Stochastics Confluences 4 in 1Description of the Pine Script:
This script plots the Full Stochastic indicator for four different time periods, and highlights conditions where potential buy or sell signals can be identified. The Stochastic indicator measures the position of the current closing price relative to the range of high and low prices over a defined period, helping traders identify overbought and oversold conditions.
Key Features:
Stochastic Calculation for 4 Different Periods:
The script calculates the Stochastic for four separate lookback periods: 9, 14, 40, and 60 bars.
Each Stochastic value is smoothed by a Simple Moving Average (SMA) to reduce noise and provide a clearer signal.
Visual Representation:
It plots each Stochastic value on the chart using different colors, allowing the user to see how the different periods of the indicator behave relative to each other.
Horizontal lines are drawn at 80 (Upper Bound) and 20 (Lower Bound), commonly used to identify overbought and oversold regions.
Highlighting Buy and Sell Conditions:
Green Highlight (Potential Buy Signal):
When all four Stochastic values (for the four different periods) are below 20, this suggests that the asset is in an oversold condition across multiple timeframes. The green background highlight appears when the Stochastic lines converge below 20, indicating a potential buy signal, as the price may be preparing to move upward from an oversold state.
Red Highlight (Potential Sell Signal):
When all four Stochastic values are above 80, the asset is in an overbought condition across multiple timeframes. The red background highlight appears when the Stochastic lines converge above 80, indicating a potential sell signal, as the price may soon reverse downward from an overbought state.
How to Interpret the Signals:
Buy Signals (Green Highlight):
When the chart is highlighted in green, it means the Stochastic indicators for all four periods are below 20, signaling that the asset is oversold and may be nearing a potential upward reversal. This condition suggests a possible buying opportunity, especially when other indicators confirm the potential for an upward trend.
Sell Signals (Red Highlight):
When the chart is highlighted in red, it indicates that the Stochastic indicators for all four periods are above 80, meaning the asset is overbought. This condition signals a possible downward reversal, suggesting a potential selling opportunity if the price begins to show signs of weakness.
By using this script, traders can visually identify periods of strong confluence across different timeframes when the Stochastic indicators are in extreme oversold or overbought conditions, which are traditionally seen as strong buy or sell signals.
This approach helps filter out weaker signals and focuses on moments when all timeframes align, increasing the probability of a successful trade.
指标和策略
Adjusted CoT IndexAdjusted COT Index
Improves upon: "COT Index Commercials vs large and small Speculators" by SystematicFutures
How: CoT Indexes are adjusted by Open Interest to normalise data over time, and threshold background colours are in-line with Larry Williams recommendations from his book.
Note: This indicator is **only** accurate on the Daily time-frame due to the mid-week release date for CoT data.
This script calculates and plots the Adjusted Commitment of Traders (COT) Index for Commercial, Large Speculator, and Retail (Small Speculator) categories.
The CoT Index is adjusted by Open Interest to normalise data through time, following the methodology of Larry Williams, providing insights into how these groups are positioned in the market with an arguably more historically accurate context.
COT Categories
-------------------
- Commercials (Producers/Hedgers): Large entities hedging against price changes in the underlying asset.
- Large Speculators (Non-commercials): Professional traders and funds speculating on price movements.
- Retail Traders (Nonreportable/Small Speculators): Small individual traders, typically less informed.
Features
----------
- Open Interest Adjustment
- The net positions for each category are normalized by Open Interest to account
for varying contract sizes.
- Customisable Look-back Period
- You can adjust the number of weeks for the index calculation to control the
historical range used for comparison.
- Thresholds for Extremes
- Upper and lower thresholds (configurable) are provided to mark overbought and
oversold conditions.
- Defaults
- Overbought: <=20
- Oversold: >= 80
- Hide Current Week Option
- Optionally hide the current week's data until market close for more accurate comparison.
- Visual Aids
- Plot the Commercials, Large Speculators, and Retail indexes, and optionally highlight extreme positioning.
Inputs
--------
- weeks
- Number of weeks for historical range comparison.
- upperExtreme and lowerExtreme
- Thresholds to identify overbought/oversold conditions (default 80/20).
- hideCurrentWeek
- Option to hide current week's data until market close.
- markExtremes
- Highlight extremes where any index crosses the upper or lower thresholds.
- Options to display or hide indexes for Commercials, Large Speculators, and Small Speculators.
Outputs
----------
- The script plots the COT Index for each of the three categories and highlights periods of extreme positioning with customisable thresholds.
Usage
-------
- This tool is useful for traders who want to track the positioning of different market participants over time.
- By identifying the extreme positions of Commercials, Large Speculators, and Retail traders, it can give insights into market sentiment and potential reversals.
- Reversals of trend can be confirmed with RSI Divergence (daily), for example
- Continuation can be confirmed with RSI overbought/oversold conditions (daily), and/or hidden RSI Hidden Divergence, for example
Vektorkerzen HighlightThe indicator highlights candles when:
The volume is at least twice the 20-period moving average.
The range (difference between high and low prices) is at least twice the 20-period average range.
*2.2 Aggregated (Raw Z-scores with MA)***To be used with other 2.2 indicator***
Key Indicators Used:
Oscillating Indicators: RSI, TSI, Stochastic, MACD, CCI, Vortex Indicator, Williams %R.
Perpetual Trend Indicators: EMA, ADX, Parabolic SAR, Supertrend, Donchian Channel, Ichimoku Cloud, RVGI.
How to Use the Indicator:
Raw Z-Score (Blue Line): This represents the real-time aggregated Z-score of all the indicators. It shows how far the current market conditions are from their average, helping you identify trends.
Moving Average of Z-Score (Orange Line): A smoothed version of the Z-score that helps confirm trends and eliminate noise.
Shaded Area: The area between the Z-score and its moving average is shaded green if the Z-score is above the moving average (bullish), and red if below the moving average (bearish).
Zero Line (Gray Line): Serves as a reference point. A Z-score crossing above zero could signal a bullish market, while crossing below zero could indicate bearish conditions.
This indicator helps in identifying market extremes and trend reversals by combining various technical indicators into a single aggregate score, ideal for spotting overbought or oversold conditions and possible trend shifts
*2.2 Aggregate Signal Indicator (trial)How to Use the Indicator:
Trend Detection:
The aggregate trend score will plot above 0 for bullish conditions and below 0 for bearish conditions.
When the trend score is green, it indicates a positive (bullish) trend, while red indicates a negative (bearish) trend.
Visual Representation:
The blue line represents the aggregate trend score, while the grey line at 0 shows the neutral point.
The area between the trend score and the 0-line is filled with green (bullish) or red (bearish) based on the score's direction.
Confirming Trends:
Look for consistency in the trend score remaining above or below 0 to confirm a lasting trend.
Use this indicator alongside other trading strategies to filter out false signals and gain confirmation of market direction.
Customizable Inputs:
The indicator allows you to customize the settings for each individual indicator (e.g., lengths for EMA, ADX, RSI, MACD, etc.) to fine-tune the system to your preference or specific market conditions.
Farley's Accumulation-Distribution Accelerator (ADA)Farley's ADA (From The Master Swing Trader)
What it is :
ADA is designed to track volume oscillations in the market and reduce the impact of shock events.
It observes the supply-demand dynamics within the market, which can trigger natural levels of price reversals.
How It Works
Volume and Price Relationship: ADA measures the lag between price and volume movements. It highlights when volume leads or lags behind price changes, helping traders identify potential reversals or trends.
Signal Generation: ADA can generate faster and cleaner signals compared to traditional indicators like On-Balance Volume (OBV).
Usage
Support and Resistance: ADA formations can help identify support and resistance levels and trendlines.
detect natural levels where price reversals might occur.
Trend Identification: Look for significant divergences between ADA and price action to identify potential trend reversals.
Volume Analysis: Use ADA to anticipate pauses in price movements when volume leads, and expect dynamic trends when ADA significantly moves ahead of price action.
Time Based 3 Candle Model CRT FrameworkThe 3 Candle Model Overview:
The 3 Candle Model serves as a sophisticated framework for traders to navigate the complexities of financial markets, particularly within futures and forex trading. This guide not only elaborates on the model's key features but also emphasizes its originality and practical usefulness in the TradingView community. The core principle of the 3 Candle Model revolves around understanding how candle patterns can represent significant price ranges, offering valuable insights into potential market movements. By integrating the model with other critical trading concepts such as the Power of Three (PO3), Open-High-Low-Close (OHLC), and Turtle Soup setups, traders can enhance their ability to identify high-probability trades and achieve better trading outcomes.
Indicator includes:
3 Customizable Timeframe choices to fractally frame 3 candle models for precision
Live Timers for each timeframe to always be aware of the models timing
Parent Candle tracking on every preffered timeframe until new models parent candle is printed
Key Features of the 3 Candle Model
The 3 Candle Model primarily utilizes a three-candle structure, where the first candle establishes a price range, the second candle may act as a confirmation (often termed a "turtle soup"), and the third candle provides the breakout or continuation. This structure is pivotal in determining entry and exit points for trades, ensuring that each trading decision is backed by solid price action analysis.
OHLC Principle:
The Open-High-Low-Close (OHLC) concept is integral to the 3 Candle Model, allowing traders to analyze price action more effectively. Understanding the relationship between these four price points helps traders gauge market sentiment and potential reversals. By incorporating OHLC into the model, traders can develop a deeper understanding of market structure and its implications for future price movements.
Delivery States:
The 3 Candle Model emphasizes the importance of delivery states, which refer to the market's phase during specific time frames. Recognizing these states aids traders in determining the appropriate conditions for entering trades, particularly when combined with the power of three and candle range patterns. This understanding is crucial for positioning trades in alignment with market momentum.
High Probability Setups:
By aligning the 3 Candle Model with inside bar setups, traders can optimize their strategies for high-probability outcomes. This approach capitalizes on the inherent fractal nature of price movements, where previous patterns repeat at different scales. The combination of the model and inside bar setups enhances the trader's toolkit, allowing for more strategic trade placements.
Turtle Soup Formation:
The 3 Candle Model intricately connects with the Turtle Soup concept, which focuses on false breakouts. Identifying these formations at critical levels enhances the trader's ability to anticipate reversals or continuation patterns. The timing of these setups, particularly during specified times like 3:00 AM, 6:00 AM, 9:00 AM, and 1:00 PM, is crucial for maximizing trade success.
Using the 3 Candle Model in Trading
Integration with PO3:
The Power of Three (PO3) is a fundamental aspect of the 3 Candle Model that emphasizes the significance of three distinct stages of price delivery. Traders can leverage this principle by observing the initial range, confirming patterns, and executing trades during the third phase, leading to higher risk-to-reward ratios. This three-stage approach enhances a trader's ability to make informed decisions based on market behavior.
Targeting Midpoints:
Successful application of the 3 Candle Model involves targeting the midpoints of identified ranges. This practice not only provides strategic entry points but also enhances the probability of reaching desired profit levels. By targeting these midpoints, traders can refine their exit strategies and manage risk more effectively.
Aligning with Market Timing:
Timing is everything in trading. By synchronizing the 3 Candle Model setups with the aforementioned key timeframes, traders can better position themselves to exploit market dynamics. This alignment also facilitates the identification of high-quality trades that exhibit strong potential for profitability.
Prioritizing A+ Setups:
By focusing on the 3 Candle Model and its associated concepts, traders can prioritize A+ setups that exhibit a strong alignment of factors. This methodical approach enhances the quality of trades taken, leading to improved overall performance. By cultivating a strategy centered on high-probability setups, traders can maximize their return on investment.
Ensuring Originality and Usefulness
To meet the TradingView community guidelines, it is essential that this script is both original and useful. The 3 Candle Model, in its essence, is designed to provide traders with a unique perspective on market movements, free from generic or rehashed strategies. This tool integrates unique interpretations of the three-candle model and the associated strategies that are distinctly articulated and innovative.
Practical Applications: there are many practical applications of the 3 Candle Model in various trading contexts. This model in conjunction with other strategies to cultivate high-probability trade setups that can enhance performance across diverse market conditions.
Educational Value: This script is crafted with educational value in mind, providing insights that extend beyond mere trading signals. It encourages users to develop a deeper understanding of market mechanics and the interplay between price action, time, and trader psychology.
Conclusion
The 3 Candle Model provides a comprehensive framework for traders to enhance their trading strategies in the futures and forex markets. By understanding and applying the principles of this model alongside the Power of Three, OHLC concepts, and Turtle Soup formations, traders can significantly improve their ability to identify high-probability trades. The emphasis on timing, delivery states, and alignment of ranges ensures that traders are well-equipped to navigate the complexities of market movements, ultimately leading to more consistent and rewarding trading outcomes.
As trading involves risk, it is essential for traders to utilize these principles judiciously and maintain a disciplined approach to their trading strategies. By adhering to the TradingView community guidelines and emphasizing originality, usefulness, and detailed descriptions, this 3 Candle Model script stands as a valuable resource for traders seeking to refine their skills and achieve greater success in the financial markets.
Through this detailed exploration of the 3 Candle Model, traders will not only learn to recognize and exploit key patterns in price action but also appreciate the interconnectedness of various trading strategies that can significantly enhance their performance and profitability.
Sell Signals EMA+SMAIndicator Overview:
This indicator identifies sell signals based on candlestick patterns, volume conditions, and moving average confirmations. It also plots support and resistance levels based on pivot highs and pivot lows. You can configure different settings like pivot lengths, moving average periods, and candlestick pattern conditions for the sell signals.
Configurable Settings:
Pivot High Length: Defines the number of bars used to calculate the resistance levels (pivot highs).
Pivot Low Length: Defines the number of bars used to calculate the support levels (pivot lows).
Volume SMA Length: The period of the simple moving average (SMA) for volume. Used to filter signals based on high volume.
Close SMA Length: The period of the simple moving average (SMA) for the close price. Used for confirmation of sell signals.
Pin Bar High Ratio: The ratio for defining the size of the upper wick in a bearish pin bar.
Pin Bar Low Ratio: The ratio for defining the size of the lower wick in a bearish pin bar.
How It Works:
Support and Resistance:
The indicator plots red lines for resistance (pivot highs) and green lines for support (pivot lows).
These levels are updated as new pivot points are detected based on the configured pivot lengths.
Sell Signal Conditions:
Candlestick Patterns: The indicator checks for two bearish patterns:
Bearish Pin Bar: A candle with a large upper wick and small lower wick where the close is below the open.
Bearish Engulfing: A candle where the current close is lower than the previous low, and the current open is higher than the previous high.
Volume Condition: The volume must be above the configured simple moving average (SMA) of the volume.
Confirmation: A sell signal is confirmed only when the price crosses below the configured SMA for the close price.
Sell Signals:
If all the conditions (candlestick pattern, volume, and confirmation) are met, the indicator will plot a red "Sell" label above the candle.
Additionally, a blue triangle will appear above the candle to indicate that the sell signal has been confirmed.
How to Use:
Adjust the Settings:
Open the settings of the indicator and adjust the parameters like pivot lengths, moving average periods, and candlestick pattern ratios based on your preferences.
Identify Key Levels:
Watch the red resistance and green support lines to identify key levels where price may reverse.
Look for Sell Signals:
When a red "Sell" label appears, it indicates a possible sell opportunity.
Ensure that a blue triangle (confirmation) also appears to validate the sell signal.
Manage Risk:
Use the support and resistance levels along with the sell signals to define your entry, stop-loss, and take-profit levels.
This indicator helps you identify potential bearish reversal points with configurable settings for added flexibility.
Cosine-Weighted MA ATR [InvestorUnknown]The Cosine-Weighted Moving Average (CWMA) ATR (Average True Range) indicator is designed to enhance the analysis of price movements in financial markets. By incorporating a cosine-based weighting mechanism , this indicator provides a unique approach to smoothing price data and measuring volatility, making it a valuable tool for traders and investors.
Cosine-Weighted Moving Average (CWMA)
The CWMA is calculated using weights derived from the cosine function, which emphasizes different data points in a distinctive manner. Unlike traditional moving averages that assign equal weight to all data points, the cosine weighting allocates more significance to values at the edges of the data window. This can help capture significant price movements while mitigating the impact of outlier values.
The weights are shifted to ensure they remain non-negative, which helps in maintaining a stable calculation throughout the data series. The normalization of these weights ensures they sum to one, providing a proportional contribution to the average.
// Function to calculate the Cosine-Weighted Moving Average with shifted weights
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * close
cwma
Cosine-Weighted ATR Calculation
The ATR is an essential measure of volatility, reflecting the average range of price movement over a specified period. The Cosine-Weighted ATR uses a similar weighting scheme to that of the CWMA, allowing for a more nuanced understanding of volatility. By emphasizing more recent price movements while retaining sensitivity to broader trends, this ATR variant offers traders enhanced insight into potential price fluctuations.
// Function to calculate the Cosine-Weighted ATR with shifted weights
f_Cosine_Weighted_ATR(simple int length) =>
var float cosine_weights_atr = array.new_float(0)
array.clear(cosine_weights_atr)
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(cosine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(cosine_weights_atr, i) / sum_weights_atr
array.set(cosine_weights_atr, i, norm_weight_atr)
// Calculate Cosine-Weighted ATR using true ranges
cwatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
cwatr := cwatr + array.get(cosine_weights_atr, i) * tr
cwatr
Signal Generation
The indicator generates long and short signals based on the relationship between the price (user input) and the calculated upper and lower bands, derived from the CWMA and the Cosine-Weighted ATR. Crossover conditions are used to identify potential entry points, providing a systematic approach to trading decisions.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(cwma_src)
float cwma = f_Cosine_Weighted_MA(src, ma_length)
// Use normal ATR or Cosine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Cosine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
float src_l = b.calc_src(src_long)
float src_s = b.calc_src(src_short)
// Signal logic for crossovers and crossunders
var int signal = 0
if ta.crossover(src_l, cwma_up)
signal := 1
if ta.crossunder(src_s, cwma_dn)
signal := -1
//}
Backtest Mode and Equity Calculation
To evaluate its effectiveness, the indicator includes a backtest mode, allowing users to test its performance on historical data:
Backtest Equity: A detailed equity curve is calculated based on the generated signals over a user-defined period (startDate to endDate).
Buy and Hold Comparison: Alongside the strategy’s equity, a Buy-and-Hold equity curve is plotted for performance comparison.
Visualization and Alerts
The indicator features customizable plots, allowing users to visualize the CWMA, ATR bands, and signals effectively. The colors change dynamically based on market conditions, with clear distinctions between long and short signals.
Alerts can be configured to notify users of crossover events, providing timely information for potential trading opportunities.
Cumulative Buying and Selling Volume with 3 Lookback PeriodsScript Overview:
This script is designed to help traders identify market momentum by analyzing buying and selling volume. It calculates the cumulative buying and selling pressure over three different lookback periods, providing insights into whether the bulls or bears are dominating at any given time. The script does this by computing the cumulative buying and selling volume for each period and comparing them through exponential moving averages (EMA) to smooth out short-term fluctuations.
Purpose and Use:
The primary goal of this script is to highlight shifts in market sentiment based on volume dynamics. Volume is a critical component in market analysis, often signaling the strength behind price movements. By focusing on cumulative buying and selling pressure, the script gives traders an idea of whether the market is trending towards more buying or selling during specific periods. Traders can use this tool to:
Identify potential entry points when buying pressure is strong.
Recognize potential selling opportunities when selling pressure is increasing.
Detect periods of indecision when neither buying nor selling dominates.
Key Concepts:
1. Buying Volume (BV):
The buying volume is calculated based on the price range of each candle. It represents the volume allocated to the bullish side of the market:
When the close is near the high, the buying volume is higher.
Formula: BV = volume * (close - low) / (high - low).
2. Selling Volume (SV):
Similarly, selling volume is derived based on the position of the close relative to the low:
When the close is near the low, selling volume is higher.
Formula: SV = volume * (high - close) / (high - low)
3. Lookback Periods:
The script allows users to define three different lookback periods (5, 10, and 20 by default). These periods smooth out the cumulative buying and selling volumes using EMA calculations:
Shorter periods capture more immediate changes in volume dynamics.
Longer periods provide a broader perspective on market trends.
4. Cumulative Volume Calculation:
For each lookback period, cumulative buying and selling volumes are tracked separately and then smoothed with EMA:
emaBuyVol and emaSellVol are the smoothed values for buying and selling volumes over the lookback periods.
5. Market Pressure Comparison:
Buying Pressure: If the EMA of buying volume is greater than the EMA of selling volume for a particular lookback period, the script considers that buying pressure dominates for that period.
Selling Pressure: Conversely, if selling volume dominates over buying volume for a period, the script registers selling pressure.
6. Overall Market Pressure:
The script aggregates the buying and selling pressures from the three lookback periods to determine the overall market sentiment:
If the majority of periods show buying pressure, the market is bullish.
If the majority show selling pressure, the market is bearish.
If neither side dominates, it suggests a neutral or indecisive market.
Visual Cues:
The script provides visual feedback to help traders quickly interpret the market pressure:
Background Color:
Green (#2bff00) when buying pressure dominates.
Red (#ff0000) when selling pressure dominates.
Gray (#404040) when there is no clear dominance.
Bar Color: The script also colors the price bars based on the dominant market pressure:
Green for buying pressure.
Red for selling pressure.
Gray for neutral or balanced market pressure.
Reset Mechanism:
At the start of each new candle, the cumulative volumes for all three periods are reset to zero. This ensures that the cumulative volumes are only measured for the current candle, preventing carryover from previous periods that could distort the analysis.
How Traders Can Use This Script:
Trend Confirmation: Traders can use the script as a trend confirmation tool. When the background turns green (buying dominance), it suggests bullish momentum. When red, bearish momentum is likely. This information can be used to confirm existing positions or signal new trades in the direction of the market pressure.
Reversal Detection: A sudden shift in the background color (from green to red or vice versa) can indicate a potential reversal. This can be particularly useful when combined with other technical indicators such as price action or support/resistance levels.
Multiple Timeframes: Since the script supports three different lookback periods, it provides a comprehensive view of market pressure across short-term, medium-term, and long-term perspectives. Traders can tailor the lookback periods based on their preferred timeframe to match their trading style, whether it’s intraday trading or longer-term swing trading.
Risk Management: The script's clear visual cues help traders manage risk by highlighting when selling pressure increases, allowing them to consider reducing long positions or tightening stop-losses.
Sine-Weighted MA ATR [InvestorUnknown]The Sine-Weighted MA ATR is a technical analysis tool designed to emphasize recent price data using sine-weighted calculations , making it particularly well-suited for analyzing cyclical markets with repetitive patterns . The indicator combines the Sine-Weighted Moving Average (SWMA) and a Sine-Weighted Average True Range (SWATR) to enhance price trend detection and volatility analysis.
Sine-Weighted Moving Average (SWMA):
Unlike traditional moving averages that apply uniform or exponentially decaying weights, the SWMA applies Sine weights to the price data.
Emphasis on central data points: The Sine function assigns more weight to the middle of the lookback period, giving less importance to the beginning and end points. This helps capture the main trend more effectively while reducing noise from recent volatility or older data.
// Function to calculate the Sine-Weighted Moving Average
f_Sine_Weighted_MA(series float src, simple int length) =>
var float sine_weights = array.new_float(0)
array.clear(sine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights, weight)
// Normalize the weights
sum_weights = array.sum(sine_weights)
for i = 0 to length - 1
norm_weight = array.get(sine_weights, i) / sum_weights
array.set(sine_weights, i, norm_weight)
// Calculate Sine-Weighted Moving Average
swma = 0.0
if bar_index >= length
for i = 0 to length - 1
swma := swma + array.get(sine_weights, i) * close
swma
Sine-Weighted ATR:
This is a variation of the Average True Range (ATR), which measures market volatility. Like the SWMA, the ATR is smoothed using Sine-based weighting, where central values are more heavily considered compared to the extremities. This improves sensitivity to changes in volatility while maintaining stability in highly volatile markets.
// Function to calculate the Sine-Weighted ATR
f_Sine_Weighted_ATR(simple int length) =>
var float sine_weights_atr = array.new_float(0)
array.clear(sine_weights_atr)
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(sine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(sine_weights_atr, i) / sum_weights_atr
array.set(sine_weights_atr, i, norm_weight_atr)
// Calculate Sine-Weighted ATR using true ranges
swatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
swatr := swatr + array.get(sine_weights_atr, i) * tr
swatr
ATR Bands:
Upper and lower bands are created by adding/subtracting the Sine-Weighted ATR from the SWMA. These bands help identify overbought or oversold conditions, and when the price crosses these levels, it may generate long or short trade signals.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(swma_src)
float swma = f_Sine_Weighted_MA(src, ma_length)
// Use normal ATR or Sine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Sine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float swma_up = swma + (atr * atr_mult)
float swma_dn = swma - (atr * atr_mult)
float src_l = b.calc_src(src_long)
float src_s = b.calc_src(src_short)
// Signal logic for crossovers and crossunders
var int signal = 0
if ta.crossover(src_l, swma_up)
signal := 1
if ta.crossunder(src_s, swma_dn)
signal := -1
//}
Signal Logic:
Long/Short Signals are triggered when the price crosses above or below the Sine-Weighted ATR bands
Backtest Mode and Equity Calculation
To evaluate its effectiveness, the indicator includes a backtest mode, allowing users to test its performance on historical data:
Backtest Equity: A detailed equity curve is calculated based on the generated signals over a user-defined period (startDate to endDate).
Buy and Hold Comparison: Alongside the strategy’s equity, a Buy-and-Hold equity curve is plotted for performance comparison.
Alerts
The indicator includes built-in alerts for both long and short signals, ensuring users are promptly notified when market conditions meet the criteria for an entry or exit.
Futures Beta Overview with Different BenchmarksBeta Trading and Its Implementation with Futures
Understanding Beta
Beta is a measure of a security's volatility in relation to the overall market. It represents the sensitivity of the asset's returns to movements in the market, typically benchmarked against an index like the S&P 500. A beta of 1 indicates that the asset moves in line with the market, while a beta greater than 1 suggests higher volatility and potential risk, and a beta less than 1 indicates lower volatility.
The Beta Trading Strategy
Beta trading involves creating positions that exploit the discrepancies between the theoretical (or expected) beta of an asset and its actual market performance. The strategy often includes:
Long Positions on High Beta Assets: Investors might take long positions in assets with high beta when they expect market conditions to improve, as these assets have the potential to generate higher returns.
Short Positions on Low Beta Assets: Conversely, shorting low beta assets can be a strategy when the market is expected to decline, as these assets tend to perform better in down markets compared to high beta assets.
Betting Against (Bad) Beta
The paper "Betting Against Beta" by Frazzini and Pedersen (2014) provides insights into a trading strategy that involves betting against high beta stocks in favor of low beta stocks. The authors argue that high beta stocks do not provide the expected return premium over time, and that low beta stocks can yield higher risk-adjusted returns.
Key Points from the Paper:
Risk Premium: The authors assert that investors irrationally demand a higher risk premium for holding high beta stocks, leading to an overpricing of these assets. Conversely, low beta stocks are often undervalued.
Empirical Evidence: The paper presents empirical evidence showing that portfolios of low beta stocks outperform portfolios of high beta stocks over long periods. The performance difference is attributed to the irrational behavior of investors who overvalue riskier assets.
Market Conditions: The paper suggests that the underperformance of high beta stocks is particularly pronounced during market downturns, making low beta stocks a more attractive investment during volatile periods.
Implementation of the Strategy with Futures
Futures contracts can be used to implement the betting against beta strategy due to their ability to provide leveraged exposure to various asset classes. Here’s how the strategy can be executed using futures:
Identify High and Low Beta Futures: The first step involves identifying futures contracts that have high beta characteristics (more sensitive to market movements) and those with low beta characteristics (less sensitive). For example, commodity futures like crude oil or agricultural products might exhibit high beta due to their price volatility, while Treasury bond futures might show lower beta.
Construct a Portfolio: Investors can construct a portfolio that goes long on low beta futures and short on high beta futures. This can involve trading contracts on stock indices for high beta stocks and bonds for low beta exposures.
Leverage and Risk Management: Futures allow for leverage, which means that a small movement in the underlying asset can lead to significant gains or losses. Proper risk management is essential, using stop-loss orders and position sizing to mitigate the inherent risks associated with leveraged trading.
Adjusting Positions: The positions may need to be adjusted based on market conditions and the ongoing performance of the futures contracts. Continuous monitoring and rebalancing of the portfolio are essential to maintain the desired risk profile.
Performance Evaluation: Finally, investors should regularly evaluate the performance of the portfolio to ensure it aligns with the expected outcomes of the betting against beta strategy. Metrics like the Sharpe ratio can be used to assess the risk-adjusted returns of the portfolio.
Conclusion
Beta trading, particularly the strategy of betting against high beta assets, presents a compelling approach to capitalizing on market inefficiencies. The research by Frazzini and Pedersen emphasizes the benefits of focusing on low beta assets, which can yield more favorable risk-adjusted returns over time. When implemented using futures, this strategy can provide a flexible and efficient means to execute trades while managing risks effectively.
References
Frazzini, A., & Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics, 111(1), 1-25.
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. Journal of Finance, 47(2), 427-465.
Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. Journal of Business, 45(3), 444-454.
Ang, A., & Chen, J. (2010). Asymmetric volatility: Evidence from the stock and bond markets. Journal of Financial Economics, 99(1), 60-80.
By utilizing the insights from academic literature and implementing a disciplined trading strategy, investors can effectively navigate the complexities of beta trading in the futures market.
Fear Greed Zones by Relative Strength IndexThis is a visual modification of the relative Strength Index (RSI) to express extreme areas as fear and greed Zones.
// Input
rsiLength = input.int(14, "RSI Length", minval=1)
// RSI calculation
rsi = ta.rsi(close, rsiLength)
FEAR GREED ZONES
The "Fear Greed Zones Script" indicator is designed to help traders identify psychological levels of fear and greed in the market by utilising relative strength index. It primarily utilises the Relative Strength Index of price to gauge market sentiment, with the following key features:
Color-Codes
Dark Red: Indicates a greed zone , suggesting extreme overbought conditions (high risk) and a possible price reversal downward.
Dark Green: Represents a fear zone, indicating extreme oversold conditions (low risk) and potential for price reversal upward.
Yellow: Serves as a neutral zone with medium risk.
Usage
Market Sentiment Analysis: Traders can use the fear and greed zones to assess overall market sentiment, aligning their strategies with prevailing emotional biases. This helps in identifying potential entry and exit points based on market psychology.
Risk Management: Understanding fear or greed influences market behavior and allows traders to manage their risk more effectively with the knowledge of high or low risk areas; as they can anticipate potential reversals or continuations in price trends.
Conclusion
The "Fear Greed Zones" Script is a valuable tool for traders looking to leverage market psychology. By clearly identifying areas where fear or greed may be influencing price movements, it aids in making more informed trading decisions.
Money Wave Script (Visual Adaptive MFI)This Script is a visual modification of the Money Flow Index (MFI)
//@version=5
indicator(title="Money Flow Index", shorttitle="MFI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
length = input.int(title="Length", defval=14, minval=1, maxval=2000)
src = hlc3
mf = ta.mfi(src, length)
plot(mf, "MF", color=#7E57C2)
overbought=hline(80, title="Overbought", color=#787B86)
hline(50, "Middle Band", color=color.new(#787B86, 50))
oversold=hline(20, title="Oversold", color=#787B86)
fill(overbought, oversold, color=color.rgb(126, 87, 194, 90), title="Background")
This Money Wave Script is culled from. the Money Flow Index with visual representation to help traders identify money flow. In addition, the waves can be smoothened. Here’s a detailed overview based on its functionality, color coding, usage, risk management, and a concluding summary.
Functionality
The Money Wave Script operates as an oscillator that measures the inflow and outflow of money into an asset over a specified period. It calculates the MFI by considering both price and volume, which allows it to assess buying and selling pressures more accurately than traditional indicators that rely solely on price data.
Color Coding
The indicator employs a color-coded scheme to enhance visual interpretation:
Green Area: Indicates bullish conditions when the normalized Money wave is above zero, suggesting buying pressure.
Red Area: Indicates bearish conditions when the normalized Money wave is below zero, suggesting selling pressure.
Background Colors: The background changes to green when the MoneyWave exceeds the upper threshold (overbought) and red when it falls below the lower threshold (oversold), providing immediate visual cues about market conditions.
Usage
Traders utilize the Money Wave indicator in various ways:
Identifying Overbought and Oversold Levels: By observing the MFI readings, traders can determine when an asset may be overbought or oversold, prompting potential entry or exit points.
Spotting Divergences: Traders look for divergences between price and the MFI to anticipate potential reversals. For example, if prices are making new highs but the MFI is not, it could indicate weakening momentum.
Trend Confirmation: The indicator can help confirm trends by showing whether buying or selling pressure is dominating.
Customizable Settings: Users can adjust parameters such as the MFI length , Smoothen index and overbought/oversold thresholds to tailor the indicator to their trading strategies.
Conclusion
The Money Wave indicator is a powerful tool for traders seeking to analyze market conditions based on the flow of money into and out of assets. Its combination of price and volume analysis, along with clear visual cues, makes it an effective choice for identifying overbought and oversold conditions, spotting divergences, and confirming trends.
Judas Swing ICT 01 [TradingFinder] New York Midnight Opening M15🔵 Introduction
The Judas Swing (ICT Judas Swing) is a trading strategy developed by Michael Huddleston, also known as Inner Circle Trader (ICT). This strategy allows traders to identify fake market moves designed by smart money to deceive retail traders.
By concentrating on market structure, price action patterns, and liquidity flows, traders can align their trades with institutional movements and avoid common pitfalls. It is particularly useful in FOREX and stock markets, helping traders identify optimal entry and exit points while minimizing risks from false breakouts.
In today's volatile markets, understanding how smart money manipulates price action across sessions such as Asia, London, and New York is essential for success. The ICT Judas Swing strategy helps traders avoid common pitfalls by focusing on key movements during the opening time and range of each session, identifying breakouts and false breakouts.
By utilizing various time frames and improving risk management, this strategy enables traders to make more informed decisions and take advantage of significant market movements.
In the Judas Swing strategy, for a bullish setup, the price first touches the high of the 15-minute range of New York midnight and then the low. After that, the price returns upward, breaks the high, and if there’s a candlestick confirmation during the pullback, a buy signal is generated.
bearish setup, the price first touches the low of the range, then the high. With the price returning downward and breaking the low, if there’s a candlestick confirmation during the pullback to the low, a sell signal is generated.
🔵 How to Use
To effectively implement the Judas Swing strategy (ICT Judas Swing) in trading, traders must first identify the price range of the 15-minute window following New York midnight. This range, consisting of highs and lows, sets the stage for the upcoming movements in the London and New York sessions.
🟣 Bullish Setup
For a bullish setup, the price first moves to touch the high of the range, then the low, before returning upward to break the high. Following this, a pullback occurs, and if a valid candlestick confirmation (such as a reversal pattern) is observed, a buy signal is generated. This confirmation could indicate the presence of smart money supporting the bullish movement.
🟣 Bearish Setup
For a bearish setup, the process is the reverse. The price first touches the low of the range, then the high. Afterward, the price moves downward again and breaks the low. A pullback follows to the broken low, and if a bearish candlestick confirmation is seen, a sell signal is generated. This confirmation signals the continuation of the downward price movement.
Using the Judas Swing strategy enables traders to avoid fake breakouts and focus on strong market confirmations. The strategy is versatile, applying to FOREX, stocks, and other financial instruments, offering optimal trading opportunities through market structure analysis and time frame synchronization.
To execute this strategy successfully, traders must combine it with effective risk management techniques such as setting appropriate stop losses and employing optimal risk-to-reward ratios. While the Judas Swing is a powerful tool for predicting price movements, traders should remember that no strategy is entirely risk-free. Proper capital management remains a critical element of long-term success.
By mastering the ICT Judas Swing strategy, traders can better identify entry and exit points and avoid common traps from fake market movements, ultimately improving their trading performance.
🔵 Setting
Opening Range : High and Low identification time range.
Extend : The time span of the dashed line.
Permit : Signal emission time range.
🔵 Conclusion
The Judas Swing strategy (ICT Judas Swing) is a powerful tool in technical analysis that helps traders identify fake moves and align their trades with institutional actions, reducing risk and enhancing their ability to capitalize on market opportunities.
By leveraging key levels such as range highs and lows, fake breakouts, and candlestick confirmations, traders can enter trades with more precision. This strategy is applicable in forex, stocks, and other financial markets and, with proper risk management, can lead to consistent trading success.
Risk Reward CalculatorPlanning your trading is an important step that you must do before buying the stock.
Risk and Reward Calculator is an important tool for the trader.
With this calculator, you only need to put the capital for one trade and it will automaticaly put the plan for you. But if you want to enter your plan for buy and sell, you just need to check the button and enter the number. the risk and reward calculator will suggest position size based on the information.
The Steps to use Risk Reward Calculator
1. enter how many percentage you can accept if your analysis is wrong.
2. enter how much money you want to trade
3. it will automaticaly calculate the plan for you
4. you can change the reward
5. but if you want to enter your own number, you can check the box. After that enter the number you want for your new plan.
TEMA For Loop [Mattes]The TEMA For Loop indicator is a powerful tool designed for technical analysis, combining the Triple Exponential Moving Average (TEMA) with a custom scoring mechanism based on a for loop. It evaluates price trends over a specified period, allowing traders to identify potential entry and exit points in the market. This indicator enhances decision-making by providing visual cues through dynamic candle coloring, reflecting market sentiment and trends effectively.
Technical Details:
Triple Exponential Moving Average (TEMA):
- TEMA is known for its responsiveness to price changes, as it reduces lag compared to traditional moving averages. The TEMA calculation employs three nested Exponential Moving Averages (EMAs) to produce a smoother trend line, which helps traders identify the direction and momentum of the market.
Scoring Mechanism:
- The scoring mechanism is based on a custom for loop that compares the current TEMA value to previous values over a specified range. The loop counts how many previous values are less than the current value, generating a score that reflects the strength of the trend:
- A higher score indicates a stronger upward trend.
- A lower (negative) score suggests a downward trend.
Threshold Levels:
- Upper Threshold: A score above this level signals a potential long entry, indicating strong bullish momentum.
- Lower Threshold: A score below this level indicates a potential short entry, suggesting bearish sentiment.
>>>These thresholds are adjustable, allowing traders to fine-tune their strategy according to their risk tolerance and market conditions.
Signal Logic:
- The indicator provides clear signals for entering long or short positions based on the score crossing the defined thresholds.
>>Long Entry Signal: When the smoothed score crosses above the upper threshold.
>>Short Entry Signal: When the smoothed score crosses below the lower threshold.
Why This Indicator Is Useful:
>>> Enhanced Decision-Making: The TEMA For Loop indicator offers traders a clear and objective view of market trends, reducing the emotional aspect of trading. By visualizing bullish and bearish conditions, it assists traders in making timely decisions.
>>> Customizable Parameters: The ability to adjust TEMA period, thresholds, and other settings allows traders to tailor the indicator to their specific trading strategies and market conditions.
Visual Clarity: The integration of dynamic candle coloring provides immediate visual cues about the prevailing trend, making it easier for traders to spot potential trade opportunities at a glance.
The TEMA For Loop - Smoothed with Candle Colors indicator is a sophisticated trading tool that utilizes TEMA and a custom scoring mechanism to identify and visualize market trends effectively. By employing dynamic candle coloring, traders gain immediate insights into market sentiment, enabling informed decision-making for entry and exit strategies. This indicator is designed for traders seeking a systematic approach to trend analysis, enhancing their trading performance through clear, actionable signals.
Risk Manage Position SizerThis is a risk management tool for traders. It calculates position sizes based on account balance and risk tolerance, and provides automated stop-loss suggestions. The script displays key information in a small table on the chart and plots important price levels.
How to use it:
Input Parameters:
Account Size: Enter your total trading account balance.
Risk Percentage: Set the percentage of your account you're willing to risk per trade.
Use Custom Stop Loss: Toggle this to use a manually entered stop loss price.
Custom Stop Loss Price: If enabled, enter your desired stop loss price.
Reading the Table:
The table displays:
Current Price
Stop Loss Price
Total Position Size (number of shares/contracts to trade)
1/3 Position Size (for scaling in/out)
Auto Stop 1, 2, and 3 (suggested stop loss levels)
Chart Indicators:
Red Line: Your stop loss level
Green Line: Auto Stop 1 (33% of range from entry to stop)
Yellow Line: Auto Stop 2 (67% of range)
Red Line: Auto Stop 3 (final stop, same as initial stop loss)
Trading Application:
Use the Total Position Size to determine how many shares/contracts to trade.
Consider using the 1/3 Position Size for scaling in or out of trades.
Use the Auto Stops to manage your risk as the trade progresses.
Customization:
Adjust the input parameters to fit your trading style and risk tolerance.
The script can be modified to add more features or change the calculation methods if needed.
This tool helps traders make more informed decisions about position sizing and stop placement, potentially improving risk management in their trading strategy. Remember, while this script provides suggestions, all trading decisions should be made based on your own analysis and risk tolerance.
Trend Strength After Reversal
This indicator measures trend strength after the reversal.
It can catch early reversal based on engulfing candlestick pattern or just the regular reversal.
Every reversal have to be confirmed by a close above reversal pattern.
Trend strength is measured by counting subsequent closing confirming the reversal
Breakout & Distribution DetectorHow the Script Works:
1. Bollinger Bands:
• The upper and lower Bollinger Bands are used to detect volatility and potential breakouts. When the price closes above the upper band, it’s considered a bullish breakout. When the price closes below the lower band, it’s a bearish breakout.
2. RSI (Relative Strength Index):
• The RSI is used for momentum confirmation. A bullish breakout is confirmed if the RSI is above 50, and a bearish breakout is confirmed if the RSI is below 50.
• If the RSI enters overbought (above 70) or oversold (below 30) levels, it signals a distribution phase, indicating the market may be ready to reverse or consolidate.
3. Moving Average:
• A simple moving average (SMA) of 20 periods is used to ensure we’re trading in the direction of the trend. Breakouts above the upper Bollinger Band are valid if the price is above the SMA, while breakouts below the lower Bollinger Band are valid if the price is below the SMA.
4. Signals and Alerts:
• BUY Signal: A green “BUY” label appears below the candle if a bullish breakout is detected.
• SELL Signal: A red “SELL” label appears above the candle if a bearish breakout is detected.
• Distribution Phase: The background turns purple if the market enters a distribution phase (RSI in overbought or oversold territory).
• Alerts: You can set alerts based on these conditions to get notifications for breakouts or when the market enters a distribution phase.
AmirAli 20 Pairs/USDT&BTCThis TradingView indicator, titled "20 Pairs/USDT&BTC," is designed to analyze and display the Exponential Moving Averages (EMAs) of various cryptocurrency pairs against USDT and BTC. Here's a detailed breakdown of its features, functionality, and usage:
Key Features:
Pairs Display: The indicator allows users to select which cryptocurrency pairs they wish to display on the chart. The available options include popular cryptocurrencies such as Ethereum (ETH), Binance Coin (BNB), Solana (SOL), Dogecoin (DOGE), Ripple (XRP), Litecoin (LTC), Polkadot (DOT), Avalanche (AVAX), Uniswap (UNI), Chainlink (LINK), Cardano (ADA), Cosmos (ATOM), Filecoin (FIL), Stellar (XLM), VeChain (VET), Enjin (ENJ), Celo (CELO), Hedera (HBAR), and Sandbox (SAND).
Dynamic Price Retrieval: For each selected pair, the indicator retrieves the closing prices for both USDT and BTC from Binance. This is done using the request.security function, which fetches real-time data.
EMA Calculation: The indicator calculates and plots the EMA for each cryptocurrency pair over a user-defined length, allowing traders to identify trends and potential buy/sell signals based on price movements relative to their EMAs.
User Customization: Users can customize several parameters, including the time frame for data retrieval, EMA length, and the visibility of each pair.
Market Hours Visualization: The indicator highlights the trading hours with a gray background, helping users identify when the market is active.
How to Use the Indicator:
Adding the Indicator: To use the indicator, add it to your TradingView chart by searching for "20 Pairs/USDT&BTC" in the public library or by pasting the provided Pine Script code into a new indicator script.
Select Pairs: Enable or disable specific cryptocurrency pairs in the input options at the top of the script. For example, if you want to analyze ETH and ADA, ensure that the respective boxes are checked.
Adjust Time Frame: Set the time frame for the indicator. You can choose any time frame or leave it blank to use the current chart's time frame.
Set EMA Length: Choose the length for the EMA calculation based on your trading strategy. A shorter EMA (e.g., 5) reacts more quickly to price changes, while a longer EMA (e.g., 20) smooths out price fluctuations.
Observe Trends: Monitor the plotted EMAs for the selected pairs. Crossovers of the price with the EMA can indicate potential buy or sell signals. For instance, if the price crosses above the EMA, it may signal a bullish trend, whereas a crossover below could indicate a bearish trend.
Consider Market Hours: Pay attention to the gray background during U.S. trading hours, as this may indicate higher volatility and trading opportunities.
Conclusion
The "20 Pairs/USDT&BTC" indicator is a powerful tool for cryptocurrency traders looking to analyze multiple pairs simultaneously. By providing a visual representation of EMAs, it aids in identifying trends and potential trading opportunities in a user-friendly manner. Make sure to adapt the settings according to your trading strategy and market conditions for optimal results.
Amir Hasankhah & Ali Beyki
Dynamic Darvas BoxBu Darvas Box göstergesi, finansal piyasadaki potansiyel fiyat kırılımlarını hacimle birlikte analiz eden dinamik bir sistem sunar. Geliştirdiğiniz bu Pine Script, belirli bir "bakış aralığı" parametresi kullanarak geçmiş fiyat hareketlerinden yüksek ve düşük noktalar oluşturur ve bu seviyelerin kırılımını takip eder. Hacimli veya hacimsiz kırılımlar da ayrıca işaretlenir. Aşağıda hem Türkçe hem de İngilizce açıklamalar yer almakta:
Türkçe Açıklama:
Darvas Kutusu ve Hacim Kırılımı
Bu gösterge, fiyatların Darvas Kutusu mantığıyla analiz edilmesini sağlar ve kutunun kırılım seviyelerini hacimle birlikte değerlendirir.
Bakış Aralığı (bakis_araligi): Bu parametre, fiyatın geçmişte kaç bar geri giderek yeni bir yüksek veya düşük seviyenin tespit edilmesi gerektiğini belirler.
Hacim SMA (hacim_sma): Hacim için kullanılan basit hareketli ortalamanın (SMA) uzunluğunu belirler. Gösterge, hacim ortalamasının üzerinde veya altında olup olmadığını bu SMA değerine göre değerlendirir.
Kapanış Fiyatı ile Tamamlama (kapanis_kullan): Eğer bu seçenek aktifse, kutu kapanış fiyatı baz alınarak tamamlanır. Aksi takdirde, yüksek ve düşük seviyelerle tamamlanır.
Kırılım Fiyatını Göster (kirilim_goster): Hacim yetersiz olsa bile kırılım seviyesini etiketlemek için kullanılır.
Bu göstergede, yüksek bir fiyatın oluşması durumunda bir kutu başlatılır. Kutu, bakış aralığı boyunca yüksek ve düşük seviyeler ile onaylanır. Sonrasında, fiyatın kutu seviyesini kırıp kırmadığı izlenir. Eğer fiyat kutunun üzerine çıkarsa veya altına düşerse, hacim durumu kontrol edilerek bir "Hacimli Kırılım" veya "Hacimsiz Kırılım" etiketi gösterilir.
Kutu Arka Plan Renkleri: Kutu içerisindeki fiyat hareketinin durumu, renklerle gösterilir:
Yukarı Kırılım: Kutunun üst seviyesinin kırılması durumunda yeşil renk.
Aşağı Kırılım: Kutunun alt seviyesinin kırılması durumunda kırmızı renk.
Nötr: Kutu içinde tarafsız durum için sarı renk.
Ayrıca, kutunun orta hattı (orta_hat), yüksek ve düşük seviyelerin ortalamasını temsil eder ve fiyatın bu çizgiyi kaç kez kestiğini analiz etmek için kullanılabilir.
English Description:
Darvas Box and Volume Breakout
This indicator implements a dynamic Darvas Box strategy that tracks potential price breakouts in combination with volume analysis.
Lookback Period (bakis_araligi): This parameter defines how many bars back the price needs to look for determining a new high or low.
Volume SMA (hacim_sma): Specifies the length of the Simple Moving Average (SMA) for volume. The indicator uses this value to determine if volume is above or below average.
Completion with Closing Price (kapanis_kullan): If this option is enabled, the box is completed based on the closing price. Otherwise, the high and low prices are used for completion.
Show Breakout Price (kirilim_goster): This option is used to label the breakout price, even if the volume is below the average.
The indicator starts a box when a new high price is detected. The box is confirmed over the lookback period using high and low levels. The breakout levels are then monitored. If the price breaks above the upper or lower box boundary, it checks the volume condition and labels the breakout as either "Volume Breakout" or "Non-Volume Breakout."
Box Background Colors: The price movement within the box is represented with colors:
Upward Breakout: The background is green if the upper box boundary is broken.
Downward Breakout: The background is red if the lower boundary is broken.
Neutral: The background is yellow for neutral price movement within the box.
Additionally, the middle line (orta_hat) represents the average of the high and low levels and can be used to analyze how many times the price crosses this midline.
HTF LQ SweepThe following script recognises QL sweeps in the desired time frame with alarm function!
Theory:
There is liquidity above highs and below lows. If this is tapped and the market reacts strongly immediately, the probability of a reversal is greatly increased! In the chart, this is defined in such a way that a candle has its wicks BELOW the old low, but the close is ABOVE the old low. the same applies to the high, of course!
In such a case we have an "LQ Sweep"
How does the script work?
Williams 3 fractals are used as a basis. These are meaningful as lows or highs. Whenever a fractal is created, the price level is saved.
This means that not only the last fractal is relevant, but all historical fractals as long as they have not been reached!
If a candle reaches the level, but shows a rejection and closes within the level again, we have our "LQ Sweep" setup.
In the script you can select the timeframe in which the market has to be analysed. When the QL sweep occurs, an alert is triggered. This saves a lot of time because you can analyse different markets in different timeframes at the same time!
Each QL Sweep is marked in the chart when we are in the selected timeframe. These can also be deactivated so that only the last sweep is displayed.
Benefits for the trader:
An LQ sweep is a nice confirmation for a reversal.
If we have such an LQ sweep, we can wait in the lower timeframe for further confirmation, such as a structural break, to position our entries there.
The alarm function saves us a lot of time and we only go to the chart when a potential setup has been created.
You can set different time frames in the script: The selected time frame is then scanned and sends a signal when the event occurs.
