Visualization of price changes with Updated LineThis indicator is used to identify the upward or downward momentum of a trend and to visualize the corresponding price fluctuations.
Calculation of the Fluctuation
The price fluctuation (Fluctuation) is calculated and added to the rising fractuation array if it is rising or to the falling fractuation array if it is falling.
Calculating Moving Averages
A moving average is calculated for each fractuation to determine the momentum or strength of the trend. In this case, the higher the value of the moving average, the stronger the momentum in that direction.
Generation of Cross Signals
Detects the point at which a rising moving average crosses a falling moving average. At this crossing point, a triangle shape will be plotted on the chart at the timing of a possible trend turning point or push.
Displaying Lines
Based on this crosspoint, a line is drawn. This line represents a push in the direction of the trend and helps to identify price reversals and pushes. The line will rise when the uptrend is strengthening and fall when the downtrend is gaining momentum.
Thus, the signals and lines used to determine trend pushes and momentum are plotted visually and designed to help traders make decisions based on this information.
Indikator dan strategi
Williams %R StrategyThe Williams %R Strategy implemented in Pine Script™ is a trading system based on the Williams %R momentum oscillator. The Williams %R indicator, developed by Larry Williams in 1973, is designed to identify overbought and oversold conditions in a market, helping traders time their entries and exits effectively (Williams, 1979). This particular strategy aims to capitalize on short-term price reversals in the S&P 500 (SPY) by identifying extreme values in the Williams %R indicator and using them as trading signals.
Strategy Rules:
Entry Signal:
A long position is entered when the Williams %R value falls below -90, indicating an oversold condition. This threshold suggests that the market may be near a short-term bottom, and prices are likely to reverse or rebound in the short term (Murphy, 1999).
Exit Signal:
The long position is exited when:
The current close price is higher than the previous day’s high, or
The Williams %R indicator rises above -30, indicating that the market is no longer oversold and may be approaching an overbought condition (Wilder, 1978).
Technical Analysis and Rationale:
The Williams %R is a momentum oscillator that measures the level of the close relative to the high-low range over a specific period, providing insight into whether an asset is trading near its highs or lows. The indicator values range from -100 (most oversold) to 0 (most overbought). When the value falls below -90, it indicates an oversold condition where a reversal is likely (Achelis, 2000). This strategy uses this oversold threshold as a signal to initiate long positions, betting on mean reversion—an established principle in financial markets where prices tend to revert to their historical averages (Jegadeesh & Titman, 1993).
Optimization and Performance:
The strategy allows for an adjustable lookback period (between 2 and 25 days) to determine the range used in the Williams %R calculation. Empirical tests show that shorter lookback periods (e.g., 2 days) yield the most favorable outcomes, with profit factors exceeding 2. This finding aligns with studies suggesting that shorter timeframes can effectively capture short-term momentum reversals (Fama, 1970; Jegadeesh & Titman, 1993).
Scientific Context:
Mean Reversion Theory: The strategy’s core relies on mean reversion, which suggests that prices fluctuate around a mean or average value. Research shows that such strategies, particularly those using oscillators like Williams %R, can exploit these temporary deviations (Poterba & Summers, 1988).
Behavioral Finance: The overbought and oversold conditions identified by Williams %R align with psychological factors influencing trading behavior, such as herding and panic selling, which often create opportunities for price reversals (Shiller, 2003).
Conclusion:
This Williams %R-based strategy utilizes a well-established momentum oscillator to time entries and exits in the S&P 500. By targeting extreme oversold conditions and exiting when these conditions revert or exceed historical ranges, the strategy aims to capture short-term gains. Scientific evidence supports the effectiveness of short-term mean reversion strategies, particularly when using indicators sensitive to momentum shifts.
References:
Achelis, S. B. (2000). Technical Analysis from A to Z. McGraw Hill.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1979). How I Made One Million Dollars… Last Year… Trading Commodities. Windsor Books.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
This explanation provides a scientific and evidence-based perspective on the Williams %R trading strategy, aligning it with fundamental principles in technical analysis and behavioral finance.
Bollinger Band Squeeze with Dotted MidlinesBollinger Band Squeeze with Dotted Midlines
Overview:
The Bollinger Band Squeeze with Dotted Midlines indicator is a powerful tool designed to identify periods of low volatility in the market, known as "squeeze" conditions, which often precede significant price movements. By combining Bollinger Bands and Keltner Channels, this indicator highlights when the market is consolidating and prepares traders for potential breakouts.
Key Features:
• Squeeze Detection: The indicator fills the area between the Bollinger Bands and Keltner Channels with a semi-transparent red color when both the upper and lower Bollinger Bands are within the Keltner Channels. This visual cue signifies a squeeze condition.
• Dynamic Color Filling: When the Bollinger Bands move outside the Keltner Channels, the fill color changes to a semi-transparent white, indicating the end of the squeeze and the potential start of increased volatility.
• Enhanced Visual Clarity:
o Upper and Lower Bands: The upper and lower lines of both the Bollinger Bands and Keltner Channels are plotted with increased thickness (3pt) for better visibility.
o Midlines with Dotted Effect: The middle lines (50% lines) for both the Bollinger Bands and Keltner Channels are plotted as dotted lines using circles with a thinner line width (1pt), providing a clear yet unobtrusive reference point.
Indicator Components:
1. Bollinger Bands (Orange Lines):
o Upper Bollinger Band: Calculated as the moving average plus a multiple of the standard deviation.
o Lower Bollinger Band: Calculated as the moving average minus a multiple of the standard deviation.
o Middle Bollinger Band: The simple moving average (SMA) of the closing price.
2. Keltner Channels (White Lines):
o Upper Keltner Channel: Calculated as the exponential moving average (EMA) plus a multiple of the average true range (ATR).
o Lower Keltner Channel: Calculated as the EMA minus a multiple of the ATR.
o Middle Keltner Channel: The EMA of the closing price.
3. Squeeze Condition Fill:
o Red Fill (40% Opacity): Indicates a squeeze condition where the Bollinger Bands are entirely within the Keltner Channels.
o White Fill (40% Opacity): Indicates normal market conditions where the Bollinger Bands have moved outside the Keltner Channels.
How to Use:
1. Identifying Squeeze Conditions:
o Look for Red Filled Areas: When you see the area between the Bollinger Bands and Keltner Channels filled in semi-transparent red, it signals a squeeze condition. This means the market is experiencing low volatility and may be preparing for a significant move.
2. Preparing for Potential Breakouts:
o Monitor for Fill Color Changes: A transition from red to white fill suggests that the squeeze is ending, and volatility is increasing. Traders often interpret this as a potential opportunity for a breakout in either direction.
3. Utilizing Midlines:
o Reference Midlines for Trend Direction: The dotted midlines provide insight into the overall trend. Crossing of the price above or below these lines can offer additional confirmation for trading decisions.
Customization Options:
• Bollinger Bands Settings:
o Length: Default is 20 periods. Adjust to change the sensitivity of the bands.
o Multiplier: Default is 2.0. Modify to increase or decrease the band width based on standard deviation.
• Keltner Channels Settings:
o Length: Default is 20 periods. Alter to adjust the responsiveness of the channels.
o Multiplier: Default is 1.5. Change to widen or narrow the channels based on average true range.
Advantages:
• Visual Clarity: Enhanced line thickness and semi-transparent fills make it easy to spot key market conditions at a glance.
• Early Warning System: By identifying squeeze conditions, traders can anticipate potential breakouts and plan their strategies accordingly.
• Flexible Application: Suitable for various timeframes and trading styles, including day trading, swing trading, and position trading.
Limitations:
• False Signals: Like all technical indicators, it may produce false signals, especially in choppy or range-bound markets.
• Should Be Used with Other Indicators: For better accuracy, it's recommended to use this indicator in conjunction with other technical analysis tools and not as a standalone signal generator.
Conclusion:
The Bollinger Band Squeeze with Dotted Midlines indicator is a valuable addition to any trader's toolkit. By effectively highlighting periods of consolidation and potential breakout points, it aids in making informed trading decisions. The visual enhancements improve usability, allowing traders to quickly interpret market conditions and respond appropriately.
Crypto Divergence from BTCThis script is used to indicate when price action of a crypto coin is diverging significantly from that of BTC.
Explanation of the Script:
Inputs:
roc_length: The period used for calculating the Rate of Change.
ma_length: The period used for the moving average of the ROC.
threshold: The percentage difference that indicates a divergence.
Price Data:
The script retrieves the current asset's price and Bitcoin's price.
ROC Calculation:
The ROC for both the current asset and BTC is calculated based on the defined roc_length.
Moving Averages:
Simple moving averages (SMA) of the ROC values are calculated to smooth out the data.
Divergence Detection:
The indicator checks if the current asset's ROC MA is significantly higher or lower than Bitcoin's ROC MA based on the specified threshold.
Plotting:
The script plots the ROC values and their moving averages.
It also highlights the background in green when a bullish divergence is detected (when the asset is moving up while BTC is lagging) and in red for a bearish divergence.
Alternative Shark Harmonic Pattern [TradingFinder] ALT Shark🔵 Introduction
The Alternative Shark harmonic pattern, similar to the original Shark harmonic pattern introduced by Scott Carney, is a powerful tool in technical analysis used to identify potential reversal zones (PRZ) in financial markets.
These harmonic patterns help traders spot key turning points in market trends by relying on specific Fibonacci ratios. The Alternative Shark pattern is particularly unique due to its distinct Fibonacci retracements within the PRZ, which differentiate it from the standard Shark pattern and provide traders with more precise entry and exit signals.
By focusing on harmonic patterns and utilizing tools like the Harmonic Pattern Indicator, traders can easily identify both the Shark and Alternative Shark patterns, making it easier to find PRZs and capture potential trend reversals. This enhanced detection of potential reversal zones allows for better trade optimization and improved risk management.
Incorporating the Alternative Shark pattern into your technical analysis strategy enables you to enhance your trading performance by identifying market reversals with greater accuracy, improving the timing of your trades, and reducing risks associated with sudden market shifts.
🟣 Understanding the Types of Alternative Shark Pattern
The Alternative Shark harmonic pattern, much like the original Shark pattern, forms at the end of price trends and is divided into two types: Bullish and Bearish Alternative Shark patterns.
Bullish Alternative Shark Pattern :
This pattern typically forms at the end of a downtrend, signaling a potential reversal into an uptrend. Traders can use this pattern to identify buy entry points. The image below illustrates the core components of the Bullish Alternative Shark Pattern.
Bearish Alternative Shark Pattern :
Conversely, the Bearish Alternative Shark Pattern appears at the end of an uptrend and signals a potential reversal to a downtrend. This variation allows traders to adjust their strategies for selling. The image below outlines the characteristics of the Bearish Alternative Shark Pattern.
🟣 Differences Between Shark and Alternative Shark Patterns
Although both patterns share similar structures and serve as tools for identifying price reversals, there is one key difference between them :
AB to XA Ratio : In the Shark pattern, the AB leg retraces between 1 and 2 of the XA leg, whereas in the Alternative Shark pattern, this retracement is reduced to 0.382 to 0.618 of the XA leg. This difference in the retracement ratio leads to slightly different trade signals and can affect the timing of entry and exit points.
Other ratios and reversal signals remain consistent between the two patterns, but this difference in the AB to XA ratio provides traders with more nuanced opportunities to optimize their trades.
🔵 How to Use
🟣 Trading with the Bullish Alternative Shark Pattern
The Bullish Alternative Shark Pattern functions similarly to the traditional Bullish Shark, acting as a reversal pattern that helps traders recognize the end of a downtrend and the beginning of an uptrend.
The main distinction lies in the reduced AB retracement, which can offer more refined entry signals. Once the pattern completes, traders can look to enter buy trades and place a stop-loss below the lowest point of the pattern for effective risk management.
🟣 Trading with the Bearish Alternative Shark Pattern
The Bearish Alternative Shark Pattern operates much like the Bearish Shark pattern but with the adjusted AB to XA ratio. This difference provides traders with unique entry points for sell trades. Once the pattern is fully identified, traders can enter short positions, placing a stop-loss above the highest point of the pattern to safeguard against market fluctuations.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Alternative Shark harmonic pattern, despite its structural similarity to the traditional Shark pattern, introduces a key difference in the AB to XA ratio, making it a valuable addition to the trader’s toolkit. This subtle variation enables traders to pinpoint reversal points with greater accuracy and fine-tune their trading strategies.
As with any technical pattern, it is crucial to use the Alternative Shark pattern in combination with other technical indicators and strong risk management practices. Incorporating this pattern into a broader trading strategy can help traders enhance their ability to detect and capitalize on market reversals more effectively.
Fourier Transformed & Kalman Filtered EMA Crossover [Mattes]The Fourier Transformed & Kalman Filtered EMA Crossover (FTKF EMAC) is a trend-following indicator that leverages Fourier Transform approximation, Kalman Filtration, and two Exponential Moving Averages (EMAs) of different lengths to provide accurate and smooth market trend signals. By combining these three components, it captures the underlying market cycles, reduces noise, and produces actionable insights, making it suitable for detecting both emerging trends and confirming existing ones.
TECHNICALITIES:
>>> The Fourier Transform approximation is designed to identify dominant cyclical patterns in price action by focusing on key frequencies, while filtering out noise and less significant movements. It emphasizes the most meaningful price cycles, enabling the indicator to isolate important trends while ignoring minor fluctuations. This cyclical awareness adds an extra layer of depth to trend detection, allowing the EMAs to work with a cleaner and more reliable data set.
>>> The Kalman Filter adds dynamic noise reduction, adjusting its predictions of future price trends based on past and current data. As new price data comes in, the filter recalibrates itself to ensure that the price action remains smooth and devoid of erratic movements. This real-time adjustment is key to minimizing lag while avoiding false signals, which ensures that the EMAs react to more accurate and stable market data. The Kalman Filter’s ability to smooth price data without losing sensitivity to trend changes complements the Fourier approximation, ensuring a high level of precision in volatile and stable market environments.
>>> The EMA Crossover involves using two EMAs: a shorter EMA that reacts quickly to price movements and a longer EMA that responds more slowly. The shorter EMA is responsible for capturing immediate market shifts, detecting potential bullish or bearish trends. The longer EMA smooths out price fluctuations and provides trend confirmation, working with the shorter EMA to ensure the signals are reliable. When the shorter EMA crosses above the longer EMA, it indicates a bullish trend, likewise when it goes below the longer EMA, it signals a bearish trend. This setup provides a clear way to track market direction, with color-coded signals (green for bullish, red for bearish) for visual clarity. The flexibility of adjusting the EMA periods allows traders to fine-tune the indicator to their preferred timeframe and strategy, making it adaptable to different market conditions.
|-> A key technical aspect is that the first EMA should always be shorter than the second one. If the first EMA is longer than the second, the tool’s effectiveness is compromised because the faster EMA is designed to signal long conditions, while the longer one is made for signaling a bearish trend. Reversing their roles would lead to delayed or confused signals, reducing the indicator’s ability to detect trend shifts early and making it less efficient in volatile markets. This is the only key weakness of the indicator, failure to submit to this rule will result in confusion.
>>> These components work together like a clock to create a comprehensive and effective trend-following system. The Fourier approximation highlights key cyclical movements, the Kalman Filter refines these movements by removing noise, and the EMAs interpret the filtered data to generate actionable trend signals. Each component enhances the next, ensuring that the final output is both responsive and reliable, with minimal false signals or lag. creating an indicator using widespread concepts which haven't been combined before.
Summary
This indicator combines Fourier Transform approximation, Kalman Filtration, and two EMAs of different lengths to deliver accurate and timely trend-following signals. The Fourier approximation identifies dominant market cycles, while the Kalman Filter dynamically removes noise and refines the price data in real time. The two EMAs then use this filtered data to generate buy and sell signals based on their crossovers. The shorter EMA reacts quickly to price changes, while the longer EMA provides smoother trend confirmation. The components work in synergy to capture trends with minimal false signals or lag, ensuring traders can act promptly on market shifts. Customizable EMA periods make the tool adaptable to different market conditions, enhancing its versatility for various trading strategies.
To use the indicator, traders should adjust the EMA lengths based on their timeframe and strategy, ensuring that the shorter EMA remains shorter than the longer EMA to preserve the tool’s responsiveness. The color-coded signals offer visual clarity, making it easy to identify potential entry and exit points. This confluence of Fourier, Kalman, and EMA methodologies provides a smooth, highly effective trend-following tool that excels in both trending and ranging markets.
Advanced Economic Indicator by USCG_VetAdvanced Economic Indicator by USCG_Vet
tldr:
This comprehensive TradingView indicator combines multiple economic and financial metrics into a single, customizable composite index. By integrating key indicators such as the yield spread, commodity ratios, stock indices, and the Federal Reserve's QE/QT activities, it provides a holistic view of the economic landscape. Users can adjust the components and their weights to tailor the indicator to their analysis, aiding in forecasting economic conditions and market trends.
Detailed Description
Overview
The Advanced Economic Indicator is designed to provide traders and investors with a powerful tool to assess the overall economic environment. By aggregating a diverse set of economic indicators and financial market data into a single composite index, it helps identify potential turning points in the economy and financial markets.
Key Features:
Comprehensive Coverage: Includes 14 critical economic and financial indicators.
Customizable Components: Users can select which indicators to include.
Adjustable Weights: Assign weights to each component based on perceived significance.
Visual Signals: Clear plotting with threshold lines and background highlights.
Alerts: Set up alerts for when the composite index crosses user-defined thresholds.
Included Indicators
Yield Spread (10-Year Treasury Yield minus 3-Month Treasury Yield)
Copper/Gold Ratio
High Yield Spread (HYG/IEF Ratio)
Stock Market Performance (S&P 500 Index - SPX)
Bitcoin Performance (BLX)
Crude Oil Prices (CL1!)
Volatility Index (VIX)
U.S. Dollar Index (DXY)
Inflation Expectations (TIP ETF)
Consumer Confidence (XLY ETF)
Housing Market Index (XHB)
Manufacturing PMI (XLI ETF)
Unemployment Rate (Inverse SPY as Proxy)
Federal Reserve QE/QT Activities (Fed Balance Sheet - WALCL)
How to Use the Indicator
Configuring the Indicator:
Open Settings: Click on the gear icon (⚙️) next to the indicator's name.
Inputs Tab: You'll find a list of all components with checkboxes and weight inputs.
Including/Excluding Components
Checkboxes: Check or uncheck the box next to each component to include or exclude it from the composite index.
Default State: By default, all components are included.
Adjusting Component Weights:
Weight Inputs: Next to each component's checkbox is a weight input field.
Default Weights: Pre-assigned based on economic significance but fully adjustable.
Custom Weights: Enter your desired weight for each component to reflect your analysis.
Threshold Settings:
Bearish Threshold: Default is -1.0. Adjust to set the level below which the indicator signals potential economic downturns.
Bullish Threshold: Default is 1.0. Adjust to set the level above which the indicator signals potential economic upswings.
Setting the Timeframe:
Weekly Timeframe Recommended: Due to the inclusion of the Fed's balance sheet data (updated weekly), it's best to use this indicator on a weekly chart.
Changing Timeframe: Select 1W (weekly) from the timeframe options at the top of the chart.
Interpreting the Indicator:
Composite Index Line
Plot: The blue line represents the composite economic indicator.
Movement: Observe how the line moves relative to the threshold lines.
Threshold Lines
Zero Line (Gray Dotted): Indicates the neutral point.
Bearish Threshold (Red Dashed): Crossing below suggests potential economic weakness.
Bullish Threshold (Green Dashed): Crossing above suggests potential economic strength.
Background Highlights
Red Background: When the composite index is below the bearish threshold.
Green Background: When the composite index is above the bullish threshold.
No Color: When the composite index is between the thresholds.
Understanding the Components
1. Yield Spread
Description: The difference between the 10-year and 3-month U.S. Treasury yields.
Economic Significance: An inverted yield curve (negative spread) has historically preceded recessions.
2. Copper/Gold Ratio
Description: The price ratio of copper to gold.
Economic Significance: Copper is tied to industrial demand; gold is a safe-haven asset. The ratio indicates risk sentiment.
3. High Yield Spread (HYG/IEF Ratio)
Description: Ratio of high-yield corporate bonds (HYG) to intermediate-term Treasury bonds (IEF).
Economic Significance: Reflects investor appetite for risk; widening spreads can signal credit stress.
4. Stock Market Performance (SPX)
Description: S&P 500 Index levels.
Economic Significance: Broad measure of U.S. equity market performance.
5. Bitcoin Performance (BLX)
Description: Bitcoin Liquid Index price.
Economic Significance: Represents risk appetite in speculative assets.
6. Crude Oil Prices (CL1!)
Description: Front-month crude oil futures price.
Economic Significance: Influences inflation and consumer spending.
7. Volatility Index (VIX)
Description: Market's expectation of volatility (fear gauge).
Economic Significance: High VIX indicates market uncertainty; inverted in the indicator to align directionally.
8. U.S. Dollar Index (DXY)
Description: Value of the U.S. dollar relative to a basket of foreign currencies.
Economic Significance: Affects international trade and commodity prices; inverted in the indicator.
9. Inflation Expectations (TIP ETF)
Description: iShares TIPS Bond ETF prices.
Economic Significance: Reflects market expectations of inflation.
10. Consumer Confidence (XLY ETF)
Description: Consumer Discretionary Select Sector SPDR Fund prices.
Economic Significance: Proxy for consumer confidence and spending.
11. Housing Market Index (XHB)
Description: SPDR S&P Homebuilders ETF prices.
Economic Significance: Indicator of the housing market's health.
12. Manufacturing PMI (XLI ETF)
Description: Industrial Select Sector SPDR Fund prices.
Economic Significance: Proxy for manufacturing activity.
13. Unemployment Rate (Inverse SPY as Proxy)
Description: Inverse of the SPY ETF price.
Economic Significance: Represents unemployment trends; higher inverse SPY suggests higher unemployment.
14. Federal Reserve QE/QT Activities (Fed Balance Sheet - WALCL)
Description: Total assets held by the Federal Reserve.
Economic Significance: Indicates liquidity injections (QE) or withdrawals (QT); impacts interest rates and asset prices.
Customization and Advanced Usage
Adjusting Weights:
Purpose: Emphasize components you believe are more predictive or relevant.
Method: Increase or decrease the weight value next to each component.
Example: If you think the yield spread is particularly important, you might assign it a higher weight.
Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Trading and investing involve risks, including possible loss of principal. Always conduct your own analysis and consult with a professional financial advisor before making investment decisions.
Kaufman's Adaptive Moving Average (KAMA)Another simple easy to use indicator that incorporates mean reversion and trend following.
Kaufman's Adaptive Moving Average (KAMA) is an indicator developed by Perry Kaufman that adjusts its sensitivity based on market volatility. It is designed to react more quickly during trending markets and slow down in sideways or volatile markets. The primary idea is that in a trending market, the moving average should be more sensitive to price changes, while in a non-trending market, it should be less responsive to noise.
KAMA Formula
The formula for the Kaufman Adaptive Moving Average is:
Efficiency Ratio (ER): Measures the efficiency of price movement over a given period.
ER
=
Smoothing Factor
Volatility
=
Sum of absolute price change
Sum of absolute price movement
ER=
Volatility
Smoothing Factor
=
Sum of absolute price movement
Sum of absolute price change
The Efficiency Ratio is calculated by taking the price change over a defined period and dividing it by the total price movement (which is the sum of absolute price changes).
Smoothing Constant (SC): This is a factor used to adjust the moving average's responsiveness:
SC
=
ER
×
(
2
/
(
𝑛
+
1
)
)
+
(
1
−
ER
)
×
(
2
/
(
𝑛
+
1
)
)
SC=ER×(2/(n+1))+(1−ER)×(2/(n+1))
where n is the length of the moving average period.
Steps to Calculate KAMA:
Efficiency Ratio (ER):
Calculate the sum of absolute price changes over the chosen period.
Calculate the sum of absolute price movements over the same period.
Smoothing Constant (SC):
Use the Efficiency Ratio to adjust the smoothing factor.
KAMA Calculation:
The initial KAMA is the simple moving average (SMA) of the first n periods.
For subsequent periods, KAMA is calculated using a formula based on the smoothing constant and previous KAMA values.
experiment with the variables as you like!!
Pappabborgia Nasdaq RSI This script provides a custom Relative Strength Index (RSI) indicator that plots both the RSI of the selected stock and the Nasdaq (IXIC) on the same chart.
It offers a clear, side-by-side view to help traders better understand the stock's momentum relative to the overall market.
Key Features:
RSI Calculation for the Stock:
The script calculates the RSI for the chosen stock, with a default period of 14, adjustable to fit different timeframes.
The stock’s RSI is displayed in green 🟢, providing a direct view of its strength and momentum 📈.
RSI of the Nasdaq:
The script fetches the Nasdaq’s closing prices and calculates its RSI, which is shown in red for clear comparison 🔴.
Legend for Clarity:
A simple legend in the top-right corner identifies the green line as the stock’s RSI and the red line as the Nasdaq’s RSI, making it easy to interpret 📊.
Why Comparing the Stock's RSI to the Nasdaq Matters:
Broader Market Context:
Viewing both RSIs on the same chart helps you see whether the stock is moving in sync with the broader market or behaving independently. This provides valuable context for decision-making 📉.
Relative Strength Insights:
Comparing the stock’s RSI to the Nasdaq’s RSI highlights whether the stock is outperforming or underperforming the overall market, helping identify potential opportunities or risks 🟢🔴.
Improved Risk Management:
Monitoring overbought or oversold conditions in both the stock and Nasdaq RSIs can signal broader market trends and help avoid risky trades ⚠️.
Overall Benefit:
By tracking the RSI of both the stock and the Nasdaq, this script offers a powerful tool for understanding a stock's relative strength, providing essential context for smarter trading decisions 🎯.
Fibonacci Retracement Levels (Horizontal)With this, you should be able to see the Fibonacc-i retracement levels plotted as horizontal lines on your chart. If needed, you can adjust the len parameter to increase or decrease the lookback period used to calculate the high and low points.
Horizontal Lines: I've added horizontal lines for each Fibonacci retracement level (0%, 23.6%, 38.2%, 50%, 61.8%, 100%), starting from the current bar index to ensure they extend horizontally across the chart.
Labels: Labels are now placed on the right side of the chart for each level so you can easily identify the Fibonacci levels.
Dont make me crossStrategy Overview
This trading strategy utilizes Exponential Moving Averages (EMAs) to generate buy and sell signals based on the crossover of two EMAs, which are shifted downwards by 50 points. The strategy aims to identify potential market reversals and trends based on these crossovers.
Components of the Strategy
Exponential Moving Averages (EMAs):
Short EMA: This is calculated over a shorter period (default is 9 periods) and is more responsive to recent price changes.
Long EMA: This is calculated over a longer period (default is 21 periods) and provides a smoother view of the price trend.
Both EMAs are adjusted by a fixed shift amount of -50 points.
Input Parameters:
Short EMA Length: The period used to calculate the short-term EMA. This can be adjusted based on the trader's preference or market conditions.
Long EMA Length: The period used for the long-term EMA, also adjustable.
Shift Amount: A fixed value (default -50) that is subtracted from both EMAs to shift their values downwards. This is useful for visual adjustments or specific strategy requirements.
Plotting:
The adjusted EMAs are plotted on the price chart. The short EMA is displayed in blue, and the long EMA is displayed in red. This visual representation helps traders identify the crossover points easily.
Signal Generation:
Buy Signal: A buy signal is generated when the short EMA crosses above the long EMA. This is interpreted as a bullish signal, indicating potential upward price movement.
Sell Signal: A sell signal occurs when the short EMA crosses below the long EMA, indicating potential downward price movement.
Trade Execution:
When a buy signal is triggered, the strategy enters a long position.
Conversely, when a sell signal is triggered, the strategy enters a short position.
Trading Logic
Market Conditions: The strategy is most effective in trending markets. During sideways or choppy market conditions, it may generate false signals.
Risk Management: While this script does not include explicit risk management features (like stop-loss or take-profit), traders should consider implementing these to manage their risk effectively.
Customization
Traders can customize the EMA lengths and the shift amount based on their analysis and preferences.
The strategy can also be enhanced with additional indicators, such as volume or volatility measures, to filter signals further.
Use Cases
This strategy can be applied to various timeframes, such as intraday, daily, or weekly charts, depending on the trader's style.
It is suitable for both novice and experienced traders, offering a straightforward approach to trading based on technical analysis.
Summary
The EMA Crossover Strategy with a -50 shift is a straightforward technical analysis approach that capitalizes on the momentum generated by the crossover of short and long-term EMAs. By shifting the EMAs downwards, the strategy can help traders visualize potential entry and exit points more clearly, although it's important to consider additional risk management and market context for effective trading.
Exponantial Spread StrategyIt is strongly recommended to evaluate the strategy's performance on long time frames such as 1D or 4H.
This strategy calculates a custom moving average by the formula EMA+(TEMA-DEMA)*G,
G being the gain parameter. The main idea behind that is since TEMA is much more adaptive than DEMA their spread give us momentum, and incorporating this with a gain allows us to calculate a very responsive but yet not noisy moving average.
We calculate 4 MAs like described with gains 0,1,2,3 from less adaptive (normal EMA) to most adaptive. When they align in terms of position and the price is above the original MA we enter a long position, and do partial exits at each crossunder weighted by how adaptive ma is, the more adaptive the less weight, we do a full stop when the price crossed below under the original MA or the position aligment changed.
European and American Trading Sessions (Blue)The European and American trading sessions, in particular, are known for their volatility and volume, making them key periods for traders to watch.
This Pine Script indicator, "European and American Trading Sessions," helps traders visually distinguish these sessions directly on their charts by shading the background during active hours. We use this indicator in combination with the one that highlights the nighttime phases in white.
Here's a breakdown of how the indicator works:
Key Features of the Script:
Timezone Configuration:
The script allows users to select a timezone from a predefined list that includes UTC, London, Rome, New York, and Tokyo. This flexibility ensures that the session times are accurately displayed regardless of the server or local time of the user.
European Session Parameters:
Users can set the start and end times for the European session. By default, the session runs from 08:00 to 12:00, but the input options make it customizable down to the minute. The European session is highlighted with a light blue background (36% opacity) to avoid overwhelming the chart while still providing a clear visual cue.
American Session Parameters:
Similar to the European session, the American session can be customized. The default times are set from 12:01 to 20:59. This session is highlighted in a slightly darker blue (80% opacity), providing a distinct visual difference from the European session.
Session Timing Calculation:
The script calculates the start and end times for each session based on the selected timezone. It uses the timestamp() function to account for year, month, day, hour, and minute, ensuring that session timings are accurately applied to each day’s trading activity.
Background Highlighting:
Once the session times are defined, the script checks if the current chart time (time) falls within the European or American trading session. If the condition is true, the corresponding background color is applied, visually highlighting the active session directly on the chart. This feature makes it easy to identify when the European or American markets are in play.
Benefits for Traders:
Clear Session Visibility: The color-coded background makes it effortless for traders to identify when key trading sessions are active without needing to constantly check the clock.
Customizable to Your Needs:
With full control over the start and end times for both sessions, traders can adapt the indicator to fit their specific trading hours or preferences.
Timezone Flexibility:
No matter where you're trading from, the ability to set the timezone ensures that the sessions are displayed correctly according to your local time.
Explanation of the Code:
Timezone Selection:
Allows the user to select a timezone from predefined options such as Europe/Rome, America/New_York, etc. This timezone will be used to calculate session start and end times.
Session Timing Inputs:
The script takes user inputs for the start and end times of the European and American trading sessions. These inputs include the hour and minute for both sessions.
Colors:
The color of the European session is set to a blue shade with 36% opacity.
The American session is also colored blue but with a higher opacity of 80%.
Timestamp Calculation:
The timestamp() function converts the input hours and minutes into a time value, accounting for the selected timezone.
Session Conditions:
The script checks if the current time (time) falls within the European or American session. If true, it applies the respective background color for that session. This approach creates clear visual highlights on the chart, marking the active hours of the European and American trading sessions based on user inputs.
Options Series - Supertrend, HalfTrend, Ichimoku Cloud and P_SAR➤ Supertrend:
➤ HalfTrend:
➤ Ichimoku Cloud:
➤ Parabolic SAR:
⭐ Overview and How It Works:
This script combines multiple popular technical indicators—Supertrend, HalfTrend, Ichimoku Cloud, and Parabolic SAR—into a single, cohesive tool for analyzing price trends and reversals. Designed for traders who prefer multi-layered confirmation, it displays non-overlay signals in a candlestick format, helping users make sense of intricate market dynamics. It also includes a "Master Candle" condition, which aggregates the signals from all indicators, providing a powerful snapshot of market sentiment.
References for study,
Supertrend and HalfTrend and Ichimoku Cloud and Parabolic SAR
⭐ Key Features and Functionality:
The script integrates four indicators and visually represents them in a non-overlay fashion, meaning that each indicator's signal appears on separate candlestick layers. It uses color coding to differentiate between bullish and bearish signals. The Master Candle is a unique feature that aggregates the signals from all indicators to show the overall sentiment.
Supertrend: It uses ATR and a multiplier factor to create a trailing stop, identifying bullish and bearish trends.
HalfTrend: It analyzes market volatility that provides buy and sell signals based on volatility channels and historical highs and lows.
Ichimoku Cloud: It leverages historical highs and lows to form the conversion and baseline, which are compared to assess market strength.
Parabolic SAR: A stop-and-reverse system that highlights potential reversals. It is based on time and price, offering traders potential reversal points.
Master Candle: It computes a score based on the confluence of all four indicators, adding another layer of confirmation.
🎨 Visualizations and User Experience:
The script's user interface is highly visual, with color-coded candlesticks plotted across multiple layers. Each indicator has its own color coding for bullish and bearish signals, ensuring clarity:
➤ Green for bullish signals.
➤ Red for bearish signals.
➤ Each candlestick layer represents a different indicator (e.g., Supertrend, HalfTrend, etc.), making it easy for the trader to isolate and interpret signals.
➤ The "Master Candle" provides an overarching view of the market by displaying a consolidated signal, which can reduce confusion from mixed indicator signals.
⭐ Settings and Customization:
The script is highly customizable, allowing users to adjust the settings for each indicator. Key customizable parameters include:
• Supertrend ATR Period and Factor
• HalfTrend Amplitude and Channel Deviation
• Ichimoku Conversion, Base, and Lagging Span Periods
• Parabolic SAR Start, Increment, and Maximum value
Additionally, users can toggle the visibility of each indicator and customize the look of the plot to suit their preferences.
⭐ Uniqueness of the Concept:
No repaints. This is the advanced representation and the combination of multiple indicators into a single script, along with a powerful "Master Candle" that aggregates them, makes this tool unique. Most scripts provide isolated indicator signals, while this one brings together four powerful indicators and visually simplifies the analysis. The non-overlay style and color-coded candlesticks offer traders an easy-to-understand, actionable visual cue, which stands out from traditional indicator overlays.
🚀 Conclusion:
This script is a comprehensive, multi-indicator trading tool suitable for traders looking for reliable trend-following and reversal detection. Its ability to provide an aggregated "Master Candle" signal reduces noise and aids in better decision-making. Customization options allow users to tailor it to their trading style, while its clear visualizations provide an excellent user experience.
Fibonacci & Bollinger Bands StrategyThis strategy combines Bollinger Bands and Fibonacci retracement/extension levels to identify potential entry and exit points in the market. Here’s a breakdown of each component and how the strategy works:
1. Bollinger Bands:
Bollinger Bands consist of a simple moving average (SMA) and two standard deviations (upper and lower bands) plotted above and below the SMA. The bands expand and contract based on market volatility.
Purpose in Strategy:
The lower band represents an area where the market might be oversold.
The upper band represents an area where the market might be overbought.
The price crossing these bands suggests overextended market conditions, which can be used to identify potential reversals.
2. Fibonacci Retracement and Extension Levels:
Fibonacci retracement levels are horizontal lines that indicate where price might find support or resistance as it retraces some of its previous movement. Common retracement levels are 61.8% and 78.6%.
Fibonacci extension levels are used to project areas where the price might extend after completing a retracement. These levels can help determine potential targets after a significant price movement.
Purpose in Strategy:
The strategy calculates the most recent swing high (fibHigh) and swing low (fibLow) over a lookback period. It then plots Fibonacci retracement and extension levels based on this range.
The Fibonacci levels are used as key support and resistance areas. The price approaching or touching these levels signals potential turning points in the market.
3. Entry Criteria:
A long position (buy) is triggered when:
The price crosses below the lower Bollinger Band, indicating an oversold condition.
The price is near or above a Fibonacci extension level (calculated based on the most recent price swing).
This suggests that the price is potentially reaching a strong support area, where a reversal is likely.
4. Exit Criteria:
The long position is closed (exit trade) when either:
The price touches or crosses the upper Bollinger Band, signaling an overbought condition.
The price reaches a Fibonacci retracement level or exceeds the recent swing high (fibHigh), indicating a potential exhaustion point or a reversal area.
5. General Strategy Logic:
The strategy takes advantage of market volatility (captured by the Bollinger Bands) and key support/resistance levels (determined by Fibonacci retracement and extension levels).
By combining these two techniques, the strategy identifies potential entry points at oversold levels with the expectation that the market will retrace or reverse upward, especially when near key Fibonacci extension levels.
Exit points are identified by potential overbought levels (Bollinger upper band) or key Fibonacci retracement levels, where the price might reverse downward.
6. Conditions to Execute the Strategy:
The Fibonacci levels are only calculated once the price has made a significant movement, establishing a recent high and low over a 50-bar period (which you can adjust). This ensures the Fibonacci levels are based on meaningful swings.
The entry and exit signals are filtered using both Bollinger Bands and Fibonacci levels to ensure that trades are not taken solely based on one indicator, thus reducing false signals.
Key Features of the Strategy:
Trend-following with reversal: It tries to catch reversals when the price hits extreme levels (Bollinger Bands) while respecting important Fibonacci levels.
Dynamic market adaptation: The strategy adapts to market conditions as it recalculates Fibonacci levels based on recent price swings and adjusts the Bollinger Bands for market volatility.
Confirmation through multiple indicators: It uses both the volatility-based signals from Bollinger Bands and the price structure from Fibonacci levels to confirm trade entries and exits.
Summary of the Strategy:
The strategy looks to buy low and sell high based on oversold/overbought signals from Bollinger Bands and Fibonacci levels that indicate key support and resistance zones.
By combining these two technical indicators, the strategy aims to reduce risk and increase accuracy by only entering trades when both indicators suggest favorable conditions.
DF: Horizontal Levels and Colors for NYSE TICK Chart
DF: Horizontal Levels and Colors for NYSE TICK Chart
This is intended to be added very specifically to your NYSE TICK chart.
This script creates a custom indicator designed to enhance the visual analysis
of market breadth through the NYSE TICK data. It features:
1. **Horizontal Levels**:
- **1300 and -1300**: Gray lines indicating extreme bullish and bearish conditions.
- **1000 and -1000**: Light red and green lines representing significant support and resistance zones.
- **850 and -850**: Customizable blue lines that can be adjusted according to user preferences.
**Zero Line**: A solid white line marking the neutral point, drawn prominently for quick reference.
2. **Color Fills**:
- Red fill between 1000 and 1300 to highlight extreme bullish sentiment.
- Green fill between -1000 and -1300 to signify extreme bearish sentiment.
3. **Exponential Moving Average (EMA)**:
- Calculated based on user-defined length (default set to 8).
- The EMA line's color dynamically adjusts based on its slope:
- White when trending upwards.
- Magenta when trending downwards, providing quick visual cues of market momentum.
Overall, this script serves as a powerful tool for traders seeking to visualize market trends, support and resistance levels, and market breadth through the NYSE TICK data, enhancing their decision-making process in trading.
TASC 2024.11 Ultimate Strength Index█ OVERVIEW
This script implements the Ultimate Strength Index (USI) indicator, introduced by John Ehlers in his article titled "Ultimate Strength Index (USI)" from the November 2024 edition of TASC's Traders' Tips . The USI is a modified version of Wilder's original Relative Strength Index (RSI) that incorporates Ehlers' UltimateSmoother lowpass filter to produce an output with significantly reduced lag.
█ CONCEPTS
Many technical indicators, including the RSI, lag due to their heavy reliance on historical data. John Ehlers reformulated the RSI to substantially reduce lag by applying his UltimateSmoother filter to upward movements ( strength up - SU ) and downward movements ( strength down - SD ) in the time series, replacing the standard process of smoothing changes with rolling moving averages (RMAs). Ehlers' recent works, covered in our recent script publications, have shown that the UltimateSmoother is an effective alternative to other classic averages, offering notably less lag in its response.
Ehlers also modified the RSI formula to produce an index that ranges from -1 to +1 instead of 0 to 100. As a result, the USI indicates bullish conditions when its value moves above 0 and bearish conditions when it falls below 0.
The USI retains many of the strengths of the traditional RSI while offering the advantage of reduced lag. It generally uses a larger lookback window than the conventional RSI to achieve similar behavior, making it suitable for trend trading with longer data lengths. When applied with shorter lengths, the USI's peaks and valleys tend to align closely with significant turning points in the time series, making it a potentially helpful tool for timing swing trades.
█ CALCULATIONS
The first step in the USI's calculation is determining each bar's strength up (SU) and strength down (SD) values. If the current bar's close exceeds the previous bar's, the calculation assigns the difference to SU. Otherwise, SU is zero. Likewise, if the current bar's close is below the previous bar's, it assigns the difference to SD. Otherwise, SD is zero.
Next, instead of the RSI's typical smoothing process, the USI's calculation applies the UltimateSmoother to the short-term average SU and SD values, reducing high-frequency chop in the series with low lag.
Finally, this formula determines the USI value:
USI = ( Ult (SU) − Ult (SD)) / ( Ult (SU) + Ult (SD)),
where Ult (SU) and Ult (SD) are the smoothed average strength up and strength down values.
Chartonaut: GlimpseDisplays an overview of some key metrics as a table.
Market Cap : value of the company.
Float Shares : number of shares available for trading.
AR# : average range over the last # sessions.
ATR# : average true range over the last # sessions.
ATR#/MA# : distance of the current price from the given moving average (MA) in terms of ATR multiples.
Rel Volatility : current session's range, including gaps from previous close, relative to the ATR.
Additionally, it highlights some metrics if they are crossing a given threshold, as to warn that some criteria might not be met.
Delayed Opening Price Line with GuardrailsThis Delayed Opening Price Line with Guardrails indicator will draw 5 price level lines on the chart each day, beginning at the open of the first candle after a delay period specified by the user in the indicator settings. The default delay is 30 minutes from market open.
The lines are drawn at the open price of the first candle after the delay period, and then a specified increment above and below that price level. These increments default to 80 and 100, and can be adjusted in the indicator settings.
Most markets, indices, and equities have a finite and consistent range of price movement within a trading day. Eg. a particular stock may usually move no more that $50 up or down in a given day, which can be proven by looking at a historical chart. This indicator allows the user to quickly display that range on the chart once it's been defined.
Important note: This indicator is designed to be used on an intra-day chart - eg. minutes, or hourly. It will give an error if used on a longer time-frame chart.
Candle Range Theory | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Candle Range Theory Indicator! This powerful tool offers a strategy built around the Candle Range Theory, which analyzes market movements through the relative size and structure of price candles. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new Candle Range Theory Indicator :
Implementation of the Candle Range Theory
FVG & Order Block Entry Methods
2 Different TP / SL Methods
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The Candle Range Theory (CRT) indicator operates by identifying significant price movements through the relative size and structure of candlesticks. A key part of the strategy is determining large candles based on their range compared to the Average True Range (ATR) in a higher timeframe. Once identified, a breakout of either the high wick or the low wick of the large candle is required. This breakout is considered a liquidity grab. After that, the indicator waits for confirmation through Fair Value Gaps (FVGs) or Order Blocks (OBs). The confirmation structure must be the opposite direction of the breakout, for example if the high wick is broken, a bearish FVG is required for the short entry. After a confirmation signal is received, the indicator will trigger entry points based on your chosen entry method (FVG or OB), and exit points will be calculated using either a dynamic ATR-based TP/SL method or fixed percentages. Alerts for Buy, Sell, Take-Proft, and Stop-Loss are available.
🚩 UNIQUENESS
This indicator stands out because it combines two highly effective entry methods: Fair Value Gaps (FVGs) and Order Blocks (OBs). You can choose between these strategies depending on market conditions. Additionally, the dynamic TP/SL system uses the ticker's volatility to automatically calculate stop-loss and take-profit targets. The backtesting dashboard provides metrics about the performance of the indicator. You can use it to tune the settings for best use in the current tiker. The Candle Range Theory approach offers more flexibility compared to traditional indicators, allowing for better customization and control based on your risk tolerance.
⚙️ SETTINGS
1. General Configuration
Higher Timeframe: Customize the higher timeframe for analysis. Recommended combinations include M15 -> H4, H4 -> Daily, Daily -> Weekly, and Weekly -> Monthly.
HTF Candle Size: Define the size of the higher timeframe candles as Big, Normal, or Small to filter valid setups based on their range relative to ATR.
Entry Mode: Choose between FVGs and Order Blocks for your entry triggers.
Require Retracement: Enable this option if you want a retracement to the FVG or OB for entry confirmation.
Show HTF Candle Lines: Toggle to display the higher timeframe candle lines for better visual clarity.
2. Fair Value Gaps
FVG Sensitivity: You may select between Low, Normal, High or Extreme FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivities resulting in spotting bigger FVGs, and higher sensitivities resulting in spotting all sizes of FVGs.
3. Order Blocks
Swing Length: Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
4. TP / SL
TP / SL Method:
a) Dynamic: The TP / SL zones will be auto-determined by the algorithm based on the Average True Range (ATR) of the current ticker.
b) Fixed : You can adjust the exact TP / SL ratios from the settings below.
Dynamic Risk: The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
Manoj Personal EMA 5-203 EMA Trading Strategy Script Overview:
EMAs Used:
5 EMA: Short-term moving average.
20 EMA: Medium-term moving average.
564 EMA: Long-term moving average to identify overall trend direction.
Entry Signals:
Strong Buy: Triggered when:
Price is above the 564 EMA (uptrend).
The 5 EMA crosses above the 20 EMA (bullish crossover).
The current candle is green (close > open).
Strong Sell: Triggered when:
Price is below the 564 EMA (downtrend).
The 5 EMA crosses below the 20 EMA (bearish crossover).
The current candle is red (close < open).
Exit Signal:
Position is closed when the price touches back to the 564 EMA (either side, up or down):
A "Close Position" label is shown in green for long trades.
A "Close Position" label is shown in red for short trades.
Risk Management:
Stop-Loss: Placed at the last swing low (for longs) or last swing high (for shorts), calculated over the last 10 bars.
Take-Profit: A 1:3 risk/reward ratio is used, where the potential reward is three times the risk.
Alerts:
Alerts are triggered for buy and sell signals.
Alerts are also triggered when the exit condition (price touching the 564 EMA) is met.
This script is designed to work on timeframes of 15 minutes or higher but can also be used for 5-minute scalping. It plots the EMAs on the chart, highlights buy/sell opportunities, shows stop-loss and take-profit levels, and generates alerts for key signals.
Stochastic Trendlines with Breakouts [Jamshid] - EnhancedStochastic Trendlines with Breakouts - Enhanced Version
This advanced Stochastic Trendlines with Breakouts script combines several powerful features to provide enhanced breakout detection based on the Stochastic Oscillator and additional confirmation signals. This script is designed to help traders identify key trend reversals, breakout points, and pivot levels with more accuracy by integrating advanced filters such as RSI confirmation, moving average trend filtering, volatility filtering, divergence detection, and multi-timeframe analysis.
Key Features:
Stochastic Oscillator-Based Breakouts:
Automatically detects breakouts based on the smoothed Stochastic Oscillator values (%K and %D), providing insights into overbought and oversold conditions.
Customizable overbought and oversold levels, with a mid-level (50) line for additional reference.
Trendlines on Pivot Points:
Automatically plots dynamic trendlines based on pivot highs and lows of the smoothed Stochastic %K, helping to visualize potential reversal points.
RSI Confirmation (Optional):
Filters breakout signals using the Relative Strength Index (RSI) to confirm breakouts only when the RSI is below 50 for downtrend breakouts and above 50 for uptrend breakouts.
Visual confirmation with a green "RSI Conf." label displayed on the chart when the RSI condition is met.
Moving Average Filter (Optional):
Confirms breakout signals in the direction of a user-defined Moving Average (MA) to trade in the overall market trend direction.
MA length is fully customizable.
Stochastic Divergence Filter (Optional):
Detects bullish or bearish divergence between the price and Stochastic Oscillator values, adding an extra layer of confirmation.
Multi-Timeframe Confirmation (Optional):
Confirms breakouts by checking the Stochastic %K and %D values from a higher timeframe. This helps in avoiding false signals by aligning with the broader market trend.
The higher timeframe can be customized to any timeframe (e.g., daily, weekly, etc.).
Volatility Filter (Optional):
Uses the ATR (Average True Range) to filter out breakouts during periods of low volatility, ensuring signals are only triggered when there is sufficient price movement.
ATR length and multiplier are fully customizable.
Custom Alerts:
Alerts are available for new trendline detections (both pivot high and pivot low) and for confirmed breakout signals. These alerts help traders stay informed in real-time without needing to monitor the chart continuously.
How to Use:
Customize the Stochastic Oscillator settings, such as %K smoothing and %D line parameters, to fit your trading strategy.
Enable or disable additional filtering features (RSI, MA, divergence, MTF, volatility) as needed.
Set up alerts for specific breakout conditions directly in TradingView to stay notified when breakout signals are triggered.
This script is designed for traders who are looking for precision breakout signals with added layers of confirmation to avoid false breakouts and enhance trading accuracy.
Prometheus Fractal WaveThe Fractal Wave is an indicator that uses a fractal analysis to determine where reversals may happen. This is done through a Fractal process, making sure a price point is in a certain set and then getting a Distance metric.
Calculation:
A bullish Fractal is defined by the current bar’s high being less than the last bar’s high, and the last bar’s high being greater than the second to last bar’s high, and the last bar’s high being greater than the third to last bar’s high.
A bearish Fractal is defined by the current low being greater than the last bar’s low, and the last bar’s low being less than the second to last bar’s low, and the last bar’s low being less than the third to last bar’s low.
When there is that bullish or bearish fractal the value we store is either the last bar’s high or low respective to bullish or bearish fractal.
Once we have that value stored we either subtract the last bar’s low from the bullish Fractal value, and subtract the last bar’s high from the bearish Fractal value. Those are our Distances.
Code:
isBullishFractal() =>
high > high and high < high and high > high
isBearishFractal() =>
low < low and low > low and low < low
var float lastBullishFractal = na
var float lastBearishFractal = na
if isBullishFractal() and barstate.isconfirmed
lastBullishFractal := high
if isBearishFractal() and barstate.isconfirmed
lastBearishFractal := low
//------------------------------
//-------CACLULATION------------
//------------------------------
bullWaveDistance = na(lastBullishFractal) ? na : lastBullishFractal - low
bearWaveDistance = na(lastBearishFractal) ? na : high - lastBearishFractal
We then plot the bullish distance and the negative bearish distance.
The trade scenarios come from when one breaks the zero line and then goes back above or below. So if the last bullish distance was below 0 and is now above, or if the last negative bearish distance was above 0 and now below. We plot a green label below a candle for a bullish scenario, or a red label above a candle for a bearish one, you can turn them on or off.
Code:
plot(bullWaveDistance, color=color.green, title="Bull Wave Distance", linewidth=2)
plot(-bearWaveDistance, color=color.red, title="Bear Wave Distance", linewidth=2)
plot(0, "Zero Line", color=color.gray, display = display.pane)
bearish_reversal = plot_labels ? bullWaveDistance < 0 and bullWaveDistance > 0 : na
bullish_reversal = plot_labels ? -bearWaveDistance > 0 and -bearWaveDistance < 0 : na
plotshape(bullish_reversal, location=location.belowbar, color=color.green, style=shape.labelup, title="Bullish Fractal", text="↑", display = display.all - display.status_line, force_overlay = true)
plotshape(bearish_reversal, location=location.abovebar, color=color.red, style=shape.labeldown, title="Bearish Fractal", text="↓", display = display.all - display.status_line, force_overlay = true)
We can see in this daily NASDAQ:QQQ chart that the indicator gives us marks that can either be used as Reversal signals or as breathers in the trend.
Since it is designed to provide reversals, on something like Gold where the uptrend has been strong, the signals may be just short breathers, not full blown strong reversal signs.
The indicator works just as well intra day as it does on larger timeframes.
We encourage traders to not follow indicators blindly, none are 100% accurate. Please comment on any desired updates, all criticism is welcome!
