunity by notifying you when conditions are met.
Visual Simplicity: Makes it easy to interpret trading signals with color-coded backgrounds and labeled arrows.
IU Higher Timeframe MA Cross StrategyIU Higher Timeframe MA Cross Strategy
The IU Higher Timeframe MA Cross Strategy is a versatile trading tool designed to identify trend by utilizing two customizable moving averages (MAs) across different timeframes and types. This strategy includes detailed entry and exit rules with fully configurable inputs, offering flexibility to suit various trading styles.
Key Features:
- Two moving averages (MA1 and MA2) with customizable types, lengths, sources, and timeframes.
- Both long and short trade setups based on MA crossovers.
- Integrated risk management with adjustable stop-loss and take-profit levels based on a user-defined risk-to-reward (RTR) ratio.
- Clear visualization of MAs, entry points, stop-loss, and take-profit zones.
Inputs:
1. Risk-to-Reward Ratio (RTR):
- Defines the take-profit level in relation to the stop-loss distance. Default is 2.
2. MA1 Settings:
- Source: Select the data source for calculating MA1 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA1 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA1 calculation. Default is 20.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA1 to merge gaps. Default is true.
3. MA2 Settings:
- Source: Select the data source for calculating MA2 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA2 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA2 calculation. Default is 50.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA2 to merge gaps. Default is true.
Entry Rules:
- Long Entry:
- Triggered when MA1 crosses above MA2 (crossover).
- Entry is confirmed only when the bar is closed and no existing position is active.
- Short Entry:
- Triggered when MA1 crosses below MA2 (crossunder).
- Entry is confirmed only when the bar is closed and no existing position is active.
Exit Rules:
- Stop-Loss:
- For long positions: Set at the low of the bar preceding the entry.
- For short positions: Set at the high of the bar preceding the entry.
- Take-Profit:
- For long positions: Calculated as (Entry Price - Stop-Loss) * RTR + Entry Price.
- For short positions: Calculated as Entry Price - (Stop-Loss - Entry Price) * RTR.
Visualization:
- Plots MA1 and MA2 on the chart with distinct colors for easy identification.
- Highlights stop-loss and take-profit levels using shaded zones for clear visual representation.
- Displays the entry level for active positions.
This strategy provides a robust framework for traders to identify and act on trend reversals while maintaining strict risk management. The flexibility of its inputs allows for seamless customization to adapt to various market conditions and trading preferences.
Directional Volume IndexDirectional Volume Index (DVI) (buying/selling pressure)
This index is adapted from the Directional Movement Index (DMI), but based on volume instead of price movements. The idea is to detect building directional volume indicating a growing amount of orders that will eventually cause the price to follow. (DVI is not displayed by default)
The rough algorithm for the Positive Directional Volume Index (green bar):
calculate the delta to the previous green bar's volume
if the delta is positive (growing buying pressure) add it to an SMA, else add 0 (also for red bars)
divide these average deltas by the average volume
the result is the Positive Directional Volume Index (DVI+) (vice versa for DVI-)
Differential Directional Volume Index (DDVI) (relative pressure)
Creating the difference of both Directional Volume Indexes (DVI+ - DVI-) creates the Differential Directional Volume Index (DDVI) with rising values indicating a growing buying pressure, falling values a growing selling pressure. (DDVI is displayed by default, smoothed by a custom moving average)
Average Directional Volume Index (ADVX) (pressure strength)
Putting the relative pressure (DDVI) in relation to the total pressure (DVI+ + DVI-) we can determine the strength and duration of the currently building volume change / trend. For the DMI/ADX usually 20 is an indicator for a strong trend, values above 50 suggesting exhaustion and approaching reversals. (ADVX is not displayed by default, smoothed by a custom moving average)
Divergences of the Differential Directional Volume Index (DDVI) (imbalances)
By detecting divergences we can detect situations where e.g. bullish volume starts to build while price is in a downtrend, suggesting that there is growing buying pressure indicating an imminent bullish pullback/order block or reversal. (strong and hidden divergences are displayed by default)
Divergences Overview:
strong bull: higher lows on volume, lower lows on price
medium bull: higher lows on volume, equal lows on price
weak bull: equal lows on volume, lower lows on price
hidden bull: lower lows on volume, higher lows on price
strong bear: lower highs on volume, higher highs on price
medium bear: lower highs on volume, equal highs on price
weak bear: equal highs on volume, higher highs on price
hidden bear: higher highs on volume, lower highs on price
DDVI Bands (dynamic overbought/oversold levels)
Using Bollinger Bands with DDVI as source we receive an averaged relative pressure with stdev band offsets. This can be used as dynamic overbought/oversold levels indicating reversals on sharp crossovers.
Alerts
As of now there are no alerts built in, but all internal data is exposed via plot and plotshape functions, so it can be used for custom crossover conditions in the alert dialog. This is still a personal research project, so if you find good setups, please let me know.
SMA- Ashish SinghSMA
This script implements a Simple Moving Average (SMA) crossover strategy using three SMAs: 200-day, 50-day, and 20-day, with buy and sell signals triggered based on specific conditions involving these moving averages. The indicator is overlaid on the price chart, providing visual cues for potential buy and sell opportunities based on moving average crossovers.
Key Features:
Moving Averages:
The 200-day, 50-day, and 20-day SMAs are calculated and plotted on the price chart. These are key levels that traders use to assess trends.
The 200-day SMA represents the long-term trend, the 50-day SMA is used for medium-term trends, and the 20-day SMA is for short-term analysis.
Buy Signal:
A buy signal is triggered when the price is below all three moving averages (200 SMA, 50 SMA, 20 SMA) and the SMAs are in a specific downward trend (200 SMA > 50 SMA > 20 SMA). This is an indication of a potential upward reversal.
The buy signal is marked with a green triangle below the price bar.
Sell Signal:
A sell signal is triggered when the price is above all three moving averages and the SMAs are in a specific upward trend (200 SMA < 50 SMA < 20 SMA). This signals a potential downward reversal.
The sell signal is marked with a red triangle above the price bar.
Trade Information:
After a buy signal, the buy price, bar index, and timestamp are recorded. When a sell signal occurs, the percentage gain or loss is calculated along with the number of days between the buy and sell signals.
The script automatically displays a label on the chart showing the gain or loss percentage along with the number of days the trade lasted. Green labels represent gains, and red labels represent losses.
User-friendly Visuals:
The buy and sell signals are plotted as small triangles directly on the chart for easy identification.
Detailed trade information is provided with well-formatted labels to highlight the profit or loss after each trade.
How It Works:
This strategy helps traders to identify trend reversals by leveraging long-term and short-term moving averages.
A single buy or sell signal is triggered based on price movement relative to the SMAs and their order.
The tool is designed to help traders quickly spot buying and selling opportunities with clear visual indicators and gain/loss metrics.
This indicator is ideal for traders looking to implement a systematic SMA-based strategy with well-defined buy/sell points and automatic performance tracking for each trade.
Disclaimer: The information provided here is for educational and informational purposes only. It is not intended as financial advice or as a recommendation to buy or sell any stocks. Please conduct your own research or consult a financial advisor before making any investment decisions. ProfitLens does not guarantee the accuracy, completeness, or reliability of any information presented.
