MomentumSignal Kit RSI-MACD-ADX-CCI-CMF-TSI-EStoch// ----------------------------------------
// Description:
// ----------------------------------------
// MomentumKit RSI/MACD-ADX-CCI-CMF-TSI-EStoch Suite is a comprehensive momentum indicator suite designed to provide robust buy and sell signals through the consensus of multiple normalized momentum indicators. This suite integrates the following indicators:
// - **Relative Strength Index (RSI)**
// - **Stochastic RSI**
// - **Moving Average Convergence Divergence (MACD)** with enhanced logic
// - **True Strength Index (TSI)**
// - **Commodity Channel Index (CCI)**
// - **Chaikin Money Flow (CMF)**
// - **Average Directional Index (ADX)**
// - **Ehlers' Stochastic**
//
// **Key Features:**
// 1. **Normalization:** Each indicator is normalized to a consistent scale, facilitating easier comparison and interpretation across different momentum metrics. This uniform scaling allows traders to seamlessly analyze multiple indicators simultaneously without the confusion of differing value ranges.
//
// 2. **Consensus-Based Signals:** By combining multiple indicators, MomentumKit generates buy and sell signals based on the agreement among various momentum measurements. This multi-indicator consensus approach enhances signal reliability and reduces the likelihood of false positives.
//
// 3. **Overlap Analysis:** The normalization process aids in identifying overlapping signals, where multiple indicators point towards a potential change in price or momentum. Such overlaps are strong indicators of significant market movements, providing traders with timely and actionable insights.
//
// 4. **Enhanced Logic for MACD:** The MACD component within MomentumKit utilizes enhanced logic to improve its responsiveness and accuracy in detecting trend changes.
//
// 5. **Debugging Features:** MomentumKit includes advanced debugging tools that display individual buy and sell signals generated by each indicator. These features are intended for users with technical and programming skills, allowing them to:
// - **Visualize Signal Generation:** See real-time buy and sell signals for each integrated indicator directly on the chart.
// - **Adjust Signal Thresholds:** Modify the criteria for what constitutes a buy or sell signal for each indicator, enabling tailored analysis based on specific trading strategies.
// - **Filter and Manipulate Signals:** Enable or disable specific indicators' contributions to the overall buy and sell signals, providing flexibility in signal generation.
// - **Monitor Indicator Behavior:** Utilize debug plots and labels to understand how each indicator reacts to market movements, aiding in strategy optimization.
//
// **Work in Progress:**
// MomentumKit is continuously evolving, with ongoing enhancements to its algorithms and user interface. Current debugging features are designed to offer deep insights for technically adept users, allowing for extensive customization and fine-tuning. Future updates aim to introduce more user-friendly interfaces and automated optimization tools to cater to a broader audience.
//
// **Usage Instructions:**
// - **Visibility Controls:** Users can toggle the visibility of individual indicators to focus on specific momentum metrics as needed.
// - **Parameter Adjustments:** Each indicator comes with customizable parameters, allowing traders to fine-tune the suite according to their trading strategies and market conditions.
// - **Debugging Features:** Enable the debugging mode to visualize individual indicator signals and adjust their contribution to the overall buy/sell signals. This requires a basic understanding of the underlying indicators and their operational thresholds.
//
// **Benefits:**
// - **Simplified Analysis:** Normalization simplifies the process of analyzing multiple indicators, making it easier to identify consistent signals across different momentum measurements.
// - **Improved Decision-Making:** Consensus-based signals backed by multiple normalized indicators provide a higher level of confidence in trading decisions.
// - **Versatility:** Suitable for various trading styles and market conditions, MomentumKit offers a versatile toolset for both novice and experienced traders.
//
// **Technical Requirements:**
// - **Programming Knowledge:** To fully leverage the debugging and signal manipulation features, users should possess a foundational understanding of Pine Script and the mechanics of momentum indicators.
// - **Customization Skills:** Ability to adjust indicator parameters and debug filters to align with specific trading strategies.
//
// **Disclaimer:**
// This indicator suite is intended for educational and analytical purposes only and does not constitute financial advice. Trading involves significant risk, and past performance is not indicative of future results. Always conduct your own analysis or consult a qualified financial advisor before making trading decisions.
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PRINT_TYPELibrary "PRINT_TYPE"
Inputs
Inputs objects
Fields:
inbalance_percent (series int) : percentage coefficient to determine the Imbalance of price levels
stacked_input (series int) : minimum number of consecutive Imbalance levels required to draw extended lines
show_summary_footprint (series bool)
procent_volume_area (series int) : definition size Value area
new_imbalance_cond (series bool) : bool input for setup alert on new imbalance buy and sell
new_imbalance_line_cond (series bool) : bool input for setup alert on new imbalance line buy and sell
stop_past_imbalance_line_cond (series bool) : bool input for setup alert on stop past imbalance line buy and sell
Constants
Constants all Constants objects
Fields:
imbalance_high_char (series string) : char for printing buy imbalance
imbalance_low_char (series string) : char for printing sell imbalance
color_title_sell (series color) : color for footprint sell
color_title_buy (series color) : color for footprint buy
color_line_sell (series color) : color for sell line
color_line_buy (series color) : color for buy line
color_title_none (series color) : color None
Calculation_data
Calculation_data data for calculating
Fields:
detail_open (array) : array open from calculation timeframe
detail_high (array) : array high from calculation timeframe
detail_low (array) : array low from calculation timeframe
detail_close (array) : array close from calculation timeframe
detail_vol (array) : array volume from calculation timeframe
previos_detail_close (array) : array close from calculation timeframe
isBuyVolume (series bool) : attribute previosly bar buy or sell
Footprint_row
Footprint_row objects one footprint row
Fields:
price (series float) : row price
buy_vol (series float) : buy volume
sell_vol (series float) : sell volume
imbalance_buy (series bool) : attribute buy inbalance
imbalance_sell (series bool) : attribute sell imbalance
buy_vol_box (series box) : for ptinting buy volume
sell_vol_box (series box) : for printing sell volume
buy_vp_box (series box) : for ptinting volume profile buy
sell_vp_box (series box) : for ptinting volume profile sell
row_line (series label) : for ptinting row price
empty (series bool) : = true attribute row with zero volume buy and zero volume sell
Imbalance_line_var_object
Imbalance_line_var_object var objects printing and calculation imbalance line
Fields:
cum_buy_line (array) : line array for saving all history buy imbalance line
cum_sell_line (array) : line array for saving all history sell imbalance line
Imbalance_line
Imbalance_line objects printing and calculation imbalance line
Fields:
buy_price_line (array) : float array for saving buy imbalance price level
sell_price_line (array) : float array for saving sell imbalance price level
var_imba_line (Imbalance_line_var_object) : var objects this type
Footprint_bar
Footprint_bar all objects one bar with footprint
Fields:
foot_rows (array) : objects one row footprint
imba_line (Imbalance_line) : objects imbalance line
row_size (series float) : size rows
total_vol (series float) : total volume one footprint bar
foot_buy_vol (series float) : buy volume one footprint bar
foot_sell_vol (series float) : sell volume one footprint bar
foot_max_price_vol (map) : map with one value - price row with max volume buy + sell
calc_data (Calculation_data) : objects with detail data from calculation resolution
Support_objects
Support_objects support object for footprint calculation
Fields:
consts (Constants) : all consts objects
inp (Inputs) : all input objects
bar_index_show_condition (series bool) : calculation bool value for show all objects footprint
row_line_color (series color) : calculation value - color for row price
dop_info (series string)
show_table_cond (series bool)
Mean Reversion Cloud (Ornstein-Uhlenbeck) // AlgoFyreThe Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator detects mean-reversion opportunities by applying the Ornstein-Uhlenbeck process. It calculates a dynamic mean using an Exponential Weighted Moving Average, surrounded by volatility bands, signaling potential buy/sell points when prices deviate.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Adaptive Mean Calculation
🔸Volatility-Based Cloud
🔸Speed of Reversion (θ)
🔶 FUNCTIONALITY
🔸Dynamic Mean and Volatility Bands
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Visualization via Table and Plotshapes
🞘 Table Overview
🞘 Plotshapes Explanation
🞘 Code extract
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) is a unique indicator that applies the Ornstein-Uhlenbeck stochastic process to identify mean-reverting behavior in asset prices. Unlike traditional moving average-based indicators, this model uses an Exponentially Weighted Moving Average (EWMA) to calculate the long-term mean, dynamically adjusting to recent price movements while still considering all historical data. It also incorporates volatility bands, providing a "cloud" that visually highlights overbought or oversold conditions. By calculating the speed of mean reversion (θ) through the autocorrelation of log returns, this indicator offers traders a more nuanced and mathematically robust tool for identifying mean-reversion opportunities. These innovations make it especially useful for markets that exhibit range-bound characteristics, offering timely buy and sell signals based on statistical deviations from the mean.
🔸Adaptive Mean Calculation Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Mean Reversion Cloud uses an Exponentially Weighted Moving Average (EWMA), which adapts to price movements by dynamically adjusting its calculation, offering a more responsive mean.
🔸Volatility-Based Cloud Unlike simple moving averages that only plot a single line, the Mean Reversion Cloud surrounds the dynamic mean with volatility bands. These bands, based on standard deviations, provide traders with a visual cue of when prices are statistically likely to revert, highlighting potential reversal zones.
🔸Speed of Reversion (θ) The indicator goes beyond price averages by calculating the speed at which the price reverts to the mean (θ), using the autocorrelation of log returns. This gives traders an additional tool for estimating the likelihood and timing of mean reversion, making the signals more reliable in practice.
🔶 FUNCTIONALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator is designed to detect potential mean-reversion opportunities in asset prices by applying the Ornstein-Uhlenbeck stochastic process. It calculates a dynamic mean through the Exponentially Weighted Moving Average (EWMA) and plots volatility bands based on the standard deviation of the asset's price over a specified period. These bands create a "cloud" that represents expected price fluctuations, helping traders to identify overbought or oversold conditions. By calculating the speed of reversion (θ) from the autocorrelation of log returns, the indicator offers a more refined way of assessing how quickly prices may revert to the mean. Additionally, the inclusion of volatility provides a comprehensive view of market conditions, allowing for more accurate buy and sell signals.
Let's dive into the details:
🔸Dynamic Mean and Volatility Bands The dynamic mean (μ) is calculated using the EWMA, giving more weight to recent prices but considering all historical data. This process closely resembles the Ornstein-Uhlenbeck (OU) process, which models the tendency of a stochastic variable (such as price) to revert to its mean over time. Volatility bands are plotted around the mean using standard deviation, forming the "cloud" that signals overbought or oversold conditions. The cloud adapts dynamically to price fluctuations and market volatility, making it a versatile tool for mean-reversion strategies. 🞘 How it works Step one: Calculate the dynamic mean (μ) The Ornstein-Uhlenbeck process describes how a variable, such as an asset's price, tends to revert to a long-term mean while subject to random fluctuations. In this indicator, the EWMA is used to compute the dynamic mean (μ), mimicking the mean-reverting behavior of the OU process. Use the EWMA formula to compute a weighted mean that adjusts to recent price movements. Assign exponentially decreasing weights to older data while giving more emphasis to current prices. Step two: Plot volatility bands Calculate the standard deviation of the price over a user-defined period to determine market volatility. Position the upper and lower bands around the mean by adding and subtracting a multiple of the standard deviation. 🞘 How to calculate Exponential Weighted Moving Average (EWMA)
The EWMA dynamically adjusts to recent price movements:
mu_t = lambda * mu_{t-1} + (1 - lambda) * P_t
Where mu_t is the mean at time t, lambda is the decay factor, and P_t is the price at time t. The higher the decay factor, the more weight is given to recent data.
Autocorrelation (ρ) and Standard Deviation (σ)
To measure mean reversion speed and volatility: rho = correlation(log(close), log(close ), length) Where rho is the autocorrelation of log returns over a specified period.
To calculate volatility:
sigma = stdev(close, length)
Where sigma is the standard deviation of the asset's closing price over a specified length.
Upper and Lower Bands
The upper and lower bands are calculated as follows:
upper_band = mu + (threshold * sigma)
lower_band = mu - (threshold * sigma)
Where threshold is a multiplier for the standard deviation, usually set to 2. These bands represent the range within which the price is expected to fluctuate, based on current volatility and the mean.
🞘 Code extract // Calculate Returns
returns = math.log(close / close )
// Calculate Long-Term Mean (μ) using EWMA over the entire dataset
var float ewma_mu = na // Initialize ewma_mu as 'na'
ewma_mu := na(ewma_mu ) ? close : decay_factor * ewma_mu + (1 - decay_factor) * close
mu = ewma_mu
// Calculate Autocorrelation at Lag 1
rho1 = ta.correlation(returns, returns , corr_length)
// Ensure rho1 is within valid range to avoid errors
rho1 := na(rho1) or rho1 <= 0 ? 0.0001 : rho1
// Calculate Speed of Mean Reversion (θ)
theta = -math.log(rho1)
// Calculate Volatility (σ)
sigma = ta.stdev(close, corr_length)
// Calculate Upper and Lower Bands
upper_band = mu + threshold * sigma
lower_band = mu - threshold * sigma
🔸Visualization via Table and Plotshapes
The table shows key statistics such as the current value of the dynamic mean (μ), the number of times the price has crossed the upper or lower bands, and the consecutive number of bars that the price has remained in an overbought or oversold state.
Plotshapes (diamonds) are used to signal buy and sell opportunities. A green diamond below the price suggests a buy signal when the price crosses below the lower band, and a red diamond above the price indicates a sell signal when the price crosses above the upper band.
The table and plotshapes provide a comprehensive visualization, combining both statistical and actionable information to aid decision-making.
🞘 Code extract // Reset consecutive_bars when price crosses the mean
var consecutive_bars = 0
if (close < mu and close >= mu) or (close > mu and close <= mu)
consecutive_bars := 0
else if math.abs(deviation) > 0
consecutive_bars := math.min(consecutive_bars + 1, dev_length)
transparency = math.max(0, math.min(100, 100 - (consecutive_bars * 100 / dev_length)))
🔶 INSTRUCTIONS
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator can be set up by adding it to your TradingView chart and configuring parameters such as the decay factor, autocorrelation length, and volatility threshold to suit current market conditions. Look for price crossovers and deviations from the calculated mean for potential entry signals. Use the upper and lower bands as dynamic support/resistance levels for setting take profit and stop-loss orders. Combining this indicator with additional trend-following or momentum-based indicators can improve signal accuracy. Adjust settings for better mean-reversion detection and risk management.
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
Adding the Indicator to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Mean Reversion Cloud (Ornstein-Uhlenbeck)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator:
Open the indicator settings by clicking on the gear icon next to its name on the chart.
Decay Factor: Adjust the decay factor (λ) to control the responsiveness of the mean calculation. A higher value prioritizes recent data.
Autocorrelation Length: Set the autocorrelation length (θ) for calculating the speed of mean reversion. Longer lengths consider more historical data.
Threshold: Define the number of standard deviations for the upper and lower bands to determine how far price must deviate to trigger a signal.
Chart Setup:
Select the appropriate timeframe (e.g., 1-hour, daily) based on your trading strategy.
Consider using other indicators such as RSI or MACD to confirm buy and sell signals.
🞘 Understanding What to Look For on the Chart
Indicator Behavior:
Observe how the price interacts with the dynamic mean and volatility bands. The price staying within the bands suggests mean-reverting behavior, while crossing the bands signals potential entry points.
The indicator calculates overbought/oversold conditions based on deviation from the mean, highlighted by color-coded cloud areas on the chart.
Crossovers and Deviation:
Look for crossovers between the price and the mean (μ) or the bands. A bullish crossover occurs when the price crosses below the lower band, signaling a potential buying opportunity.
A bearish crossover occurs when the price crosses above the upper band, suggesting a potential sell signal.
Deviations from the mean indicate market extremes. A large deviation indicates that the price is far from the mean, suggesting a potential reversal.
Slope and Direction:
Pay attention to the slope of the mean (μ). A rising slope suggests bullish market conditions, while a declining slope signals a bearish market.
The steepness of the slope can indicate the strength of the mean-reversion trend.
🞘 Possible Entry Signals
Bullish Entry:
Crossover Entry: Enter a long position when the price crosses below the lower band with a positive deviation from the mean.
Confirmation Entry: Use additional indicators like RSI (above 50) or increasing volume to confirm the bullish signal.
Bearish Entry:
Crossover Entry: Enter a short position when the price crosses above the upper band with a negative deviation from the mean.
Confirmation Entry: Look for RSI (below 50) or decreasing volume to confirm the bearish signal.
Deviation Confirmation:
Enter trades when the deviation from the mean is significant, indicating that the price has strayed far from its expected value and is likely to revert.
🞘 Possible Take Profit Strategies
Static Take Profit Levels:
Set predefined take profit levels based on historical volatility, using the upper and lower bands as guides.
Place take profit orders near recent support/resistance levels, ensuring you're capitalizing on the mean-reversion behavior.
Trailing Stop Loss:
Use a trailing stop based on a percentage of the price deviation from the mean to lock in profits as the trend progresses.
Adjust the trailing stop dynamically along the calculated bands to protect profits as the price returns to the mean.
Deviation-Based Exits:
Exit when the deviation from the mean starts to decrease, signaling that the price is returning to its equilibrium.
🞘 Possible Stop-Loss Levels
Initial Stop Loss:
Place an initial stop loss outside the lower band (for long positions) or above the upper band (for short positions) to protect against excessive deviations.
Use a volatility-based buffer to avoid getting stopped out during normal price fluctuations.
Dynamic Stop Loss:
Move the stop loss closer to the mean as the price converges back towards equilibrium, reducing risk.
Adjust the stop loss dynamically along the bands to account for sudden market movements.
🞘 Additional Tips
Combine with Other Indicators:
Enhance your strategy by combining the Mean Reversion Cloud with momentum indicators like MACD, RSI, or Bollinger Bands to confirm market conditions.
Backtesting and Practice:
Backtest the indicator on historical data to understand how it performs in various market environments.
Practice using the indicator on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The indicator reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Customize settings 🞘 Decay Factor (λ): Defines the weight assigned to recent price data in the calculation of the mean. A value closer to 1 places more emphasis on recent prices, while lower values create a smoother, more lagging mean.
🞘 Autocorrelation Length (θ): Sets the period for calculating the speed of mean reversion and volatility. Longer lengths capture more historical data, providing smoother calculations, while shorter lengths make the indicator more responsive.
🞘 Threshold (σ): Specifies the number of standard deviations used to create the upper and lower bands. Higher thresholds widen the bands, producing fewer signals, while lower thresholds tighten the bands for more frequent signals.
🞘 Max Gradient Length (γ): Determines the maximum number of consecutive bars for calculating the deviation gradient. This setting impacts the transparency of the plotted bands based on the length of deviation from the mean.
🔶 CONCLUSION
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator offers a sophisticated approach to identifying mean-reversion opportunities by applying the Ornstein-Uhlenbeck stochastic process. This dynamic indicator calculates a responsive mean using an Exponentially Weighted Moving Average (EWMA) and plots volatility-based bands to highlight overbought and oversold conditions. By incorporating advanced statistical measures like autocorrelation and standard deviation, traders can better assess market extremes and potential reversals. The indicator’s ability to adapt to price behavior makes it a versatile tool for traders focused on both short-term price deviations and longer-term mean-reversion strategies. With its unique blend of statistical rigor and visual clarity, the Mean Reversion Cloud provides an invaluable tool for understanding and capitalizing on market inefficiencies.
ICT Indicator with Paper TradingThe strategy implemented in the provided Pine Script is based on **ICT (Inner Circle Trader)** concepts, particularly focusing on **order blocks** to identify key levels for potential reversals or continuations in the market. Below is a detailed description of the strategy:
### 1. **Order Block Concept**
- **Order blocks** are price levels where large institutional orders accumulate, often leading to a reversal or continuation of price movement.
- In this strategy, **order blocks** are identified when:
- The high of the current bar crosses above the high of the previous bar (for bullish order blocks).
- The low of the current bar crosses below the low of the previous bar (for bearish order blocks).
### 2. **Buy and Sell Signal Generation**
The core of the strategy revolves around identifying the **breakout** of order blocks, which is interpreted as a signal to either enter or exit trades:
- **Buy Signal**:
- Generated when the closing price crosses **above** the last identified bullish order block (i.e., the highest point during the last upward crossover of highs).
- This signals a potential upward trend, and the strategy enters a long position.
- **Sell Signal**:
- Generated when the closing price crosses **below** the last identified bearish order block (i.e., the lowest point during the last downward crossover of lows).
- This signals a potential downward trend, and the strategy exits any open long positions.
### 3. **Strategy Execution**
The strategy is executed using the `strategy.entry()` and `strategy.close()` functions:
- **Enter Long Positions**: When a buy signal is generated, the strategy opens a long position (buying).
- **Exit Positions**: When a sell signal is generated, the strategy closes the long position.
### 4. **Visual Indicators on the Chart**
To make the strategy easier to follow visually, buy and sell signals are marked directly on the chart:
- **Buy signals** are indicated with a green upward-facing triangle above the bar where the signal occurred.
- **Sell signals** are indicated with a red downward-facing triangle below the bar where the signal occurred.
### 5. **Key Elements of the Strategy**
- **Trend Continuation and Reversals**: This strategy is attempting to capture trends based on the breakout of important price levels (order blocks). When the price breaks above or below a significant order block, it is expected that the market will continue in that direction.
- **Order Block Strength**: Order blocks are considered strong areas where price action could reverse or accelerate, based on how institutional investors place large orders.
### 6. **Paper Trading**
This script uses **paper trading** to simulate trades without actual money being involved. This allows users to backtest the strategy, seeing how it would have performed in historical market conditions.
### 7. **Basic Strategy Flow**
1. **Order Block Identification**: The script constantly monitors price movements to detect bullish and bearish order blocks.
2. **Buy Signal**: If the closing price crosses above the last order block high, the strategy interprets it as a sign of bullish momentum and enters a long position.
3. **Sell Signal**: If the closing price crosses below the last order block low, it signals a bearish momentum, and the strategy closes the long position.
4. **Visual Representation**: Buy and sell signals are displayed on the chart for easy identification.
### **Advantages of the Strategy:**
- **Simple and Clear Rules**: The strategy is based on clearly defined rules for identifying order blocks and trade signals.
- **Effective for Trend Following**: By focusing on breakouts of order blocks, this strategy attempts to capture strong trends in the market.
- **Visual Aids**: The plot of buy/sell signals helps traders to quickly see where trades would have been placed.
### **Limitations:**
- **No Shorting**: This strategy only enters long positions (buying). It does not account for shorting opportunities.
- **No Risk Management**: There are no built-in stop losses, trailing stops, or profit targets, which could expose the strategy to large losses during adverse market conditions.
- **Whipsaws in Range Markets**: The strategy could produce false signals in sideways or choppy markets, where breakouts are short-lived and prices quickly reverse.
### **Overall Strategy Objective:**
The goal of the strategy is to enter into long positions when the price breaks above a significant order block, and exit when it breaks below. The strategy is designed for trend-following, with the assumption that price will continue in the direction of the breakout.
Let me know if you'd like to enhance or modify this strategy further!
Charan_Trading_IndicatorCharan_Trading_Indicator Overview:
The Charan_Trading_Indicator combines several technical analysis tools, including Bollinger Bands, RSI (Relative Strength Index), VWAP (Volume-Weighted Average Price), and ATR (Average True Range), to provide buy and sell signals. The script incorporates multiple strategies, such as crack snap setups, overbought/oversold levels, and trend continuation indicators, all tailored for precise market entry and exit points.
Key Components:
RSI (Relative Strength Index):
The indicator uses RSI to detect overbought (RSI > 70) and oversold (RSI < 30) market conditions.
Alerts are triggered when prices are within the specified buy/sell range and RSI crosses these thresholds.
Bollinger Bands:
Bollinger Bands are calculated based on a configurable moving average and standard deviation.
The script identifies potential buy signals when the price dips below the lower Bollinger Band and recovers, and sell signals when the price exceeds the upper Bollinger Band and retraces.
Crack Snap Strategies:
The indicator incorporates multiple variations of the crack snap strategy:
Buy Signals: Triggered when price opens below the lower Bollinger Band and closes above it, alongside certain conditions in previous candles.
Sell Signals: Triggered when price opens above the upper Bollinger Band and closes below it, with similar candle patterns.
Variations such as 3-candle (3C) and 4-candle (4C) versions refine the crack snap setups for more robust signals.
Isolated Candle Conditions:
The indicator tracks isolated candles, where the entire candle lies above or below the Bollinger Bands, to identify potential reversal points.
Trend Continuation Signals:
Conditions based on the candle range and previous highs/lows allow the indicator to generate signals for trend continuation:
Buy signals when price breaks above the previous two highs.
Sell signals when price breaks below the previous two lows.
VWAP (Volume-Weighted Average Price):
The indicator integrates VWAP to give additional support and resistance levels, ensuring signals align with volume trends.
ATR-Based Stop Loss:
For both buy and sell conditions, the script plots stop-loss levels based on the ATR (Average True Range), giving dynamic risk management levels.
Buy/Sell Ranges:
The user can set minimum and maximum price ranges for buy and sell signals, ensuring that the indicator only generates alerts within desired price ranges.
How It Works:
Buy Signals: The script generates buy signals based on multiple conditions, including the crack snap strategy, oversold RSI levels, and trend continuation setups. When these conditions are met, green triangles appear below the price bars, and an alert is triggered.
Sell Signals: Sell signals are triggered when the opposite conditions are met (overbought RSI, crack snap sell setups, trend breaks), and red triangles appear above the price bars.
Visual Indicators: The script plots upper and lower Bollinger Bands, stop loss levels, and VWAP on the chart, providing a comprehensive view of market conditions and support/resistance levels.
This indicator is versatile, combining multiple technical tools for robust decision-making in trading. It generates alerts, plots visual markers, and integrates risk management, making it a well-rounded tool for technical analysis.
This indicator is versatile, combining multiple technical tools for robust decision-making in trading. It generates alerts, plots visual markers, and integrates risk management, making it a well-rounded tool for technical analysis.
Varanormal Mac N Cheez Strategy v1Mac N Cheez Strategy (Set a $200 Take profit Manually)
It's super cheesy. Strategy does the following:
Here's a detailed explanation of what the entire script does, including its key components, functionality, and purpose.
1. Strategy Setup and Input Parameters:
Strategy Name: The script is named "NQ Futures $200/day Strategy" and is set as an overlay, meaning all elements (like moving averages and signals) are plotted on the price chart.
Input Parameters:
fastLength: This sets the length of the fast moving average. The user can adjust this value, and it defaults to 9.
slowLength: This sets the length of the slow moving average. The user can adjust this value, and it defaults to 21.
dailyTarget: The daily profit target, which defaults to $200. If set to 0, this disables the daily profit target.
stopLossAmount: The fixed stop-loss amount per trade, defaulting to $100. This value is used to calculate how much you're willing to lose on a single trade.
trailOffset: This value sets the distance for a trailing stop. It helps protect profits by automatically adjusting the stop-loss as the price moves in your favor.
2. Calculating the Moving Averages:
fastMA: The fast moving average is calculated using the ta.sma() function on the close price with a period length of fastLength. The ta.sma() function calculates the simple moving average.
slowMA: The slow moving average is also calculated using ta.sma() but with the slowLength period.
These moving averages are used to determine trend direction and identify entry points.
3. Buy and Sell Signal Conditions:
longCondition: This is the buy condition. It occurs when the fast moving average crosses above the slow moving average. The script uses ta.crossover() to detect this crossover event.
shortCondition: This is the sell condition. It occurs when the fast moving average crosses below the slow moving average. The script uses ta.crossunder() to detect this crossunder event.
4. Executing Buy and Sell Orders:
Buy Orders: When the longCondition is true (i.e., fast MA crosses above slow MA), the script enters a long position using strategy.entry("Buy", strategy.long).
Sell Orders: When the shortCondition is true (i.e., fast MA crosses below slow MA), the script enters a short position using strategy.entry("Sell", strategy.short).
5. Setting Stop Loss and Trailing Stop:
Stop-Loss for Long Positions: The stop-loss is calculated as the entry price minus the stopLossAmount. If the price falls below this level, the trade is exited automatically.
Stop-Loss for Short Positions: The stop-loss is calculated as the entry price plus the stopLossAmount. If the price rises above this level, the short trade is exited.
Trailing Stop: The trail_offset dynamically adjusts the stop-loss as the price moves in favor of the trade, locking in profits while still allowing room for market fluctuations.
6. Conditional Daily Profit Target:
The script includes a daily profit target that automatically closes all trades once the total profit for the day reaches or exceeds the dailyTarget.
Conditional Logic:
If the dailyTarget is greater than 0, the strategy checks whether the strategy.netprofit (total profit for the day) has reached or exceeded the target.
If the strategy.netprofit >= dailyTarget, the script calls strategy.close_all(), closing all open trades for the day and stopping further trading.
If dailyTarget is set to 0, this logic is skipped, and the script continues trading without a daily profit target.
7. Plotting Moving Averages:
plot(fastMA): This plots the fast moving average as a blue line on the price chart.
plot(slowMA): This plots the slow moving average as a red line on the price chart. These help visualize the crossover points and the trend direction on the chart.
8. Plotting Buy and Sell Signals:
plotshape(): The script uses plotshape() to add visual markers when buy or sell conditions are met:
"Long Signal": When a buy condition (longCondition) is met, a green marker is plotted below the price bar with the label "Long".
"Short Signal": When a sell condition (shortCondition) is met, a red marker is plotted above the price bar with the label "Short".
These markers help traders quickly see when buy or sell signals occurred on the chart.
In addition, triangle markers are plotted:
Green Triangle: Indicates where a buy entry occurred.
Red Triangle: Indicates where a sell entry occurred.
Summary of What the Script Does:
Inputs: The script allows the user to adjust moving average lengths, daily profit targets, stop-loss amounts, and trailing stop offsets.
Signals: It generates buy and sell signals based on the crossovers of the fast and slow moving averages.
Order Execution: It executes long positions on buy signals and short positions on sell signals.
Stop-Loss and Trailing Stop: It sets dynamic stop-losses and uses a trailing stop to protect profits.
Daily Profit Target: The strategy stops trading for the day once the net profit reaches the daily target (unless the target is disabled by setting it to 0).
Visual Markers: It plots moving averages and buy/sell signals directly on the main price chart to aid in visual analysis.
This script is designed to trade based on moving average crossovers, with robust risk management features like stop-loss and trailing stops, along with an optional daily profit target to limit daily trading activity. Let me know if you need further clarification or want to adjust any specific part of the script!
Anomaly Detection with Standard Deviation [CHE]Anomaly Detection with Standard Deviation in Trading
Application for Traders
Traders can use this indicator to identify potential turning points in the market. Anomalies above the upper threshold may indicate overbought conditions, suggesting a possible reversal or sell opportunity. Conversely, anomalies below the lower threshold might signal oversold conditions, presenting a potential buying opportunity. By combining these signals with other technical analysis tools, traders can make more informed decisions and refine their trading strategies.
Introduction
Welcome to this presentation on Anomaly Detection using Standard Deviation in the context of trading. This method helps traders identify unusual price movements that may indicate potential trading opportunities. We will walk through the concept, explain how to set up the indicator, and discuss how traders can utilize it effectively.
Concept Overview
Anomaly Detection using Standard Deviation is a statistical method that identifies price points in a financial market that deviate significantly from the norm. The method relies on calculating the moving average and the standard deviation of a chosen price indicator over a specified period. By defining thresholds (e.g., 3 standard deviations above and below the mean), the method flags these deviations as anomalies, which can signal potential trading opportunities.
1. Selecting the Data Source
Description: The first step in setting up the indicator is choosing the price data that will be analyzed. Common options include the closing price, opening price, highest price, lowest price, or a combination of these (such as the average of the open, high, low, and close prices, known as OHLC4).
Importance: The choice of data source affects the sensitivity and relevance of the detected anomalies.
2. Setting the Calculation Period
Description: The calculation period refers to the number of time units (such as days, hours, or minutes) used to compute the moving average and standard deviation. A typical default period might be 20 units.
Importance: A shorter period makes the indicator more responsive to recent changes, while a longer period smooths out short-term fluctuations and highlights more significant trends.
3. Determining the Number of Displayed Lines and Labels
Description: Traders can configure how many anomaly lines and labels are displayed on the chart at any given time. This is crucial for maintaining a clear and readable chart, especially in volatile markets.
Importance: Limiting the number of displayed anomalies helps avoid clutter and focuses attention on the most recent or relevant data points.
4. Calculating the Mean and Standard Deviation
Description: The mean (or moving average) represents the central tendency of the price data, while the standard deviation measures the dispersion or volatility around this mean.
Importance: These statistical measures are fundamental to determining the thresholds for what constitutes an "anomaly."
5. Defining Anomaly Thresholds
Description: Anomaly thresholds are typically set at 3 standard deviations above and below the mean. Prices that exceed these thresholds are considered anomalies, signaling potential overbought (above the upper threshold) or oversold (below the lower threshold) conditions.
Importance: These thresholds help traders identify extreme market conditions that might present trading opportunities.
6. Identifying Anomalies
Description: The indicator checks whether the high or low prices exceed the defined thresholds. If they do, these price points are flagged as anomalies.
Importance: Identifying these points can alert traders to unusual market behavior, prompting them to consider buying, selling, or holding their positions.
7. Visualizing the Anomalies
Description: The indicator plots the thresholds on the chart as lines, with anomalies highlighted through additional visual cues, such as labels or lines.
Importance: This visualization makes it easy for traders to spot significant deviations from the norm, which might warrant further analysis or immediate action.
8. Managing Displayed Anomalies
Description: To keep the chart organized, the indicator automatically removes the oldest lines and labels when the number exceeds the user-defined limit.
Importance: This feature ensures that the chart remains clear and focused on the most relevant data points, preventing information overload.
Conclusion
The Anomaly Detection with Standard Deviation indicator is a powerful tool for identifying significant deviations in market behavior. By customizing parameters such as the calculation period and the number of displayed anomalies, traders can tailor the indicator to suit their specific needs, leading to more effective trading decisions.
Best regards
Chervolino
Enhanced Alligator Trend Indicator By Er. Parvez HaleemPurpose: The Enhanced Alligator Trend Indicator aims to identify strong and reliable buy and sell signals on the price chart by combining the Alligator Indicator with trend strength and volume filters. It is specifically designed for use on a 1-minute chart to enhance precision in short-term trading decisions.
Components:
Alligator Indicator:
Jaw Line (Blue): Calculated as a simple moving average (SMA) of the closing price over a specified period (default: 13 bars). Represents the long-term trend.
Teeth Line (Red): Calculated as a simple moving average (SMA) of the closing price over a shorter period (default: 8 bars). Represents the medium-term trend.
Lips Line (Green): Calculated as a simple moving average (SMA) of the closing price over an even shorter period (default: 5 bars). Represents the short-term trend.
Trend Strength Indicator:
Relative Strength Index (RSI): Measures the strength of the current trend, using a default period of 14 bars. RSI values above 50 suggest a bullish trend, while values below 50 suggest a bearish trend.
Volume Filter:
Volume Threshold: Filters signals based on trading volume to ensure they only appear when volume exceeds a specified threshold (default: 100,000). This helps to avoid low-volume noise and enhance signal reliability.
Additional Trend Filters:
Short-Term SMA: A simple moving average with a default period of 20 bars, used to assess short-term trend direction.
Long-Term SMA: A simple moving average with a default period of 50 bars, used to assess long-term trend direction.
SMA Crossover: A bullish crossover occurs when the short-term SMA is above the long-term SMA, and a bearish crossover occurs when the short-term SMA is below the long-term SMA.
Signal Generation:
Buy Signal: Generated when:
The Lips line is above the Teeth line, and the Teeth line is above the Jaw line (indicating a bullish alignment in the Alligator Indicator).
The RSI is above 50 (indicating strong bullish trend strength).
The trading volume exceeds the specified volume threshold (indicating sufficient trading activity).
The short-term SMA is above the long-term SMA (confirming a bullish trend).
Sell Signal: Generated when:
The Lips line is below the Teeth line, and the Teeth line is below the Jaw line (indicating a bearish alignment in the Alligator Indicator).
The RSI is below 50 (indicating strong bearish trend strength).
The trading volume exceeds the specified volume threshold (indicating sufficient trading activity).
The short-term SMA is below the long-term SMA (confirming a bearish trend).
Plotting on Chart:
Alligator Lines: The Jaw, Teeth, and Lips lines are plotted directly on the price chart in blue, red, and green, respectively, to indicate the long-term, medium-term, and short-term trends.
Buy/Sell Signals: Buy signals are plotted below the price bars in green, and sell signals are plotted above the price bars in red. These signals are marked with labels ("BUY" and "SELL") to clearly indicate trading opportunities.
Debugging: RSI and SMA lines are plotted but hidden by default. They can be revealed for verification purposes to ensure the correctness of the indicator’s calculations.
Alerts:
Buy Alert: Triggers when a buy signal condition is met, sending a notification that a buy opportunity has been identified.
Sell Alert: Triggers when a sell signal condition is met, sending a notification that a sell opportunity has been identified.
Supply and Demand Zones with Enhanced SignalsThis Pine Script indicator combines supply and demand zone analysis with dynamic buy/sell signals to enhance trading strategies. It provides a robust framework for identifying optimal trading opportunities and managing existing trades.
Key Features:
Supply and Demand Zones: The indicator identifies significant supply and demand zones based on recent price action. These zones are plotted as horizontal lines to help traders visualize potential reversal points.
Exponential Moving Average (EMA): A 21-period EMA is used to determine the prevailing trend and generate buy and sell signals.
Relative Strength Index (RSI): The 14-period RSI is utilized to filter buy and sell signals, providing additional context on overbought and oversold conditions.
Signal Generation:
Buy Signal: Triggered when the price crosses above the EMA and RSI indicates that the market is not overbought.
Sell Signal: Triggered when the price crosses below the EMA and RSI indicates that the market is not oversold.
Enhanced Exit Signals:
Exit Buy Signal: Generated if an opposite sell signal occurs or the higher timeframe RSI indicates overbought conditions.
Exit Sell Signal: Generated if an opposite buy signal occurs or the higher timeframe RSI indicates oversold conditions.
Trade Management:
Tracks active trades and provides exit signals based on the occurrence of opposite trading signals. This helps in managing positions more effectively and reducing potential losses.
Usage:
Supply and Demand Zones: Look for price action around these zones to identify potential trading opportunities.
EMA and RSI: Use buy and sell signals in conjunction with EMA and RSI to validate trading decisions.
Higher Timeframe RSI: Utilize this for additional confirmation and exit signals.
Plotting:
Supply Zone: Plotted as a red horizontal line.
Demand Zone: Plotted as a green horizontal line.
EMA: Plotted as a blue line.
Buy and Sell Signals: Indicated by green and red triangle shapes, respectively.
Exit Signals: Indicated by blue and orange X shapes.
This indicator is designed to help traders make informed decisions by combining technical analysis with strategic trade management.
Volatility Adaptive Signal Tracker (VAST)The Adaptive Trend Following Buy/Sell Signals Pine Script is designed to help traders identify and capitalize on market trends using an adaptive trend-following strategy. This script focuses on generating reliable buy and sell signals by analyzing market trends and volatility. It simplifies the trading process by providing clear signals without plotting additional lines, making it easy to use and interpret.
Key Features:
Adaptive Trend Following:
The script employs an adaptive trend-following approach that leverages market volatility to generate buy and sell signals. This method is effective in both trending and volatile markets.
Inputs and Customization:
The script includes customizable parameters for the Simple Moving Average (SMA) length, the Average True Range (ATR) length, and the ATR multiplier. These inputs allow traders to adjust the sensitivity of the signals to match their trading style and market conditions.
Signal Generation:
Buy Signal: Generated when the closing price crosses above the upper adaptive band, indicating a potential upward trend.
Sell Signal: Generated when the closing price crosses below the lower adaptive band, indicating a potential downward trend.
Visual Signals:
The script uses plotshape to mark buy signals with green labels below the bars and sell signals with red labels above the bars. This clear visual representation helps traders quickly identify trading opportunities.
Alert Conditions:
The script sets up alert conditions for both buy and sell signals. Traders can use these alerts to receive notifications when a signal is generated, ensuring they do not miss any trading opportunities.
How It Works:
SMA Calculation: The script calculates the Simple Moving Average (SMA) over a specified period, which helps in identifying the general trend direction.
ATR Calculation: The Average True Range (ATR) is calculated to measure market volatility.
Adaptive Bands: Upper and lower adaptive bands are created by adding and subtracting a multiple of the ATR to the SMA, respectively.
Signal Logic: Buy signals are generated when the closing price crosses above the upper band, while sell signals are generated when the closing price crosses below the lower band.
Example Use Case:
A trader looking to capitalize on medium-term trends in the Nifty futures market can use this script to receive timely buy and sell signals. By customizing the SMA length and ATR parameters, the trader can fine-tune the script to match their trading strategy, ensuring they enter and exit trades at optimal points.
Benefits:
Simplicity: The script provides clear buy and sell signals without cluttering the chart with additional lines or indicators.
Adaptability: Customizable parameters allow traders to adapt the script to various market conditions and trading styles.
Alerts: Built-in alert conditions ensure traders receive timely notifications, helping them to act quickly on trading signals.
How to Use:
Open TradingView: Go to the TradingView website and log in.
Create a New Chart: Click on the “Chart” button to open a new chart.
Open the Pine Script Editor: Click on the “Pine Editor” tab at the bottom of the chart.
Create a New Script: Delete any default code in the Pine Script editor and paste the provided script.
Add to Chart: Click on the “Add to Chart” button to compile and add the script to your chart.
Save the Script: Click “Save” and name the script.
Set Alerts: Right-click on the chart, select “Add Alert,” and choose the appropriate condition to set alerts for buy and sell signals.
Carlos IndexOverview:
The "Carlos Index" is designed to help traders identify potential buy and sell opportunities by combining an Exponential Moving Average (EMA) with recent high and low levels of price action. This indicator is particularly useful for those looking to spot trend reversals and potential support/resistance zones.
How It Works:
EMA Calculation: The indicator uses a customizable EMA to smooth price data, making it easier to identify the underlying trend. The default length of the EMA is set to 20 periods, but this can be adjusted to suit different trading styles or timeframes.
High and Low Levels: The script plots the highest and lowest prices over the last 8 periods, providing a visual representation of recent market extremes. These levels can act as potential support and resistance areas.
Buy and Sell Signals: The indicator generates buy and sell signals based on the crossover and crossunder of the price and the EMA. A "Buy" signal is generated when the price crosses above the EMA and was higher than the previous period, indicating a potential bullish reversal. Conversely, a "Sell" signal appears when the price crosses below the EMA and was lower than the previous period, suggesting a bearish reversal.
Customization:
Length: The period length for the EMA can be adjusted to better fit the user's trading strategy.
Source: Users can select the price source for the EMA calculation, such as close, open, high, or low prices.
Originality and Usefulness:
The "Carlos Index" combines traditional technical analysis tools in a unique way to enhance traders' decision-making processes. While moving averages and price extremes are commonly used in market analysis, this indicator integrates them to provide a more holistic view of market conditions. The combination of EMA crossovers with recent high and low levels helps identify potential trend reversals and market sentiment changes more effectively.
What sets the "Carlos Index" apart is its dual approach to signal generation: it not only uses EMA crossovers but also considers the immediate price movement relative to the previous period, adding a layer of confirmation to buy and sell signals. This feature aims to reduce false signals and improve the accuracy of market entry and exit points.
Additionally, the customizable settings allow traders to tailor the indicator to their specific trading strategies, making it adaptable across different market environments and timeframes. The clear visual cues provided by the plotted EMA and price levels, along with the buy/sell labels, offer an intuitive understanding of market dynamics, even for those new to technical analysis.
Chart Usage:
This indicator should be used on a clean chart for best visibility.
The plotted lines (EMA, highs, and lows) and signals (Buy/Sell labels) provide a straightforward visual guide for traders.
By using the Carlos Index, traders can gain a clearer understanding of market dynamics and make more informed trading decisions. This script combines both trend-following and mean-reversion elements, making it versatile across various market conditions.
Jobinsabu014This Pine Script code is for an advanced trading indicator that displays enhanced moving averages with buy and sell labels, trend probability, and support/resistance levels. Here’s a detailed description of its components and functionality:
### Description:
1. **Indicator Initialization**:
- The indicator is named "Enhanced Moving Averages with Buy/Sell Labels and Trend Probability" and is set to overlay on the chart.
2. **Input Parameters**:
- **Moving Averages**: Four different moving averages (short and long periods for default and enhanced) with customizable periods.
- **Probability Threshold**: Determines the threshold for trend probability.
- **Support/Resistance Lookback**: Number of bars to look back for calculating support and resistance levels.
- **Signals Valid From**: Timestamp from which the signals are considered valid.
3. **Moving Averages Calculation**:
- **Default Moving Averages**: Calculated using simple moving averages (SMA) for the specified periods.
- **Enhanced Moving Averages**: Calculated using SMAs for different specified periods.
4. **Plotting Moving Averages**:
- Plots the default and enhanced moving averages with different colors for distinction.
5. **Crossover Detection**:
- Detects when the short moving average crosses above or below the long moving average for default moving averages.
6. **Buy/Sell Signal Labels**:
- Adds "BUY" and "SELL" labels on the chart when crossovers are detected after the specified valid timestamp.
- Tracks entry prices for buy/sell signals and adds labels when the price moves +100 points.
7. **Trend Detection for Enhanced Indicator**:
- Detects uptrend or downtrend based on the enhanced moving averages.
- Calculates a simple probability of trend based on price movement and EMA.
- Determines buy and sell signals based on trend conditions and volume-based buy/sell pressure.
8. **Plot Buy/Sell Signals for Enhanced Indicator**:
- Plots buy/sell signals based on the enhanced conditions.
9. **Background Color for Trends**:
- Changes the background color to green for uptrend and red for downtrend.
10. **Trend Lines**:
- Draws imaginary trend lines for uptrend and downtrend based on enhanced moving averages.
11. **Support and Resistance Levels**:
- Calculates and plots support and resistance levels using the specified lookback period.
- Stores and plots previous support and resistance levels with dashed lines.
12. **Expected Trend Labels**:
- Adds labels indicating expected uptrend or downtrend based on buy/sell signals.
13. **Alerts**:
- Sets alert conditions for buy and sell signals, triggering alerts when these conditions are met.
14. **Demand and Supply Zones**:
- Draws and extends horizontal lines for demand (support) and supply (resistance) zones.
### Summary:
This script enhances traditional moving average crossovers by adding trend probability calculations, volume-based pressure, and support/resistance levels. It visualizes expected trends and provides comprehensive buy/sell signals with corresponding labels, background color changes, and alerts to help traders make informed decisions.
Notional Trade Table
Notional Trade Table indicator displays notional trade values for given Buy and Sell of given input of Symbol, Quantity, Entry Price and Stop Loss .
Sections of Input Menu Table are supported with Tool Tip icons.
Input Symbols:
(Refer Input Menu)
User can choose maximum 20 Symbols.
Input Side Choice (BUY/SELL):
(Refer Input Menu)
After choosing Symbol, User has to choose the BUY or SELL option for each Symbol against the corresponding Sybol number. If NIL is selected “Nil is selected ” message is displayed prompting the user to select BUY or SELL sides.
For example in the above Input Menu:
Sym1 is BATS:AAPL. Corresponding Side 1 is Sell1.
Sym2 is BATS:NVDA Corresponding Side 2 Sell 2.
Sym12 is BATS:NFLX. Corresponding Side 12 is Buy12 and so on.
Input Quantity:
(Refer Input Menu)
Next enter Corresponding Quantity of BUY or SELL in relevant Quantity Input Box. Quantity cannot be Zero. Defval is 1.
For Sym1 input in Qty 1 box,for Sym2 input in Qty 2 box and so on.
Input Entry Price:
(Refer Input Menu)
After entering Quantity Input Entry Price for Corresponding Symbol.
Input for Sym1 Entry Price in EP1 box
Input for Sym2 Entry Price in EP2 box
and so on.
Input Stop Loss:
(Refer Input Menu)
Next Enter corresponding Stop Loss for each Symbol.
SL1 input box denotes Sym1 Stop Loss.
SL2 input box denotes Sym2 Stop Loss.
SL3 input box denotes Sym3 Stop Loss and so on.
Stop Loss for Chosen BUY side should be below corresponding Entry Price/Last Price. Otherwise a message is displayed “SL Hit”. User has to enter valid data.
Stop Loss for Chosen SELL side should be above corresponding Entry Price/Last Price. Otherwise a message is displayed “SL Hit”. User has to enter valid data.
Notional Trade Table:
(Refer the Table on Chart)
From the input menu filled by User script captures the Symbol, BUY/SELL options, Quantity,
Entry Price and Stop Loss details under the corresponding heads in the Notional Trade Table.
The script captures the live Last traded Price under the head LP and calculates and displays corresponding Profit or Loss under PR/LO column in the table.
SL+- LP is the difference between Last traded Price (LP) and Stop Loss Price. Positive figure under this head reflects Stop Loss cushion available .
Nil header column reflects message “NIL selected” prompting the User to select BUY or SELL sides.
SLH header displays “SL Hit” on Stop Loss Hit or wrong input of Stop Loss inconsistent with BUY or SELL sides of Trade. On “SL Hit” message all values in corresponding Symbol becomes Zero. User has to re-enter the details fresh .
On the top left side corner of the table there are 2 cells with Prono and Lono.They denote the number of trades which are in Profit (Prono) and which are in Loss(Lono).
It is preferable to choose Symbols from a single country exchange commensurate with the Time zone. Otherwise if Exchange and Chart time Zone differs there is risk of data loss in the table.
DISCLAIMER: For educational and entertainment purpose only .Nothing in this content should be interpreted as financial advice or a recommendation to buy or sell any sort of security/ies or investment/s.
Supertrend + BB + Consecutive Candles + QQE + EMA [Pineify]Overview
This indicator, developed by Pineify, is a comprehensive tool designed to assist traders in making informed decisions by combining multiple technical analysis methods. It integrates Supertrend, Bollinger Bands (BB), Consecutive Candles, Quantitative Qualitative Estimation (QQE), and Exponential Moving Averages (EMA) into a single, cohesive script. This multi-faceted approach allows traders to analyze market trends, volatility, and potential buy/sell signals with greater accuracy.
Key Features
1. Supertrend: Utilizes the Supertrend indicator to identify the prevailing market trend. It provides clear buy and sell signals based on the direction of the trend.
2. Bollinger Bands (BB): Measures market volatility and identifies overbought or oversold conditions. The script calculates the middle, upper, and lower bands, along with the Bollinger Band Width (BBW) and Bollinger Band %B (BBR).
3. Consecutive Candles: Detects sequences of consecutive bullish or bearish candles, providing signals when a specified number of consecutive candles are detected.
4. Quantitative Qualitative Estimation (QQE): Combines the Relative Strength Index (RSI) with a smoothing factor to generate buy and sell signals based on the QQE methodology.
5. Exponential Moving Averages (EMA): Includes both fast and slow EMAs to identify potential crossovers, which are used as buy and sell signals.
How It Works
- Supertrend: The Supertrend indicator is calculated using a factor and ATR length. It plots the trend direction and generates buy/sell signals when the trend changes.
- Bollinger Bands: The BB indicator calculates the middle band as a Simple Moving Average (SMA) of the closing prices. The upper and lower bands are derived by adding and subtracting a multiple of the standard deviation from the middle band.
- Consecutive Candles: This feature counts the number of consecutive candles that close higher or lower than the previous candle. When the count reaches a specified threshold, it generates a buy or sell signal.
- QQE: The QQE indicator smooths the RSI values and calculates the QQE Fast and QQE Slow lines. Buy and sell signals are generated based on the crossover of these lines.
- EMA: The script calculates fast and slow EMAs and generates buy/sell signals based on their crossovers.
How to Use
1. Inputs: Customize the indicator settings through the input parameters:
- Supertrend Factor and ATR Length
- BB Length
- Consecutive Candles Counting
- QQE RSI Length
- Fast and Slow EMA Lengths
- Enable/Disable Alerts for various signals
2. Alerts: Set up alerts for Supertrend, Consecutive Candles, and EMA crossovers. Alerts can be enabled or disabled based on user preference.
3. Visualization: The indicator plots the Supertrend, Bollinger Bands, and EMA lines on the chart. It also marks buy and sell signals with arrows and labels for easy identification.
Concepts Underlying Calculations
- Supertrend: Based on the Average True Range (ATR) to determine the trend direction and potential reversal points.
- Bollinger Bands: Utilizes standard deviation to measure market volatility and identify overbought/oversold conditions.
- Consecutive Candles: A method to detect momentum by counting consecutive bullish or bearish candles.
- QQE: Enhances the traditional RSI by smoothing it and using a dynamic threshold to generate signals.
- EMA: A widely used moving average that gives more weight to recent prices, making it responsive to market changes.
This indicator is a powerful tool for traders looking to combine multiple technical analysis methods into a single, easy-to-use script. By integrating these diverse techniques, it provides a comprehensive view of market conditions and potential trading opportunities.
Market Structure Volume Distribution [LuxAlgo]The Market Structure Volume Distribution tool allows traders to identify the strength behind breaks of market structure at defined price ranges to measure de correlation of forces between bulls and bears visually and easily.
🔶 USAGE
This tool has three main features: market structure highlighting, grid levels, and volume profile. Each feature is covered more in depth below:
🔹 Market Structure
The basic unit of market structure is a swing point, the period of the swing point is user-defined, so traders can identify longer-term market structures. Price breaking a prior swing point will confirm the occurrence of a market structure.
The tool will plot a line after a market structure is confirmed, by default the lines on bullish MS will be green (indicative of an uptrend), and red in case of bearish MS (indicative of a downtrend).
🔹 Grid Levels
The Grid visually divides the price range contained inside the tool execution window, into equal size rows, the number of rows is user-defined so users can divide the full price range up to 100 rows.
The main objective of this feature is to help identify the execution window and the limits of each row in the volume profile so traders can know in a simple look what BoMS belongs to each row.
There is however another use for the grid, by dividing the range into equal-sized parts, this feature provides automatic support and resistance levels as good as any other.
Grid provides a visual help to know what our execution window is and to associate MS with their rows in the profile. It can provide S/R levels too.
🔹 Volume Profile
The volume profile feature shows in a visually easy way the volume behind each MS aggregated by rows and divided into buy and sell volume to spot the differences in a simple look.
This tool allows users to spot the liquidity associated with the event of a market structure in a specific price range, allowing users to know which price areas where associated with the most trading activity during the occurrence of a market structutre.
🔶 SETTINGS
🔹 Data Gathering
Execute on all visible range: Activate this to use all visible bars on the calculations. This disables the use of the next parameter "Execute on the last N bars". Default false.
Execute on the last N bars: Use last N bars on the calculations. To use this parameter "Execute on all visible range" must be disabled. Values from 20 to 5000, default 500.
Pivot Length: How many bars will be used to confirm a pivot. The bigger this parameter is the fewer breaks of structure will detect. Values from 1, default 2
🔹 Profile
Profile Rows: Number of rows in the volume profile. Values from 2 to 100, default 10.
Profile Width: Maximum width of the volume profile. Values from 25 to 500, default 200.
Profile Mode: How the volume will be displayed on each row. "TOTAL VOLUME" will aggregate buy & sell volume per row, "BUY&SELL VOLUME" will separate the buy volume from the sell volume on each row. Default BUY&SELL VOLUME.
🔹 Style
Buy Color: This is the color for the buy volume on the profile when the "BUY&SELL VOLUME" mode is activated. Default green.
Sell Color: This is the color for the sell volume on the profile when the "BUY&SELL VOLUME" mode is activated. Default red.
Show dotted grid levels: Show dotted inner grid levels. Default true.
footprint_typeLibrary "footprint_type"
Contains all types for calculating and rendering footprints
Inputs
Inputs objects
Fields:
inbalance_percent (series int) : percentage coefficient to determine the Imbalance of price levels
stacked_input (series int) : minimum number of consecutive Imbalance levels required to draw extended lines
show_summary_footprint (series bool) : bool input for show summary footprint
procent_volume_area (series int) : definition size Value area
show_vah (series bool) : bool input for show VAH
show_poc (series bool) : bool input for show POC
show_val (series bool) : bool input for show VAL
color_vah (series color) : color VAH line
color_poc (series color) : color POC line
color_val (series color) : color VAL line
show_volume_profile (series bool)
new_imbalance_cond (series bool) : bool input for setup alert on new imbalance buy and sell
new_imbalance_line_cond (series bool) : bool input for setup alert on new imbalance line buy and sell
stop_past_imbalance_line_cond (series bool) : bool input for setup alert on stop past imbalance line buy and sell
Constants
Constants all Constants objects
Fields:
imbalance_high_char (series string) : char for printing buy imbalance
imbalance_low_char (series string) : char for printing sell imbalance
color_title_sell (series color) : color for footprint sell
color_title_buy (series color) : color for footprint buy
color_line_sell (series color) : color for sell line
color_line_buy (series color) : color for buy line
color_title_none (series color) : color None
Calculation_data
Calculation_data data for calculating
Fields:
detail_open (array) : array open from calculation timeframe
detail_high (array) : array high from calculation timeframe
detail_low (array) : array low from calculation timeframe
detail_close (array) : array close from calculation timeframe
detail_vol (array) : array volume from calculation timeframe
previos_detail_close (array) : array close from calculation timeframe
isBuyVolume (series bool) : attribute previosly bar buy or sell
Footprint_row
Footprint_row objects one footprint row
Fields:
price (series float) : row price
buy_vol (series float) : buy volume
sell_vol (series float) : sell volume
imbalance_buy (series bool) : attribute buy inbalance
imbalance_sell (series bool) : attribute sell imbalance
buy_vol_box (series box) : for ptinting buy volume
sell_vol_box (series box) : for printing sell volume
buy_vp_box (series box) : for ptinting volume profile buy
sell_vp_box (series box) : for ptinting volume profile sell
row_line (series label) : for ptinting row price
empty (series bool) : = true attribute row with zero volume buy and zero volume sell
Value_area
Value_area objects for calculating and printing Value area
Fields:
vah_price (series float) : VAH price
poc_price (series float) : POC price
val_price (series float) : VAL price
vah_label (series label) : label for VAH
poc_label (series label) : label for POC
val_label (series label) : label for VAL
vah_line (series line) : line for VAH
poc_level (series line) : line for POC
val_line (series line) : line for VAL
Imbalance_line_var_object
Imbalance_line_var_object var objects printing and calculation imbalance line
Fields:
cum_buy_line (array) : line array for saving all history buy imbalance line
cum_sell_line (array) : line array for saving all history sell imbalance line
Imbalance_line
Imbalance_line objects printing and calculation imbalance line
Fields:
buy_price_line (array) : float array for saving buy imbalance price level
sell_price_line (array) : float array for saving sell imbalance price level
var_imba_line (Imbalance_line_var_object) : var objects this type
Footprint_info_var_object
Footprint_info_var_object var objects for info printing
Fields:
cum_delta (series float) : var delta volume
cum_total (series float) : var total volume
cum_buy_vol (series float) : var buy volume
cum_sell_vol (series float) : var sell volume
cum_info (series table) : table for ptinting
Footprint_info
Footprint_info objects for info printing
Fields:
var_info (Footprint_info_var_object) : var objects this type
total (series label) : total volume
delta (series label) : delta volume
summary_label (series label) : label for ptinting
Footprint_bar
Footprint_bar all objects one bar with footprint
Fields:
foot_rows (array) : objects one row footprint
val_area (Value_area) : objects Value area
imba_line (Imbalance_line) : objects imbalance line
info (Footprint_info) : objects info - table,label and their variable
row_size (series float) : size rows
total_vol (series float) : total volume one footprint bar
foot_buy_vol (series float) : buy volume one footprint bar
foot_sell_vol (series float) : sell volume one footprint bar
foot_max_price_vol (map) : map with one value - price row with max volume buy + sell
calc_data (Calculation_data) : objects with detail data from calculation resolution
Support_objects
Support_objects support object for footprint calculation
Fields:
consts (Constants) : all consts objects
inp (Inputs) : all input objects
bar_index_show_condition (series bool) : calculation bool value for show all objects footprint
row_line_color (series color) : calculation value - color for row price
Pivot Points + Day First Candle Breakout + VWAP + Supertrend This indicator amalgamates several key indicators to provide a comprehensive analysis for trading decisions, including SuperTrend, Pivot Points, VWAP, along with the Day First Candle Breakout strategy.
Key Features:
Day First Candle Breakout: Identifies potential breakout opportunities based on the first candle of the trading day. It utilizes the high and low of the initial trading range to determine entry points.
Timeframe Selection: Allows users to select the timeframe for analyzing the first candle (e.g., 5, 15, or 60 minutes).
Previous Day and Week High/Low: Displays the high and low of the previous day and week to provide additional context for trading decisions and assess the strength of the trend.
Trend Strength Analysis: Indicates whether the current price is above or below the previous day's high or low, signaling a stronger bullish or bearish trend respectively.
SuperTrend Indicator: Visualizes the trend direction and potential reversal points based on the SuperTrend indicator. It helps traders to stay aligned with the prevailing trend and avoid premature exits.
Pivot Points: Presents key support and resistance levels derived from Pivot Points, assisting traders in identifying potential reversal or breakout zones.
VWAP (Volume Weighted Average Price): Plots VWAP to provide insight into the average price traded over a given period, aiding in determining the fair value of the asset and potential buying/selling zones.
Trading Signals:
Buy Signal: Triggered when the price exceeds the high of the initial trading range after an upward price gap.
Sell Signal: Generated when the price falls below the low of the initial trading range after a downward price gap.
Caveats for Effective Trading:
Extended Trading Ranges: Adjusts support and resistance levels if the initial trading range extends beyond the defined timeframe.
Morning Noise Consideration: Exercises caution during volatile morning sessions to avoid false breakouts and whipsaws.
Pullbacks and Narrow Range Bars: Looks for opportunities during pullbacks or when the price forms narrow range bars to enter trades, reducing the risk of sudden reversals.
MACD by Take and TradeImproved version of MACD with asymmetrical BUY and SELL approaches.
This indicator is based on popular MACD one, but with some "tricks" designed to make it more applicable to the rapidly changing crypto market.
Key benefits:
Dynamic auto-adjusted threshold to filter out weak signals
Highlighted BUY/SELL signals with divergence (if a signal is accompanied by divergence, for example, price makes a new high while macd has a second high below the first, this signal is considered stronger and will be highlighted in a darker color)
Boost BUY signals on very slow market in accumulation phase
Not symmetric! It uses 2 different signal lines, which allows to obtain SELL signals earlier comparing to classic MACD approach
Classic concept of MACD
Classic MACD, in its simplest case, consists of two lines - macd line and signal line. Macd line is a difference between so-called "fast" and "slow" EMA lines (there are just a Exponential Moving Average lines with different windows: "12" for fast and "26" for slow). Signal line is just a smoothed "macd" line.
When macd line crosses signal line from bottom to up and intersection point < 0, this is "BUY" signal. And vise versa, when macd line crosses signal line from top to bottom, and intersection point > 0, this is "SELL" signal.
Parameters used in default configuration of classic MACD indicator:
Fast line: EMA-12
Slow line: EMA-26
Signal line: EMA-9
Problem of classic concept
Classic MACD indicator usually gives not bad "BUY" signals, especially if using them not for operational trading but for "investment" strategy. But "SELL" signalls usually generated too late. Simply because the market tends to fall much faster than it rises.
Possible solution (the main feature of our version of MACD)
To make indicator react faster on SELL condition, while still keeping it reliable for BUY signals, we decided to use two signal lines . Faster than default signal line (with window=6) for BUY signals and much faster than default (with window=2) for SELL signals.
This approach allowed us to receive sell signals earlier and exit deals on more favorable prices. Trade off of this change - is the number of SELL signals - there were more of them. However, this does not matter, since we receive the very first sell signal with a "very fast signal line" much earlier than with classic indicator settings.
Parameters we use in our improved MACD indicator:
Fast line: EMA-12
Slow line: EMA-24
Faster signal line: EMA-6
Much faster signal line: EMA-2
Removing noise (false triggerings)
Other drawback of classic MACD - it generates a lot of "weak" (false) signals. This signals are generated when macd crosses signal line much close to zero-line. And usually there are a lot of such intersections.
To remove this kind of noise, we added a trigger threshold, which by default is equal to 2.5% of the average asset price over a long period of time. Due to the link to the average price, this threshold automatically takes a specific value for each trading pair. Threshold 2.5% works perfect for all trading pairs for 1D timeframe. For other timeframes user can (and maybe will want) change it.
Boost weak BUY signals in a prolonged bear market
Signals on bearish stage are usually very weak, because there is no volatility, and no price impulse. And such signals will be filtered out as "noise" - see above. But this time is perfect time to buy! Therefore, we further boost the buy signals in a prolonged bear market so that they can pass through the filter and appear on the chart. Bearish period is the best time to invest!
Developed by Take and Trade. Enjoy using it!
KDJ / Connectable [Azullian]Enhance your analysis with our KDJ. Oscillate through buying and selling signals seamlessly, identifying potential reversals with accuracy.
This connectable KDJ indicator is part of an indicator system designed to help test, visualize and build strategy configurations without coding. Like all connectable indicators , it interacts through the TradingView input source, which serves as a signal connector to link indicators to each other. All connectable indicators send signal weight to the next node in the system until it reaches either a connectable signal monitor, signal filter and/or strategy.
█ UNIFORM SETTINGS AND A WAY OF WORK
Although connectable indicators may have specific weight scoring conditions, they all aim to follow a standardized general approach to weight scoring settings, as outlined below.
■ Connectable indicators - Settings
• 🗲 Energy: Energy applies an ATR multiplier to the plotted shapes on the chart. A higher value plots shapes farther away from the candle, enhancing visibility.
• ☼ Brightness: Brightness determines the opacity of the shape plotted on the chart, aiding visibility. Indicator weight also influences opacity.
• → Input: Use the input setting to specify a data source for the indicator. Here you can connect the indicator to other indicators.
• ⌥ Flow: Determine where you want to receive signals from:
○ Both: Weights from this indicator and the connected indicator will apply
○ Indicator only: Only weights from this indicator will apply
○ Input only: Only weights from the connected indicator will apply
• ⥅ Weight multiplier: Multiply all weights in the entire indicator by a given factor, useful for quickly testing different indicators in a granular setup.
• ⥇ Threshold: Set a threshold to indicate the minimum amount of weight it should receive to pass it through to the next indicator.
• ⥱ Limiter: Set a hard limit to the maximum amount of weight that can be fed through the indicator.
■ Connectable indicators - Weight scoring settings
▢ Weight scoring conditions
• SM – Signal mode: Enable specific conditions for weight scoring
○ All: All signals will be scored.
○ Entries only: Only entries will score.
○ Exits only: Only exits will score.
○ Entries & exits: Both entries and exits will score.
○ Zone: Continuous scoring for each candle within the zone.
• SP – Signal period: Defines a range of candles within which a signal can score.
• SC - Signal count: Specifies the number of bars to retrospectively examine and score.
○ Single: Score for a single occurrence
○ All occurrences: Score for all occurrences
○ Single + Threshold: Score for single occurrences within the signal period (SP)
○ Every + Threshold: Score for all occurrences within the signal period (SP)
▢ Weight scoring direction
• ES: Enter Short weight
• XL: Exit long weight
• EL: Enter Long weight
• XS: Exit Short weight
▢ Weight scoring values
• Weights can hold either positive or negative scores. Positive weights enhance a particular trading direction, while negative weights diminish it.
█ KDJ - INDICATOR SETTINGS
■ Main settings
• Enable/Disable Indicator: Toggle the entire indicator on or off.
• S - Source: Choose an alternative data source for the KDJ calculation.
• T - Timeframe: Select an alternative timeframe for the KDJ calculation.
• P - Period: Define the number of bars or periods used in the KDJ calculation.
• SL - Signal line: Adjust the smoothing factor for the KDJ's J line. This not only offers clearer buy/sell cues by reducing market noise but also determines the precise points for potential crossovers and crossunders.
■ Scoring functionality
• The KDJ scores long entries when the J line crosses over the signal (SL) line.
• The KDJ scores long exits when the J line crosses under the signal (SL) line after a prior crossover.
• The KDJ scores long zones the entire time the J line is above the signal (SL) line.
• The KDJ scores short entries when the J line crosses under the signal (SL) line.
• The KDJ scores short exits when the J line crosses over the signal (SL) line after a prior crossunder.
• The KDJ scores short zones the entire time the J line is below the signal (SL) line.
█ PLOTTING
• Standard: Symbols (EL, XS, ES, XL) appear relative to candles based on set conditions. Their opacity and position vary with weight.
• Conditional Settings: A larger icon appears if global conditions are met. For instance, with a Threshold(⥇) of 12, Signal Period (SP) of 3, and Scoring Condition (SC) set to "EVERY", an KDJ signaling over two times in 3 candles (scoring 6 each) triggers a larger icon.
█ USAGE OF CONNECTABLE INDICATORS
■ Connectable chaining mechanism
Connectable indicators can be connected directly to the signal monitor, signal filter or strategy , or they can be daisy chained to each other while the last indicator in the chain connects to the signal monitor, signal filter or strategy. When using a signal filter you can chain the filter to the strategy input to make your chain complete.
• Direct chaining: Connect an indicator directly to the signal monitor, signal filter or strategy through the provided inputs (→).
• Daisy chaining: Connect indicators using the indicator input (→). The first in a daisy chain should have a flow (⌥) set to 'Indicator only'. Subsequent indicators use 'Both' to pass the previous weight. The final indicator connects to the signal monitor, signal filter, or strategy.
■ Set up this indicator with a signal filter and strategy
The indicator provides visual cues based on signal conditions. However, its weight system is best utilized when paired with a connectable signal filter, signal monitor, or strategy .
Let's connect the KDJ to a connectable signal filter and a strategy :
1. Load all relevant indicators
• Load KDJ / Connectable
• Load Signal filter / Connectable
• Load Strategy / Connectable
2. Signal Filter: Connect the KDJ to the Signal Filter
• Open the signal filter settings
• Choose one of the three input dropdowns (1→, 2→, 3→) and choose : KDJ / Connectable: Signal Connector
• Toggle the enable box before the connected input to enable the incoming signal
3. Signal Filter: Update the filter signals settings if needed
• The default settings of the filter enable EL (Enter Long), XL (Exit Long), ES (Enter Short) and XS (Exit Short).
4. Signal Filter: Update the weight threshold settings if needed
• All connectable indicators load by default with a score of 6 for each direction (EL, XL, ES, XS)
• By default, weight threshold (TH) is set at 5. This allows each occurrence to score, as the default score in each connectable indicator is 1 point above the threshold. Adjust to your liking.
5. Strategy: Connect the strategy to the signal filter in the strategy settings
• Select a strategy input → and select the Signal filter: Signal connector
6. Strategy: Enable filter compatible directions
• Set the signal mode of the strategy to a compatible direction with the signal filter.
Now that everything is connected, you'll notice green spikes in the signal filter representing long signals, and red spikes indicating short signals. Trades will also appear on the chart, complemented by a performance overview. Your journey is just beginning: delve into different scoring mechanisms, merge diverse connectable indicators, and craft unique chains. Instantly test your results and discover the potential of your configurations. Dive deep and enjoy the process!
█ BENEFITS
• Adaptable Modular Design: Arrange indicators in diverse structures via direct or daisy chaining, allowing tailored configurations to align with your analysis approach.
• Streamlined Backtesting: Simplify the iterative process of testing and adjusting combinations, facilitating a smoother exploration of potential setups.
• Intuitive Interface: Navigate TradingView with added ease. Integrate desired indicators, adjust settings, and establish alerts without delving into complex code.
• Signal Weight Precision: Leverage granular weight allocation among signals, offering a deeper layer of customization in strategy formulation.
• Advanced Signal Filtering: Define entry and exit conditions with more clarity, granting an added layer of strategy precision.
• Clear Visual Feedback: Distinct visual signals and cues enhance the readability of charts, promoting informed decision-making.
• Standardized Defaults: Indicators are equipped with universally recognized preset settings, ensuring consistency in initial setups across different types like momentum or volatility.
• Reliability: Our indicators are meticulously developed to prevent repainting. We strictly adhere to TradingView's coding conventions, ensuring our code is both performant and clean.
█ COMPATIBLE INDICATORS
Each indicator that incorporates our open-source 'azLibConnector' library and adheres to our conventions can be effortlessly integrated and used as detailed above.
For clarity and recognition within the TradingView platform, we append the suffix ' / Connectable' to every compatible indicator.
█ COMMON MISTAKES, CLARIFICATIONS AND TIPS
• Removing an indicator from a chain: Deleting a linked indicator and confirming the "remove study tree" alert will also remove all underlying indicators in the object tree. Before removing one, disconnect the adjacent indicators and move it to the object stack's bottom.
• Point systems: The azLibConnector provides 500 points for each direction (EL: Enter long, XL: Exit long, ES: Enter short, XS: Exit short) Remember this cap when devising a point structure.
• Flow misconfiguration: In daisy chains the first indicator should always have a flow (⌥) setting of 'indicator only' while other indicator should have a flow (⌥) setting of 'both'.
• Hide attributes: As connectable indicators send through quite some information you'll notice all the arguments are taking up some screenwidth and cause some visual clutter. You can disable arguments in Chart Settings / Status line.
• Layout and abbreviations: To maintain a consistent structure, we use abbreviations for each input. While this may initially seem complex, you'll quickly become familiar with them. Each abbreviation is also explained in the inline tooltips.
• Inputs: Connecting a connectable indicator directly to the strategy delivers the raw signal without a weight threshold, meaning every signal will trigger a trade.
█ A NOTE OF GRATITUDE
Through years of exploring TradingView and Pine Script, we've drawn immense inspiration from the community's knowledge and innovation. Thank you for being a constant source of motivation and insight.
█ RISK DISCLAIMER
Azullian's content, tools, scripts, articles, and educational offerings are presented purely for educational and informational uses. Please be aware that past performance should not be considered a predictor of future results.
Asset capital flows - multi-timeframeIndicator for use on the any timeframe to show net capital flows into an asset of your choosing, to allow the user to track potential buy and selling pressure.
Net volume is derived from lower timeframe data (5 minute chart by default for daily timeframe) and multiplied by the average price for the same LTF period (defined by the mean of the high, low + close values). This gives the net capital inflow or outflow for the asset per bar. The cumulative sum of all previous bars is also calculated each period/day and available to be plotted as a line chart.
This might be preferred to other similar indicators as it uses low time frame bars to calculate the up/down volumes and price, thus accuracy is improved.
It should be borne in mind that the values of capital flows displayed are specific to the asset and the volume/price feed origin (ie the listed exchange used), and thus correlated with the total underlying flows, but there are other external factors influencing the volume/price data feed beyond the buy/sell volume of the specified exchange (such as spot and futures trading on other locations/exchanges)
LV Stock Valuation by Benjamin Graham's FormulaBenjamin Graham's stock valuation formula for growth companies is based on the principle that a stock is a part of a business, and that by analyzing the fundamentals of any company in the stock market, you should be able to derive its intrinsic value independent from its current stock price. Graham suggests that over the long-term, the stock price of a company and its intrinsic/fair value will converge towards each other until the stock price reflects the true value of the company. Finally, Graham recommends that after estimating the intrinsic value of a stock, investors should always purchase the stock with a "margin of safety," to protect oneself from assumptions and potential errors made in the valuation process.
Graham's stock valuation formula to calculate intrinsic value was originally shown in the 1962 edition of Security Analysis as follows:
V = EPS * (8.5 + 2g)
where:
V = intrinsic value per share (over the next 7-10 years)
EPS = earnings per share (over the trailing twelve months (TTM))
8.5 = price-to-earnings (P/E) base for a no-growth company
g = reasonably expected annual growth rate (over the next 7-10 years)
In 1974, Graham revised this formula, as published in The Intelligent Investor, to include a discount rate (aka required rate of return). This was after he concluded that the greatest contributing to stock values and prices over the past decade had been due to interest rates.
Graham's current stock valuation formula is shown below:
V = (EPS * (8.5 + 2g) * Z) / Y
where:
V = intrinsic value per share (over the next 7-10 years)
EPS = diluted earnings per share (over the trailing twelve months (TTM))
8.5 = price-to-earnings (P/E) base for a no-growth company (you can change it manually)
g = reasonably expected annual growth rate (calculated by 5-Yr EPS CAGR%) (you can change year period)
Z = average yield of XXX Bonds (4.4 is default on Graham's formula)
Y = current yield of XXX Bonds
Current bond yield values (Z and Y) are selected as an example from Turkey. You need to change it according to the country of stocks.
Buy price (BP) = Intrinsic value per share * (1 - Margin of safety %)
Margin of safety = selected 20% (you need to change it to 0, if you don’t want to use margin of safety and to see intrinsic value)
Buy price > Current market price: Consider buying the stock, as the current market price appears to be undervalued.
Buy price < Current market price: Consider selling or not buying the stock, as the current market price appears to be overvalued.
Keep in mind that this buy/sell recommendation is purely based on Graham's stock valuation formula and the current market price, and ignores all other fundamental, news, and market factors investors should examine as well before making an investment decision.
Buy price is calculated for 5 different P/E values in the script.
1. with fixed P/E
2. with current P/E
3. with forward P/E
4. with sector P/E (optional)
5. with index P/E (optional)
You can also do calculations by using different growth rate by selecting that option.
Different type of moving averages is also included in the script as an option.
QQE MOD + SSL Hybrid + Waddah Attar Explosion IndicatorINDICATOR PURPOSE
This indicator is designed to complement my original QQE MOD + SSL Hybrid + Waddah Attar Explosion strategy.
Multiple users have requested that I convert the strategy to an indicator because alertconditions do not work on strategies and people want to specific set alerts for BUY, SELL, CLOSE BUY and CLOSE SELL. This can only be achieved using alertcondition().
This indicator functions in the exact same way as the strategy, but it doesn't have any backtesting functionality. I recomment that you use the original QQE MOD + SSL Hybrid + Waddah Attar Explosion strategy for parameter tuning and backtesting, then if you need more control on alerts you can use this indicator for that purpose.
Only other difference is that I have added grey exit labels on the chart since it's not obvious where the exits would happen like it was in the strategy version.
CREDITS
QQE MOD byMihkel00
SSL Hybrid by Mihkel00
Waddah Attar Explosion by shayankm
Saty Volume StackBreaks volume into buy and sell volume and stacks them based on which side has higher volume.
Dynamic Buy / Sell Stack
Unlike other buy/sell volume indicators, which statically display this information (typically green over red), this indicator dynamically stacks the higher volume side on top. For example, green over red indicates more buy-side volume, red over green indicators more sell-side volume.
Current Candle Volume Buy/Sell %
A label shows the % buy vs sell volume for the current candle in real-time. This label is also dynamic with the left position being higher volume.
How the Buy/Sell Volume is Calculated
Buy/Sell % is calculated based on price.
Buy % is calculated using the distance between the low of the candle to the closing value of the candle and dividing that by the total range of the candle high to low.
Sell % is calculated using the distance between the high of the candle to the closing value of the candle and dividing that by the total range of the candle high to low.
Please note this is a proxy metric and while it is incredibly useful, it is not going to match up exactly with actual buy/sell volume that can be found on tape.
