buysellsignal-yashgode9The "buysellsignal-yashgode9" indicator utilizes a signal library to generate buy and sell signals based on price action, allowing traders to make informed decisions in their trading strategies.
Overview of the Indicator
The "buysellsignal-yashgode9" indicator is a technical analysis tool that identifies potential buying and selling points in the market. It does this by leveraging a signal library imported from `yashgode9/signalLib/2`, which contains predefined algorithms for analyzing market trends based on specified parameters.
Key Features
1.Input Parameters: The indicator allows users to customize several parameters:
- Depth: Determines the number of bars to look back for price analysis (default is 150).
- Deviation: Sets the threshold for price movement (default is 120).
- Backstep: Defines how many bars to step back when evaluating signals (default is 100).
- Label Transparency: Adjusts the transparency of labels displayed on the chart.
- Color Customization: Users can specify colors for buy and sell signals.
2.Signal Generation: The core functionality is driven by the `signalLib.signalLib` function, which analyzes the low and high prices over the specified depth and deviation. It returns a direction indicator along with price points (`zee1` and `zee2`) that are used to determine whether to issue a buy or sell signal.
3. Labeling and Visualization:
- The indicator creates labels on the chart to indicate buy and sell points based on the direction of the signal.
- Labels are color-coded according to user-defined settings, enhancing visual clarity.
- The indicator also manages the deletion of previous labels and lines to avoid clutter on the chart.
4. Repainting Logic: The script includes a repainting option, allowing it to update signals in real-time as new price data comes in. This can be beneficial for traders who want to see the most current signals but may also lead to misleading signals if not used cautiously.
Conclusion:-
The "buysellsignal-yashgode9" indicator is a versatile tool for traders looking to enhance their decision-making process by identifying key market entry and exit points. By allowing customization of parameters and colors, it caters to individual trading preferences while providing clear visual signals based on price action analysis. This indicator is particularly useful for those who rely on technical analysis in their trading strategies, as it combines automated signal generation with user-friendly visual cues.
Benefits and Applications:
1.Intraday Trading: The "buysellsignal-yashgode9" indicator is particularly well-suited for intraday trading, as it provides accurate and timely buy and sell signals based on the current market dynamics.
2.Trend-following Strategies: Traders who employ trend-following strategies can leverage the indicator's ability to identify the overall market direction, allowing them to align their trades with the dominant trend.
3.Swing Trading: The dynamic price tracking and signal generation capabilities of the indicator can be beneficial for swing traders, who aim to capture medium-term price movements.
Security Measures:
1. The code includes a security notice at the beginning, indicating that it is subject to the Mozilla Public License 2.0, which is a reputable open-source license.
2. The code does not appear to contain any obvious security vulnerabilities or malicious content that could compromise user data or accounts.
NOTE:- This indicator is provided under the Mozilla Public License 2.0 and is subject to its terms and conditions.
Disclaimer: The usage of "buysellsignal-yashgode9" indicator might or might not contribute to your trading capital(money) profits and losses and the author is not responsible for the same.
IMPORTANT NOTICE:
While the indicator aims to provide reliable buy and sell signals, it is crucial to understand that the market can be influenced by unpredictable events, such as natural disasters, political unrest, changes in monetary policies, or economic crises. These unforeseen situations may occasionally lead to false signals generated by the "buysellsignal-yashgode9" indicator.
Users should exercise caution and diligence when relying on the indicator's signals, as the market's behavior can be unpredictable, and external factors may impact the accuracy of the signals. It is recommended to thoroughly backtest the indicator's performance in various market conditions and to use it as one of the many tools in a comprehensive trading strategy, rather than solely relying on its output.
Ultimately, the success of the "buysellsignal-yashgode9" indicator will depend on the user's ability to adapt it to their specific trading style, market conditions, and risk management approach. Continuous monitoring, analysis, and adjustment of the indicator's settings may be necessary to maintain its effectiveness in the ever-evolving financial markets.
Author:- yashgode9
PineScript-version:- 5
This indicator aims to enhance trading decision-making by combining DEPTH, DEVIATION, BACKSTEP with custom signal generation, offering a comprehensive tool for traders seeking clear buy and sell signals on the TradingView platform.
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[DarkTrader] Strong High LowThe Strong High Low indicator calculates strong high and low pivots based on price action and the Average True Range (ATR). The calculation for both the high and low pivots involves analyzing recent candle behavior to identify significant levels where price reversal is likely. Specifically, it looks for consecutive bearish or bullish candles to determine whether a strong high or low has been established.
Indicator In Use :
For strong highs, the indicator checks if three consecutive candles are bearish, meaning their closing price is lower than their opening price. It further examines prior candles to confirm that they followed a specific pattern where a reversal could occur. If one of these earlier candles closed higher than it opened, the indicator assumes that this was a strong high, and it records either the high of the second or third candle from the pattern, depending on their relationship to each other.
Similarly, for strong lows, the indicator searches for three consecutive bullish candles where the close is higher than the open. The algorithm then reviews prior candles in the sequence to ensure that the market condition supports a potential low pivot. If an earlier candle closes lower than it opens, it marks this as a strong low. The final low point for the pivot is chosen based on a comparison between the second and third candles of the pattern.
Once the high and low pivots are determined, the indicator adjusts these levels using the ATR value. The ATR is added to the strong high pivot and subtracted from the strong low pivot to create slightly modified levels. This helps accommodate market volatility by widening the range of the high and low pivots, making the levels more reliable in reflecting potential reversal zones.
Finally, the strong high and low pivot lines are drawn on the chart, extending both to the left and right of the current price, based on the user-defined offset values. These lines give a visual cue of where key resistance and support levels exist, with labels marking the exact pivot values for easy reference.
[ALGOA+] Markov Chains Library by @metacamaleoLibrary "MarkovChains"
Markov Chains library by @metacamaleo. Created in 09/08/2024.
This library provides tools to calculate and visualize Markov Chain-based transition matrices and probabilities. This library supports two primary algorithms: a rolling window Markov Chain and a conditional Markov Chain (which operates based on specified conditions). The key concepts used include Markov Chain states, transition matrices, and future state probabilities based on past market conditions or indicators.
Key functions:
- `mc_rw()`: Builds a transition matrix using a rolling window Markov Chain, calculating probabilities based on a fixed length of historical data.
- `mc_cond()`: Builds a conditional Markov Chain transition matrix, calculating probabilities based on the current market condition or indicator state.
Basically, you will just need to use the above functions on your script to default outputs and displays.
Exported UDTs include:
- s_map: An UDT variable used to store a map with dummy states, i.e., if possible states are bullish, bearish, and neutral, and current is bullish, it will be stored
in a map with following keys and values: "bullish", 1; "bearish", 0; and "neutral", 0. You will only use it to customize your own script, otherwise, itĀ“s only for internal use.
- mc_states: This UDT variable stores user inputs, calculations and MC outputs. As the above, you donĀ“t need to use it, but you may get features to customize your own script.
For example, you may use mc.tm to get the transition matrix, or the prob map to customize the display. As you see, functions are all based on mc_states UDT. The s_map UDT is used within mc_statesĀ“s s array.
Optional exported functions include:
- `mc_table()`: Displays the transition matrix in a table format on the chart for easy visualization of the probabilities.
- `display_list()`: Displays a map (or array) of string and float/int values in a table format, used for showing transition counts or probabilities.
- `mc_prob()`: Calculates and displays probabilities for a given number of future bars based on the current state in the Markov Chain.
- `mc_all_states_prob()`: Calculates probabilities for all states for future bars, considering all possible transitions.
The above functions may be used to customize your outputs. Use the returned variable mc_states from mc_rw() and mc_cond() to display each of its matrix, maps or arrays using mc_table() (for matrices) and display_list() (for maps and arrays) if you desire to debug or track the calculation process.
See the examples in the end of this script.
Have good trading days!
Best regards,
@metacamaleo
-----------------------------
KEY FUNCTIONS
mc_rw(state, length, states, pred_length, show_table, show_prob, table_position, prob_position, font_size)
āāBuilds the transition matrix for a rolling window Markov Chain.
āāParameters:
āāāā state (string) : The current state of the market or system.
āāāā length (int) : The rolling window size.
āāāā states (array) : Array of strings representing the possible states in the Markov Chain.
āāāā pred_length (int) : The number of bars to predict into the future.
āāāā show_table (bool) : Boolean to show or hide the transition matrix table.
āāāā show_prob (bool) : Boolean to show or hide the probability table.
āāāā table_position (string) : Position of the transition matrix table on the chart.
āāāā prob_position (string) : Position of the probability list on the chart.
āāāā font_size (string) : Size of the table font.
āāReturns: The transition matrix and probabilities for future states.
mc_cond(state, condition, states, pred_length, show_table, show_prob, table_position, prob_position, font_size)
āāBuilds the transition matrix for conditional Markov Chains.
āāParameters:
āāāā state (string) : The current state of the market or system.
āāāā condition (string) : A string representing the condition.
āāāā states (array) : Array of strings representing the possible states in the Markov Chain.
āāāā pred_length (int) : The number of bars to predict into the future.
āāāā show_table (bool) : Boolean to show or hide the transition matrix table.
āāāā show_prob (bool) : Boolean to show or hide the probability table.
āāāā table_position (string) : Position of the transition matrix table on the chart.
āāāā prob_position (string) : Position of the probability list on the chart.
āāāā font_size (string) : Size of the table font.
āāReturns: The transition matrix and probabilities for future states based on the HMM.
Uptrick: Momentum-Volatility Composite Signal### Title: Uptrick: Momentum-Volatility Composite Signal
### Overview
The "Uptrick: Momentum-Volatility Composite Signal" is an innovative trading tool designed to offer traders a sophisticated synthesis of momentum, volatility, volume flow, and trend detection into a single comprehensive indicator. This tool stands out by providing an integrated view of market dynamics, which is critical for identifying potential trading opportunities with greater precision and confidence. Its unique approach differentiates it from traditional indicators available on the TradingView platform, making it a valuable asset for traders aiming to enhance their market analysis.
### Unique Features
This indicator integrates multiple crucial elements of market behavior:
- Momentum Analysis : Utilizes Rate of Change (ROC) metrics to assess the speed and strength of market movements.
- Volatility Tracking : Incorporates Average True Range (ATR) metrics to measure market volatility, aiding in risk assessment.
- Volume Flow Analysis : Analyzes shifts in volume to detect buying or selling pressure, adding depth to market understanding.
- Trend Detection : Uses the difference between short-term and long-term Exponential Moving Averages (EMA) to detect market trends, providing insights into potential reversals or confirmations.
Customization and Inputs
The Uptrick indicator offers a variety of user-defined settings tailored to fit different trading styles and strategies, enhancing its adaptability across various market conditions:
Rate of Change Length (rocLength) : This setting defines the period over which momentum is calculated. Shorter periods may be preferred by day traders who need to respond quickly to market changes, while longer periods could be better suited for position traders looking at more extended trends.
ATR Length (atrLength) : Adjusts the timeframe for assessing volatility. A shorter ATR length can help day traders manage the quick shifts in market volatility, whereas longer lengths might be more applicable for swing or position traders who deal with longer-term market movements.
Volume Flow Length (volumeFlowLength): Determines the analysis period for volume flow to identify buying or selling pressure. Day traders might opt for shorter periods to catch rapid volume changes, while longer periods could serve swing traders to understand the accumulation or distribution phases better.
Short EMA Length (shortEmaLength): Specifies the period for the short-term EMA, crucial for trend detection. Shorter lengths can aid day traders in spotting immediate trend shifts, whereas longer lengths might help swing traders in identifying more sustainable trend changes.
Long EMA Length (longEmaLength): Sets the period for the long-term EMA, which is useful for observing longer-term market trends. This setting is particularly valuable for position traders who need to align with the broader market direction.
Composite Signal Moving Average Length (maLength): This parameter sets the smoothing period for the composite signal's moving average, helping to reduce noise in the signal output. A shorter moving average length can be beneficial for day traders reacting to market conditions swiftly, while a longer length might help swing and position traders in smoothing out less significant fluctuations to focus on significant trends.
These customization options ensure that traders can fine-tune the Uptrick indicator to their specific trading needs, whether they are scanning for quick opportunities or analyzing more prolonged market trends.
### Functionality Details
The indicator operates through a sophisticated algorithm that integrates multiple market dimensions:
1. Momentum and Volatility Calculation : Combines ROC and ATR to gauge the marketās momentum and stability.
2. Volume and Trend Analysis : Integrates volume data with EMAs to provide a comprehensive view of current market trends and potential shifts.
3. Signal Composite : Each component is normalized and combined into a composite signal, offering traders a nuanced perspective on when to enter or exit trades.
The indicator performs its calculations as follows:
Momentum and Volatility Calculation:
roc = ta.roc(close, rocLength)
atr = ta.atr(atrLength)
Volume and Trend Analysis:
volumeFlow = ta.cum(volume) - ta.ema(ta.cum(volume), volumeFlowLength)
emaShort = ta.ema(close, shortEmaLength)
emaLong = ta.ema(close, longEmaLength)
emaDifference = emaShort - emaLong
Composite Signal Calculation:
Normalizes each component (ROC, ATR, volume flow, EMA difference) and combines them into a composite signal:
rocNorm = (roc - ta.sma(roc, rocLength)) / ta.stdev(roc, rocLength)
atrNorm = (atr - ta.sma(atr, atrLength)) / ta.stdev(atr, atrLength)
volumeFlowNorm = (volumeFlow - ta.sma(volumeFlow, volumeFlowLength)) / ta.stdev(volumeFlow, volumeFlowLength)
emaDiffNorm = (emaDifference - ta.sma(emaDifference, longEmaLength)) / ta.stdev(emaDifference, longEmaLength)
compositeSignal = (rocNorm + atrNorm + volumeFlowNorm + emaDiffNorm) / 4
### Originality
The originality of the Uptrick indicator lies in its ability to merge diverse market metrics into a unified signal. This multi-faceted approach goes beyond traditional indicators by offering a deeper, more holistic analysis of market conditions, providing traders with insights that are not only based on price movements but also on underlying market dynamics.
### Practical Application
The Uptrick indicator excels in environments where understanding the interplay between volume, momentum, and volatility is crucial. It is especially useful for:
- Day Traders : Can leverage real-time data to make quick decisions based on sudden market changes.
- Swing Traders : Benefit from understanding medium-term trends to optimize entry and exit points.
- Position Traders : Utilize long-term market trend data to align with overall market movements.
### Best Practices
To maximize the effectiveness of the Uptrick indicator, consider the following:
- Combine with Other Indicators : Use alongside other technical tools like RSI or MACD for additional validation.
- Adapt Settings to Market Conditions : Adjust the indicator settings based on the asset and market volatility to improve signal accuracy.
- Risk Management : Implement robust risk management strategies, including setting stop-loss orders based on the volatility measured by the ATR.
### Practical Examples and Demonstrations
- Example for Day Trading : In a volatile market, a trader notices a sharp increase in the momentum score coinciding with a surge in volume but stable volatility, signaling a potential bullish breakout.
- Example for Swing Trading : On a 4-hour chart, the indicator shows a gradual alignment of decreasing volatility and increasing buying volume, suggesting a strengthening upward trend suitable for a long position.
### Alerts and Their Uses
- Alert Configurations : Set alerts for when the composite score crosses predefined thresholds to capture potential buy or sell events.
- Strategic Application : Use alerts to stay informed of significant market moves without the need to continuously monitor the markets, enabling timely and informed trading decisions.
Technical Notes
Efficiency and Compatibility: The indicator is designed for efficiency, running smoothly across different trading platforms including TradingView, and can be easily integrated with existing trading setups. It leverages advanced mathematical models for normalizing and smoothing data, ensuring consistent and reliable signal quality across different market conditions.
Limitations : The effectiveness of the Uptrick indicator can vary significantly across different market conditions and asset classes. It is designed to perform best in liquid markets where data on volume, volatility, and price trends are readily available and reliable. Traders should be aware that in low-liquidity or highly volatile markets, the signals might be less reliable and require additional confirmation.
Usage Recommendations : While the Uptrick indicator is a powerful tool, it is recommended to use it in conjunction with other analysis methods to confirm signals. Traders should also continuously monitor the performance and adjust settings as needed to align with their specific trading strategies and market conditions.
### Conclusion
The "Uptrick: Momentum-Volatility Composite Signal" is a revolutionary tool that offers traders an advanced methodology for analyzing market dynamics. By combining momentum, volatility, volume, and trend detection into a single, cohesive indicator, it provides a powerful, actionable insight into market movements, making it an indispensable tool for traders aiming to optimize their trading strategies.
Larry Connors RSI 3 StrategyThe Larry Connors RSI 3 Strategy is a short-term mean-reversion trading strategy. It combines a moving average filter and a modified version of the Relative Strength Index (RSI) to identify potential buying opportunities in an uptrend. The strategy assumes that a short-term pullback within a long-term uptrend is an opportunity to buy at a discount before the trend resumes.
Components of the Strategy:
200-Day Simple Moving Average (SMA): The price must be above the 200-day SMA, indicating a long-term uptrend.
2-Period RSI: This is a very short-term RSI, used to measure the speed and magnitude of recent price changes. The standard RSI is typically calculated over 14 periods, but Connors uses just 2 periods to capture extreme overbought and oversold conditions.
Three-Day RSI Drop: The RSI must decline for three consecutive days, with the first drop occurring from an RSI reading above 60.
RSI Below 10: After the three-day drop, the RSI must reach a level below 10, indicating a highly oversold condition.
Buy Condition: All the above conditions must be satisfied to trigger a buy order.
Sell Condition: The strategy closes the position when the RSI rises above 70, signaling that the asset is overbought.
Who Was Larry Connors?
Larry Connors is a trader, author, and founder of Connors Research, a firm specializing in quantitative trading research. He is best known for developing strategies that focus on short-term market movements. Connors co-authored several popular books, including "Street Smarts: High Probability Short-Term Trading Strategies" with Linda Raschke, which has become a staple among traders seeking reliable, rule-based strategies. His research often emphasizes simplicity and robust testing, which appeals to both retail and institutional traders.
Scientific Foundations
The Relative Strength Index (RSI), originally developed by J. Welles Wilder in 1978, is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is typically used to identify overbought or oversold conditions in an asset. However, the use of a 2-period RSI in Connors' strategy is unconventional, as most traders rely on longer periods, such as 14. Connors' research showed that using a shorter period like 2 can better capture short-term reversals, particularly when combined with a longer-term trend filter such as the 200-day SMA.
Connors' strategies, including this one, are built on empirical research using historical data. For example, in a study of over 1,000 signals generated by this strategy, Connors found that it performed consistently well across various markets, especially when trading ETFs and large-cap stocks (Connors & Alvarez, 2009).
Risks and Considerations
While the Larry Connors RSI 3 Strategy is backed by empirical research, it is not without risks:
Mean-Reversion Assumption: The strategy is based on the premise that markets revert to the mean. However, in strong trending markets, the strategy may underperform as prices can remain oversold or overbought for extended periods.
Short-Term Nature: The strategy focuses on very short-term movements, which can result in frequent trading. High trading frequency can lead to increased transaction costs, which may erode profits.
Market Conditions: The strategy performs best in certain market environments, particularly in stable uptrends. In highly volatile or strongly trending markets, the strategy's performance can deteriorate.
Data and Backtesting Limitations: While backtests may show positive results, they rely on historical data and do not account for future market conditions, slippage, or liquidity issues.
Scientific literature suggests that while technical analysis strategies like this can be effective in certain market conditions, they are not foolproof. According to Lo et al. (2000), technical strategies may show patterns that are statistically significant, but these patterns often diminish once they are widely adopted by traders.
References
Connors, L., & Alvarez, C. (2009). Short-Term Trading Strategies That Work. TradingMarkets Publishing Group.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705-1770.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research
Kalman PSaR [BackQuant]Kalman PSaR
Overview and Innovation
The Kalman PSaR combines the well-known Parabolic SAR (PSaR) with the advanced smoothing capabilities of the Kalman Filter . This innovative tool aims to enhance the traditional PSaR by integrating Kalman filtering, which reduces noise and improves trend detection. The Kalman PSaR adapts dynamically to price movements, making it a highly effective indicator for spotting trend shifts while minimizing the impact of false signals caused by market volatility.
Please Find the Basic Kalman Here:
Kalman Filter Dynamics
The Kalman Filter is a powerful algorithm for estimating the true value of a system amidst noisy data. In the Kalman PSaR, this filter is applied to the high, low, and closing prices, resulting in a smoother and more accurate representation of price action. The filterās parametersāprocess noise and measurement noiseāare customizable, allowing traders to fine-tune the sensitivity of the indicator to market conditions. By reducing the impact of noise, the Kalman-filtered PSaR offers clearer signals for identifying trend reversals and continuations.
Enhanced PSaR Calculation
The traditional Parabolic SAR is a popular trend-following indicator that highlights potential entry and exit points based on price acceleration. In the Kalman PSaR, this calculation is enhanced by the Kalman-filtered prices, providing a smoother and more reliable signal. The indicator continuously updates based on the acceleration factor and max step values, while the Kalman filter ensures that sudden price spikes or market noise do not trigger false signals.
Min Step and Max Step: These settings control the sensitivity of the PSaR. The Min Step sets the initial acceleration factor, while the Max Step limits how fast the PSaR adapts to price changes, helping traders fine-tune the indicatorās responsiveness.
Optional Smoothing Techniques To further enhance the signal clarity, the Kalman PSaR includes an optional smoothing feature. Traders can choose from various smoothing methods, such as SMA, Hull, EMA, WMA, TEMA, and more, to reduce short-term fluctuations and emphasize the underlying trend. The smoothing period is customizable, allowing traders to adjust the indicatorās behavior according to their preferred trading style and timeframe.
Color-Coded Candle Painting The Kalman PSaR features color-coded candles that change according to the trend direction. When the price is above the PSaR, candles are painted green to indicate a long trend, and when the price is below the PSaR, candles are painted red to signal a short trend. This visual representation makes it easy to interpret market sentiment at a glance, improving decision-making speed during fast-moving markets.
Key Features and Customization
Kalman Filter Customization: The process noise and measurement noise parameters allow traders to adjust how aggressively the filter adapts to price changes, making it suitable for both volatile and stable markets.
Smoothing Options: A variety of moving average types, such as SMA, Hull, EMA, and more, can be applied to smooth the PSaR values, ensuring that the signal remains clear even in choppy markets.
Dynamic Trend Detection: The Kalman PSaR dynamically updates based on price movements, helping traders spot trend reversals early while filtering out false signals caused by short-term volatility.
Bar Coloring and PSaR Plotting: Traders can choose to color candles based on trend direction or plot the PSaR directly on the chart for additional visual clarity.
Practical Applications
Trend-Following Strategies: The Kalman PSaR excels in trend-following strategies by providing timely signals of trend changes. The dynamic nature of the indicator allows traders to capture significant price movements while avoiding market noise.
Reversal Identification: The indicatorās ability to filter out noise and provide smoother signals makes it ideal for identifying reversals in volatile markets.
Risk Management: By plotting clear stop levels based on the PSaR, traders can use this indicator to effectively manage risk, placing stop-loss orders at key points based on the trend direction.
Conclusion
The Kalman PSaR is a fusion of the classic Parabolic SAR and the Kalman filter, offering enhanced trend detection with reduced noise. Its customizable filtering and smoothing options, combined with dynamic trend-following capabilities, make it a versatile tool for traders seeking to improve their timing and signal accuracy. The adaptive nature of the Kalman filter, combined with the robust PSaR logic, helps traders stay on the right side of the market and manage risk more effectively.
Trend/with EMA382Introduction to the "Trend/with EMA382" Indicator
The "Trend/with EMA382" indicator is a powerful technical analysis tool that combines trend signals with Exponential Moving Averages (EMA), offering traders a comprehensive view of market dynamics and helping identify potential trading opportunities.
1. Trend Analysis with Trend
The first part of this indicator uses a trend calculation algorithm based on the recent market highs and lows. These levels are used to determine the primary trend:
Bullish (Uptrend): When the market is in an uptrend, the chart will display buy signals in green.
Bearish (Downtrend): When the market is trending down, sell signals are shown in red.
The crossover points between price and trend levels will indicate buy or sell signals on the chart, enabling traders to easily spot entry and exit points.
2. Combination with EMA382
EMA (Exponential Moving Average) is a crucial tool in technical analysis, helping smooth price data and eliminate insignificant short-term fluctuations. This indicator uses three key EMAs:
EMA 34: Reflects short-term trends.
EMA 89: Helps identify medium-term trends.
EMA 200: Determines long-term trends.
These three EMAs assist traders in identifying the overall direction of the market, allowing them to forecast potential trend developments.
3. Application in Trading
The "Trend/with EMA382" indicator is designed to suit various time frames, from short-term to long-term trading. The combination of trend signals and EMAs helps:
Identify the primary market trend.
Provide accurate entry and exit signals.
Deliver clear signals for risk management and profit optimization.
Conclusion
"Trend/with EMA382" is an effective indicator that offers clear signals for both trend and market momentum. By combining EMAs with trend analysis, this indicator empowers traders to make more informed and precise trading decisions.
Grid Bot Parabolic [xxattaxx]š© The Grid Bot Parabolic, a continuation of the Grid Bot Simulator Series , enhances traditional gridbot theory by employing a dynamic parabolic curve to visualize potential support and resistance levels. This adaptability is particularly useful in volatile or trending markets, enabling traders to explore grid-based strategies and gain deeper market insights. The grids are divided into customizable trade zones that trigger signals as prices move into new zones, empowering traders to gain deeper insights into market dynamics and potential turning points.
While traditional grid bots excel in ranging markets, the Grid Bot Parabolicās introduction of acceleration and curvature adds new dimensions, enabling its use in trending markets as well. It can function as a traditional grid bot with horizontal lines, a tilted grid bot with linear slopes, or a fully parabolic grid with curves. This dynamic nature allows the indicator to adapt to various market conditions, providing traders with a versatile tool for visualizing dynamic support and resistance levels.
š KEY FEATURES š
Adaptable Grid Structures (Horizontal, Linear, Curved)
Buy and Sell Signals with Multiple Trigger/Confirmation Conditions
Secondary Buy and Secondary Sell Signals
Projected Grid Lines
Customizable Grid Spacing and Zones
Acceleration and Curvature Control
Sensitivity Adjustments
š GRID STRUCTURES š
Beyond its core parabolic functionality, the Parabolic Grid Bot offers a range of grid configurations to suit different market conditions and trading preferences. By adjusting the "Acceleration" and "Curvature" parameters, you can transform the grid's structure:
Parabolic Grids
Setting both acceleration and curvature to non-zero values results in a parabolic grid.This configuration can be particularly useful for visualizing potential turning points and trend reversals. Example: Accel = 10, Curve = -10)
Linear Grids
With a non-zero acceleration and zero curvature, the grid tilts to represent a linear trend, aiding in identifying potential support and resistance levels during trending phases. Example: Accel =1.75, Curve = 0
Horizontal Grids
When both acceleration and curvature are set to zero, the indicator reverts to a traditional grid bot with horizontal lines, suitable for ranging markets. Example: Accel=0, Curve=0
āļø INITIAL SETUP āļø
1.Adding the Indicator to Your Chart
Locate a Starting Point: To begin, visually identify a price point on your chart where you want the grid to start.This point will anchor your grid.
2. Setting Up the Grid
Add the Grid Bot Parabolic Indicator to your chart. A āStart Time/Priceā dialog will appear
CLICK on the chart at your chosen start point. This will anchor the start point and open a "Confirm Inputs" dialog box.
3. Configure Settings. In the dialog box, you can set the following:
Acceleration: Adjust how quickly the grid reacts to price changes.
Curve: Define the shape of the parabola.
Intervals: Determine the distance between grid levels.
If you choose to keep the default settings, with acceleration set to 0 and curve set to 0, the grid will display as traditional horizontal lines. The grid will align with your selected price point, and you can adjust the settings at any time through the indicatorās settings panel.
āļø CONFIGURATION AND SETTINGS āļø
Grid Settings
Accel (Acceleration): Controls how quickly the price reacts to changes over time.
Curve (Curvature): Defines the overall shape of the parabola.
Intervals (Grid Spacing): Determines the vertical spacing between the grid lines.
Sensitivity: Fine tunes the magnitude of Acceleration and Curve.
Buy Zones & Sell Zones: Define the number of grid levels used for potential buy and sell signals.
* Each zone is represented on the chart with different colors:
* Green: Buy Zones
* Red: Sell Zones
* Yellow: Overlap (Buy and Sell Zones intersect)
* Gray: Neutral areas
Trigger: Chooses which part of the candlestick is used to trigger a signal.
* `Wick`: Uses the high or low of the candlestick
* `Close`: Uses the closing price of the candlestick
* `Midpoint`: Uses the middle point between the high and low of the candlestick
* `SWMA`: Uses the Symmetrical Weighted Moving Average
Confirm: Specifies how a signal is confirmed.
* `Reverse`: The signal is confirmed if the price moves in the opposite direction of the initial trigger
* `Touch`: The signal is confirmed when the price touches the specified level or zone
Sentiment: Determines the market sentiment, which can influence signal generation.
* `Slope`: Sentiment is based on the direction of the curve, reflecting the current trend
* `Long`: Sentiment is bullish, favoring buy signals
* `Short`: Sentiment is bearish, favoring sell signals
* `Neutral`: Sentiment is neutral. No secondary signals will be generated
Show Signals: Toggles the display of buy and sell signals on the chart
Chart Settings
Grid Colors: These colors define the visual appearance of the grid lines
Projected: These colors define the visual appearance of the projected lines
Parabola/SWMA: Adjust colors as needed. These are disabled by default.
Time/Price
Start Time & Start Price: These set the starting point for the parabolic curve.
* These fields are automatically populated when you add the indicator to the chart and click on an initial location
* These can be adjusted manually in the settings panel, but he easiest way to change these is by directly interacting with the start point on the chart
Please note: Time and Price must be adjusted for each chart when switching assets. For example, a Start Price on BTCUSD of $60,000 will not work on an ETHUSD chart.
š¤ ALGORITHM AND CALCULATION š¤
The Parabolic Function
At the core of the Parabolic Grid Bot lies the parabolic function, which calculates a dynamic curve that adapts to price action over time. This curve serves as the foundation for visualizing potential support and resistance levels.
The shape and behavior of the parabola are influenced by three key user-defined parameters:
Acceleration: This parameter controls the rate of change of the curve's slope, influencing its tilt or steepness. A higher acceleration value results in a more pronounced tilt, while a lower value leads to a gentler slope. This applies to both curved and linear grid configurations.
Curvature: This parameter introduces and controls the curvature or bend of the grid. A higher curvature value results in a more pronounced parabolic shape, while a lower value leads to a flatter curve or even a straight line (when set to zero).
Sensitivity: This setting fine-tunes the overall responsiveness of the grid, influencing how strongly the Acceleration and Curvature parameters affect its shape. Increasing sensitivity amplifies the impact of these parameters, making the grid more adaptable to price changes but potentially leading to more frequent adjustments. Decreasing sensitivity reduces their impact, resulting in a more stable grid structure with fewer adjustments. It may be necessary to adjust Sensitivity when switching between different assets or timeframes to ensure optimal scaling and responsiveness.
The parabolic function combines these parameters to generate a curve that visually represents the potential path of price movement. By understanding how these inputs influence the parabola's shape and behavior, traders can gain valuable insights into potential support and resistance areas, aiding in their decision-making process.
Sentiment
The Parabolic Grid Bot incorporates sentiment to enhance signal generation. The "Sentiment" input allows you to either:
Manually specify the market sentiment: Choose between 'Long' (bullish), 'Short' (bearish), or 'Neutral'.
Let the script determine sentiment based on the slope of the parabolic curve: If 'Slope' is selected, the sentiment will be considered 'Long' when the curve is sloping upwards, 'Short' when it's sloping downwards, and 'Neutral' when it's flat.
Buy and Sell Signals
The Parabolic Grid Bot generates buy and sell signals based on the interaction between the price and the grid levels.
Trigger: The "Trigger" input determines which part of the candlestick is used to trigger a signal (wick, close, midpoint, or SWMA).
Confirmation: The "Confirm" input specifies how a signal is confirmed ('Reverse' or 'Touch').
Zones: The number of "Buy Zones" and "Sell Zones" determines the areas on the grid where buy and sell signals can be generated.
When the trigger condition is met within a buy zone and the confirmation criteria are satisfied, a buy signal is generated. Similarly, a sell signal is generated when the trigger and confirmation occur within a sell zone.
Secondary Signals
Secondary signals are generated when a regular buy or sell signal contradicts the prevailing sentiment. For example:
A buy signal in a bearish market (Sentiment = 'Short') would be considered a "secondary buy" signal.
A sell signal in a bullish market (Sentiment = 'Long') would be considered a "secondary sell" signal.
These secondary signals are visually represented on the chart using hollow triangles, differentiating them from regular signals (filled triangles).
While they can be interpreted as potential contrarian trade opportunities, secondary signals can also serve other purposes within a grid trading strategy:
Exit Signals: A secondary signal can suggest a potential shift in market sentiment or a weakening trend. This could be a cue to consider exiting an existing position, even if it's currently profitable, to lock in gains before a potential reversal
Risk Management: In a strong trend, secondary signals might offer opportunities for cautious counter-trend trades with controlled risk. These trades could utilize smaller position sizes or tighter stop-losses to manage potential downside if the main trend continues
Dollar-Cost Averaging (DCA): During a prolonged trend, the parabolic curve might generate multiple secondary signals in the opposite direction. These signals could be used to implement a DCA strategy, gradually accumulating a position at potentially favorable prices as the market retraces or consolidates within the larger trend
Secondary signals should be interpreted with caution and considered in conjunction with other technical indicators and market context. They provide additional insights into potential market reversals or consolidation phases within a broader trend, aiding in adapting your grid trading strategy to the evolving market dynamics.
Examples
Trigger=Wick, Confirm=Touch. Signals are generated when the wick touches the next gridline.
Trigger=Close, Confirm=Touch. Signals require the close to touch the next gridline.
Trigger=SWMA, Confirm=Reverse. Signals are triggered when the Symmetrically Weighted Moving Average reverse crosses the next gridline.
š§ THEORY AND RATIONALE š§
The innovative approach of the Parabolic Grid Bot can be better understood by first examining the limitations of traditional grid trading strategies and exploring how this indicator addresses them by incorporating principles of market cycles and dynamic price behavior
Traditional Grid Bots: One-Dimensional and Static
Traditional grid bots operate on a simple premise: they divide the price chart into a series of equally spaced horizontal lines, creating a grid of trading zones. These bots excel in ranging markets where prices oscillate within a defined range. Buy and sell orders are placed at these grid levels, aiming to profit from mean reversion as prices bounce between the support and resistance zones.
However, traditional grid bots face challenges in trending markets. As the market moves in one direction, the bot continues to place orders in that direction, leading to a stacking of positions. If the market eventually reverses, these stacked trades can be profitable, amplifying gains. But the risk lies in the potential for the market to continue trending, leaving the trader with a series of losing trades on the wrong side of the market
The Parabolic Grid Bot: Adding Dimensions
The Parabolic Grid Bot addresses the limitations of traditional grid bots by introducing two additional dimensions:
Acceleration (Second Dimension): This parameter introduces a second dimension to the grid, allowing it to tilt upwards or downwards to align with the prevailing market trend. A positive acceleration creates an upward-sloping grid, suitable for uptrends, while a negative acceleration results in a downward-sloping grid, ideal for downtrends. The magnitude of acceleration controls the steepness of the tilt, enabling you to fine-tune the grid's responsiveness to the trend's strength
Curvature (Third Dimension): This parameter adds a third dimension to the grid by introducing a parabolic curve. The curve's shape, ranging from gentle bends to sharp turns, is controlled by the curvature value. This flexibility allows the grid to closely mirror the market's evolving structure, potentially identifying turning points and trend reversals.
Mean Reversion in Trending Markets
Even in trending markets, the Parabolic Grid Bot can help identify opportunities for mean reversion strategies. While the grid may be tilted to reflect the trend, the buy and sell zones can capture short-term price oscillations or consolidations within the broader trend. This allows traders to potentially pinpoint entry and exit points based on temporary pullbacks or reversals.
Visualize and Adapt
The Parabolic Grid Bot acts as a visual aid, enhancing your understanding of market dynamics. It allows you to "see the curve" by adapting the grid to the market's patterns. If the market shows a parabolic shape, like an upward curve followed by a peak and a downward turn (similar to a head and shoulders pattern), adjust the Accel and Curve to match. This highlights potential areas of interest for further analysis.
Beyond Straight Lines: Visualizing Market Cycle
Traditional technical analysis often employs straight lines, such as trend lines and support/resistance levels, to interpret market movements. However, many analysts, including Brian Millard, contend that these lines can be misleading. They propose that what might appear as a straight line could represent just a small part of a larger curve or cycle that's not fully visible on the chart.
Markets are inherently cyclical, marked by phases of expansion, contraction, and reversal. The Parabolic Grid Bot acknowledges this cyclical behavior by offering a dynamic, curved grid that adapts to these shifts. This approach helps traders move beyond the limitations of straight lines and visualize potential support and resistance levels in a way that better reflects the market's true nature
By capturing these cyclical patterns, whether subtle or pronounced, the Parabolic Grid Bot offers a nuanced understanding of market dynamics, potentially leading to more accurate interpretations of price action and informed trading decisions.
ā ļø DISCLAIMERā ļø
This indicator utilizes a parabolic curve fitting approach to visualize potential support and resistance levels. The mathematical formulas employed have been designed with adaptability and scalability in mind, aiming to accommodate various assets and price ranges. While the resulting curves may visually resemble parabolas, it's important to note that they might not strictly adhere to the precise mathematical definition of a parabola.
The indicator's calculations have been tested and generally produce reliable results. However, no guarantees are made regarding their absolute mathematical accuracy. Traders are encouraged to use this tool as part of their broader analysis and decision-making process, combining it with other technical indicators and market context.
Please remember that trading involves inherent risks, and past performance is not indicative of future results. It is always advisable to conduct your own research and exercise prudent risk management before making any trading decisions.
š§ BEYOND THE CODE š§
The Parabolic Grid Bot, like the other grid bots in this series, is designed with education and community collaboration in mind. Its open-source nature encourages exploration, experimentation, and the development of new grid trading strategies. We hope this indicator serves as a framework and a starting point for future innovations in the field of grid trading.
Your comments, suggestions, and discussions are invaluable in shaping the future of this project. We welcome your feedback and look forward to seeing how you utilize and enhance the Parabolic Grid Bot.
Enhanced Local Polynomial Regression [Yosiet]Local Polynomial Regression (LPR) is an advanced statistical method that offers a flexible approach to estimating the underlying trend in financial time series data.
The Mathematical Explanation
The core idea of LPR is to fit a polynomial of degree p at each point x using weighted least squares. The weight of each data point decreases with its distance from x, controlled by a kernel function and a bandwidth parameter.
The general form of the local polynomial estimator is:
Ī²Ģ(x) = argmin Ī£ K((Xi - x) / h) (Yi - Ī²0 - Ī²1(Xi - x) - ... - Ī²p(Xi - x)^p)^2
Where:
Ī²Ģ(x) is the vector of estimated coefficients
K is the kernel function
h is the bandwidth
Xi and Yi are the predictor and response variables
p is the degree of the polynomial
Our implementation uses the Epanechnikov kernel:
K(u) = 3/4 * (1 - u^2) for |u| ā¤ 1, 0 otherwise
The Implementation
This script implements LPR for the easier way to interpret its values with the following key components:
Input Parameters: Can adjust the lookback period, bandwidth, and polynomial degree.
Kernel Function: The Epanechnikov kernel is used for weighting.
LPR Function: Implements the core algorithm using matrix operations.
Signal Generation: Generates buy/sell signals based on crossovers of smoothed price and LPR results.
How to Use
Apply the indicator to your chart in TradingView.
Adjust the input parameters:
Lookback Period: Controls how many past bars are considered.
Bandwidth: Affects the smoothness of the regression line.
Polynomial Degree: Determines the complexity of the local fit.
Signal Smoothing Length: Adjusts the responsiveness of buy/sell signals.
Monitor buy/sell signals for potential trade entries.
Limitations
Sensitivity to Parameters: The choice of bandwidth and polynomial degree significantly impacts the results.
Lag: Like all trend-following indicators, LPR may lag behind rapid price movements.
Edge Effects: The indicator may be less reliable at the edges of the data (recent bars).
Recommendations
Parameter Optimization: Experiment with different lookback periods, bandwidths, and polynomial degrees to find the best fit for your trading style and timeframe.
Combine with Other Indicators: Use LPR in conjunction with momentum oscillators or volume indicators for confirmation.
Multiple Timeframes: Apply LPR on different timeframes to gain a more comprehensive view of the trend.
Avoid Overfitting: Be cautious of using high polynomial degrees, as they may lead to overfitting on historical data.
Consider Market Conditions: LPR works best in trending markets; be aware of its limitations in ranging or highly volatile conditions.
Backtest Thoroughly: Always backtest strategies based on LPR across different market conditions before live trading.
Conclusion
Local Polynomial Regression offers a sophisticated approach to trend analysis in financial markets. By providing a flexible, adaptive trend line, it can help traders identify potential entry and exit points with greater precision than traditional moving averages. However, like all technical indicators, it should be used as part of a comprehensive trading strategy that includes proper risk management and consideration of fundamental factors.
if you have an strategy or idea and need to make it real through an indicator or trading bot, you can DM or comment
Unicorn ICT Signals [TradingFinder] Breaker Block + FVG Zonesšµ Introduction
The "ICT Unicorn Model" trading strategy in the "Inner Circle Trader" (ICT) style is one of the well-known strategies in the world of Forex and financial market trading.
The ICT methodology was developed by Michael Huddleston and is based on technical analysis and Price Action concepts.
This style focuses specifically on interpreting price movements and identifying optimal entry and exit points in the market.
In the Unicorn strategy, traders seek points where the probability of price reversal or trend continuation is high. This strategy is primarily based on recognizing and analyzing Price Action patterns and market structure.
By understanding"ICT Unicorn Model", traders can make more informed decisions about where to enter or exit trades, thereby increasing their chances of success in the market.
š£ Understanding the Breaker Block
A Breaker Block is a specialized form of an Order Block that changes its role after a key market level is broken. Typically, an Order Block is an area on the chart where large institutional orders are likely to be placed, providing strong support or resistance.
However, when this area is breached, and the price moves in the opposite direction, it transforms into what is known as a Breaker Block. This shift indicates a reversal in market sentiment, turning the previous support into resistance or vice versa, thereby signaling a potential trend change to traders.
š£ The Significance of the Fair Value Gap (FVG)
The Fair Value Gap (FVG) refers to an area on a price chart where the price rapidly moves through a level, leaving behind a gap. This gap represents an imbalance between supply and demand and is often seen as a potential area for price to return and fill the gap.
These zones are crucial for traders as they can indicate future price movements, providing opportunities to enter or exit trades.
š£ Defining the ICT Unicorn Model
When an FVG overlaps with a Breaker Block, it forms a highly significant trading area known as a Unicorn. This overlap creates an ideal zone for traders to enter the market, as it combines two powerful technical signals.
The Unicorn Model is therefore considered an optimal strategy for identifying precise entry and exit points in the financial markets.
Demand ICT Unicorn Model :
Supply ICT Unicorn Model :
šµ How to Use
š£ Bullish ICT Unicorn
The Bullish ICT Unicorn model is applicable when the market is in an uptrend, and traders are seeking buying opportunities.
Follow these steps to identify Bullish ICT Unicorn :
Identify the Bullish Breaker Block : Locate an area where the price moved upward after breaking an Order Block. This area now acts as a Breaker Block.
Identify the Bullish FVG : Look for a Fair Value Gap near the Breaker Block.
Confirm the Unicorn : When the Bullish Breaker Block and Bullish FVG overlap, a Bullish Unicorn is confirmed. Traders can enter a buy position when the price returns to this zone.
š£Bearish ICT Unicorn
The Bearish ICT Unicorn model is used when the market is in a downtrend, and traders are looking for selling opportunities.
To identify Bearish ICT Unicorn, follow these steps :
Identify the Bearish Breaker Block : Find an area where the price moved downward after breaking an Order Block. This area now acts as a Breaker Block.
Identify the Bearish FVG : Check if a Fair Value Gap has formed near the Breaker Block.
Confirm the Unicorn : When the Bearish Breaker Block and Bearish FVG overlap, a Bearish Unicorn is confirmed. Traders can enter a sell position when the price returns to this zone.
šµ Setting
š£ Global Setting
Pivot Period of Order Blocks Detector : Enter the desired pivot period to identify the Order Block.
Order Block Validity Period (Bar) : You can specify the maximum time the Order Block remains valid based on the number of candles from the origin.
Mitigation Level Breaker Block : Determining the basic level of a Breaker Block. When the price hits the basic level, the Breaker Block due to mitigation.
Mitigation Level FVG : Determining the basic level of a FVG. When the price hits the basic level, the FVG due to mitigation.
Mitigation Level Unicorn : Determining the basic level of a Unicorn Block. When the price hits the basic level, the Unicorn Block due to mitigation.
š£ Unicorn Block Display
Show All Unicorn Block : If it is turned off, only the last Order Block will be displayed.
Demand Unicorn Block : Show or not show and specify color.
Supply Unicorn Block : Show or not show and specify color.
š£ Breaker Block Display
Show All Breaker Block : If it is turned off, only the last Breaker Block will be displayed.
Demand Main Breaker Block : Show or not show and specify color.
Demand Sub (Propulsion & BoS Origin) Breaker Block : Show or not show and specify color.
Supply Main Breaker Block : Show or not show and specify color.
Supply Sub (Propulsion & BoS Origin) Breaker Block : Show or not show and specify color.
š£ Fair Value Gap Display
Show Bullish FVG : Toggles the display of demand-related boxes.
Show Bearish FVG : Toggles the display of supply-related boxes.
š£ Logic Settings
š£ Order Block Refinement
Refine Order Blocks : Enable or disable the refinement feature. Mode selection.
š£ FVG Filter
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filters :
Very Aggressive Filter: Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter: Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter: Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filter: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
š£ Alert
Alert Name : The name of the alert you receive.
Alert ICT Unicorn Model Block Mitigation :
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.
šµConclusion
The Unicorn Model in ICT, utilizing the concepts of Breaker Blocks and Fair Value Gaps, provides an effective tool for identifying entry and exit points in financial markets. By offering more precise signals, this model helps traders make better decisions and minimize trading risks.
Success in applying this model requires practice and a deep understanding of market structure, but it can significantly improve trading performance.
Time Zone CorrectorThe Time Zone Corrector library provides a utility function designed to adjust time based on the user's current time zone. This library supports a wide range of time zones across the Americas, Europe, Asia, and Oceania, making it highly versatile for traders around the world. It simulates a switch-case structure using ternary operators to output the appropriate time offset relative to UTC.
Whether you're dealing with market sessions in New York, Tokyo, London, or other major trading hubs, this library helps ensure your trading algorithms can accurately account for time differences. The library is particularly useful for strategies that rely on precise timing, as it dynamically adjusts the time zone offset depending on the symbol being traded.
Price & Volume Breakout Fibonacci Probability [TradeDots]š OVERVIEW
The "Price & Volume Breakout Fibonacci Probability" indicator is designed to detect the probability of the maximum run-up and drawdown of each breakout trade on an asset, assisting traders in optimizing their take profit and stop loss strategies.
š§® CALCULATIONS
The algorithm detects price and volume breakouts to activate the Fibonacci levels displayed on the chart. It calculates these levels using the period pivot high and low, with the close price of the breakout bar as the reference price.
The indicator then forward-tests within an user-selected number of bars, detecting the maximum run-up and drawdown during that period. Consequently, it calculates the probability of the price hitting either side of the Fibonacci levels, showing the likelihood of reaching take profit and stop loss targets for each breakout trade.
š EXAMPLE
The above example shows two breakout trades, circled within the yellow rectangle zone.
The first trade has a maximum run-up above the +0.382 Fibonacci level zone and a maximum drawdown below the -0.618 Fibonacci level zone.
When the price reaches the maximum run-up, it only has a ~45% probability of moving further upward into the last two zones (25% + 19.44%). This indicates that setting a take profit at a higher level may have less than a 50% chance of success.
Conversely, when the price reaches its maximum drawdown, there is only an ~8% probability of moving further downward into the last drawdown zone. This could indicate a potential reversal.
āļø SETTINGS
Breakout Condition: Determines the type of breakout condition to track: "Price", "Volume", "Price & Volume".
Backtest Period: The maximum run-up and drawdown are detected within this bar period.
Price Breakout Period: Specifies the number of bars the price needs to break out from.
Volume Breakout Period: Specifies the number of bars the volume needs to break out from.
Trendline Confirmation: Confirms that the close price needs to be above the trendline.
š HOW TO USE
By understanding the probabilities of price movements to both the upside and downside, traders can set take profit and stop loss targets with greater accuracy.
For instance, placing a stop loss order below the zone with the highest probability minimizes the chances of being stopped out of a profitable trade. Conversely, setting a take profit target at the zone with the highest probability increases the win rate.
Additionally, if the price breaches multiple Fibonacci levels during the breakout period, it may indicate an abnormal state, signaling a potential reversal or pullback. This can help traders exit trades in a timely manner.
Traders can adjust their take profit and stop loss levels based on their individual risk tolerance.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Uptrick: Adaptive Cloud Oscillator (ACO)### **Uptrick: Adaptive Cloud Oscillator (ACO)**
---
### Introduction
The **Uptrick: Adaptive Cloud Oscillator (ACO)** is an advanced technical analysis tool designed to empower traders with precise trend detection and visual clarity in dynamic market conditions. By seamlessly integrating adaptive trend analysis, volatility filtering, and cloud-based support and resistance levels, the ACO provides traders with the actionable insights needed to navigate complex markets with confidence.
This indicator is highly customizable, allowing traders to tailor its functionality to their specific trading style and preferences. Whether you're a trend follower, swing trader, or looking to identify key support and resistance zones, the **Uptrick: ACO** is an indispensable tool that can adapt to a variety of market conditions.
### Indicator Purpose and Functionality
#### 1. **Adaptive Trend Detection**
At the heart of the **Uptrick: ACO** lies its adaptive trend detection algorithm. Unlike traditional moving averages that may lag in volatile markets or react too slowly to rapid changes, this adaptive method uses a smoothing technique that dynamically adjusts based on market conditions. By doing so, it provides a more responsive trend line that captures meaningful price movements while filtering out minor fluctuations.
- **How It Works:** The trend line is calculated using an adaptive smoothing factor, making it responsive to recent price actions while maintaining a level of stability that prevents whipsaw signals. This ensures that traders are always in tune with the prevailing market trend, whether bullish, bearish, or neutral.
#### 2. **Dynamic Cloud Support and Resistance**
The **Uptrick: ACO** features a dynamic "cloud" that serves as a key element in its analysis. This cloud is constructed using a moving average combined with the Average True Range (ATR), which adjusts based on the marketās volatility. The cloud provides dynamic support and resistance levels, essential for identifying potential reversal zones or confirming trend continuations.
- **Cloud Displacement:** The cloud is displaced forward by a user-defined number of bars, offering a predictive view of where future support and resistance levels may lie. This forward-looking feature helps traders anticipate potential price movements, making the ACO a powerful tool for planning trades ahead of time.
#### 3. **Versatile Visualization Options**
The **Uptrick: ACO** is designed with flexibility in mind, allowing users to choose between two distinct display modes:
- **Buy/Sell Signals:** In this mode, the indicator generates clear buy and sell signals based on crossovers of the trend line and the cloud boundaries. These signals are visualized directly on the chart with up and down labels, making it easy for traders to identify potential entry and exit points.
- **Cloud Fill Only:** For traders who prefer a cleaner chart, this mode removes the buy/sell signals and instead focuses on coloring the area between the upper and lower cloud boundaries. The color of the cloud fill changes based on the trend direction, providing a visual representation of the market's momentum.
- **Optional EMA Line:** An Exponential Moving Average (EMA) line can be optionally displayed on the chart. The EMA serves as an additional trend filter, helping traders further refine their entries and exits. The length, color, and thickness of the EMA are fully customizable to fit individual trading strategies.
### Practical Applications
#### 1. **Trend Following and Reversals**
The **Uptrick: ACO** excels in identifying and following trends. By analyzing the relationship between the trend line and the cloud, traders can determine the strength and direction of the current market trend. The cloudās dynamic nature means it can adapt to both trending and ranging markets, providing consistent insights regardless of market conditions.
- **Example:** If the trend line crosses above the upper cloud boundary, it signals a potential buy opportunity. Conversely, a cross below the lower cloud boundary suggests a sell opportunity. Traders can use these signals to enter trades aligned with the prevailing trend.
#### 2. **Support and Resistance Identification**
The forward-displaced cloud acts as a predictive support and resistance zone. Traders can use these zones to set stop-loss levels, determine take-profit targets, or identify potential reversal points.
- **Example:** When the price approaches the upper cloud boundary from below, the boundary may act as resistance, indicating a potential reversal or pullback. If the price breaks through this level, it may signal a continuation of the bullish trend.
#### 3. **Volatility-Based Analysis**
By incorporating ATR into its calculations, the **Uptrick: ACO** provides a built-in mechanism to adapt to varying levels of market volatility. This makes it particularly useful in markets prone to sudden spikes in volatility, such as during major economic announcements or geopolitical events.
- **Example:** In a high-volatility environment, the cloud widens, allowing for greater price fluctuations within the trend. Traders can use this information to adjust their risk management strategies, such as widening stop-loss levels during volatile periods to avoid being stopped out prematurely.
### Customization and Flexibility
The **Uptrick: ACO** is designed to be highly customizable, ensuring it can meet the needs of traders with different strategies and preferences. Key customization options include:
- **Cloud and Trend Settings:** Traders can adjust the length of the cloud, the smoothing factor for the trend line, and the displacement of the cloud to optimize the indicator for their specific market and timeframe.
- **Display Modes:** With a simple dropdown selection, traders can choose whether to display buy/sell signals or focus solely on the cloud fill, providing flexibility in how the indicator is visualized.
- **Color and Style Customization:** The colors for bullish and bearish trends, cloud fill, buy/sell signals, and the EMA line can all be customized, allowing traders to integrate the **Uptrick: ACO** seamlessly into their existing chart setups.
### Conclusion
The **Uptrick: Adaptive Cloud Oscillator (ACO)** is more than just a trend indicatorāit's a comprehensive market analysis tool that provides traders with a deep understanding of market dynamics. Its combination of adaptive trend analysis, dynamic support and resistance levels, and versatile visualization options makes it an essential tool for traders looking to gain an edge in any market environment.
Whether you're a seasoned trader or just starting, the **Uptrick: ACO** offers the insights and flexibility needed to make informed trading decisions. By helping you identify trends, anticipate reversals, and adapt to changing market conditions, the **Uptrick: ACO** can significantly enhance your trading strategy and improve your overall trading performance.
Gann + Laplace Smoothed Hybrid Volume Spread Analysis Indicator
This Indicator stands apart by integrating the principles of the upgraded Discrete Fourier Transform (DFT), the Laplace Stieltjes Transform and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
The length of EMA and Strategy Entries are modified with the Gann swings.
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the GannLSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
WHAT IS GannLSHVSA INDICATOR:
The GannLSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
ORIGINALITY & USEFULNESS:
The GannLSHVSA Strategy is unique because it applies upgraded DFT, the Laplace Stieltjes Transform for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions. The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread?
It results in a neutral, not trending price action.
Thus the Indicator/Strategy returns 0 and Closes all long and short positions.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
6 days ago
Release Notes
[1] Dynamic Support and Resistance with breakout [Dr Future]This script appears to be designed to identify and visualize dynamic support and resistance levels on a price chart, along with potential breakout signals.
Key Components & Functionality (Inferred):
Dynamic Support and Resistance: The script likely employs algorithms to calculate and plot support and resistance levels that adjust in real-time as price action evolves.
Breakout Detection: The script probably incorporates logic to recognize when the price breaks out of these dynamic support or resistance zones. This could trigger alerts or visual cues on the chart.
Dr Future's Approach: It's worth noting the " " tag, suggesting the script might be based on specific methodologies or insights associated with a trader or analyst known as "Dr Future." Without more context on their strategies, it's difficult to pinpoint the exact techniques used.
Potential Benefits:
Adaptive Levels: Dynamic support and resistance can offer a more responsive approach compared to static levels, as they account for changing market conditions.
Breakout Opportunities: Identifying breakouts can help traders spot potential entry or exit points.
Visual Clarity: Plotting these levels directly on the chart can provide a clearer picture of the current market structure and potential turning points.
Caveats:
False Signals: Like any technical tool, dynamic support and resistance can generate false signals. Breakouts might not always lead to sustained trends.
Parameter Sensitivity: The script's effectiveness likely depends on how its parameters are configured. Fine-tuning might be required to suit different markets or timeframes.
"Dr Future" Factor: The script's performance could be tied to the specific strategies of "Dr Future," which might not be universally applicable.
Important Note:
Without access to the actual code and a deeper understanding of "Dr Future's" methods, this description is based on inference and general knowledge of technical analysis.
Recommendation:
If you're considering using this script, it would be prudent to:
Backtest Thoroughly: Test the script on historical data to assess its performance and identify potential pitfalls.
Understand the Parameters: Familiarize yourself with the script's settings and how they impact the plotted levels and breakout signals.
Combine with Other Tools: Use this script in conjunction with other technical indicators and risk management strategies for a more holistic trading approach.
Trendlines (long)Hi all!
I hope that this indicator helps you to be a more efficient trader. The concept is well known and useful. So this is not some magic algorithm founded by me, but rather a well known concept. The concept is the drawing of trendlines.
It draws trendlines that has a retest. It draws the trendlines in different colors, the colors used are blue, red, fuchsia and lime.
These are the steps for finding a trendline:
1. Find a generic retest
Find a low that has 2 earlier lows and 1 later low that are higher. This is the reason that a trendline will be created "1 bar late". This is the base and the indicator goes on from here, meaning that this needs to be true to continue.
2. Find an uptrend
Look back 8 bars to find a low that is lower than the retest low.
3. Create the first point of a trendline
Go thru every bar between the user defined "Lookback" and the retest bar (minus the user defined "Skip gap" that's needed between points to create a trendline). From the earliest bar to the latest.
4. Create the second point of the trendline
Go thru every bar between the retest bar and the the first point (bar) minus the "Skip gap". From latest bar to the earliest. A trendline between the two bars are invalidated if some of the criteria are met in-between the bars creating the trendline:
- closed above the trendline (trendline broken)
- is not within the retest bar
- the slope of the trendline is upwards (this indicator is for long entries only)
- at least 1 of the bars creating the retest (1 main bar and 2 earlier bars) has NOT been above the trendline
- is not the created trendline (between the two points) that's closest to the low of the retest bar
TODO:
- add functionality to draw trendlines directly on breakouts
- add volume (high volume needed to create a trendline from a breakout/retest)
- ...?
I hope this explanation makes sense, let me know otherwise. Also let me know if you have any suggestions on improvements.
Best of luck trading!
Approximate Spectral Entropy-Based Market Momentum (SEMM)Overview
The Approximate Spectral Entropy-Based Market Momentum (SEMM) indicator combines the concepts of spectral entropy and traditional momentum to provide traders with insights into both the strength and the complexity of market movements. By measuring the randomness or predictability of price changes, SEMM helps traders understand whether the market is in a trending or consolidating state and how strong that trend or consolidation might be.
Key Features
Entropy Measurement: Calculates the approximate spectral entropy of price movements to quantify market randomness.
Momentum Analysis: Integrates entropy with rate-of-change (ROC) to highlight periods of strong or weak momentum.
Dynamic Market Insight: Provides a dual perspective on market behaviorāboth the trend strength and the underlying complexity.
Customizable Parameters: Adjustable window length for entropy calculation, allowing for fine-tuning to suit different market conditions.
Concepts Underlying the Calculations
The indicator utilizes Shannon entropy, a concept from information theory, to approximate the spectral entropy of price returns. Spectral entropy traditionally involves a Fourier Transform to analyze the frequency components of a signal, but due to Pine Script limitations, this indicator uses a simplified approach. It calculates log returns over a rolling window, normalizes them, and then computes the Shannon entropy. This entropy value represents the level of disorder or complexity in the market, which is then multiplied by traditional momentum measures like the rate of change (ROC).
How It Works
Price Returns Calculation: The indicator first computes the log returns of price data over a specified window length.
Entropy Calculation: These log returns are normalized and used to calculate the Shannon entropy, representing market complexity.
Momentum Integration: The calculated entropy is then multiplied by the rate of change (ROC) of prices to generate the SEMM value.
Signal Generation: High SEMM values indicate strong momentum with higher randomness, while low SEMM values indicate lower momentum with more predictable trends.
How Traders Can Use It
Trend Identification: Use SEMM to identify strong trends or potential trend reversals. Low entropy values can indicate a trending market, whereas high entropy suggests choppy or consolidating conditions.
Market State Analysis: Combine SEMM with other indicators or chart patterns to confirm the market's stateāwhether it's trending, ranging, or transitioning between states.
Risk Management: Consider high SEMM values as a signal to be cautious, as they suggest increased market unpredictability.
Example Usage Instructions
Add the Indicator: Apply the "Approximate Spectral Entropy-Based Market Momentum (SEMM)" indicator to your chart.
Adjust Parameters: Modify the length parameter to suit your trading timeframe. Shorter lengths are more responsive, while longer lengths smooth out the signal.
Analyze the Output: Observe the blue line for entropy and the red line for SEMM. Look for divergences or confirmations with price action to guide your trades.
Combine with Other Tools: Use SEMM alongside moving averages, support/resistance levels, or other indicators to build a comprehensive trading strategy.
ICT Balanced Price Range [TradingFinder] BPR | FVG + IFVGšµ Introduction
The ICT Balanced Price Range (BPR) indicator is a valuable tool that helps traders identify key areas on price charts where a balance between buyers and sellers is established. These zones can serve as critical points for potential price reversals or continuations.
š£ Bullish Balanced Price Range
A Bullish BPR forms when a buying pressure zone (Bullish FVG) overlaps with a Bullish Inversion FVG. This overlap indicates a high probability of price moving upwards, making it a crucial area for traders to consider.
š£ Bearish Balanced Price Range
Similarly, a Bearish BPR is created when a selling pressure zone (Bearish FVG) overlaps with a Bearish Inversion FVG. This zone is often seen as a key area where the price is likely to move downward.
šµ How to Use
š£ Identifying the Balanced Price Range (BPR)
To identify the Balanced Price Range (BPR), you must first locate two Fair Value Gaps (FVGs) on the price chart. One FVG should be on the sell side, and the other on the buy side. When these two FVGs horizontally oppose each other, the area where they overlap is recognized as the Balanced Price Range (BPR).
This BPR zone is highly sensitive to price movements due to the combination of two FVGs, often leading to strong market reactions. As the price approaches this area, the likelihood of a significant market move increases, making it a prime target for professional traders.
š£ Bullish Balanced Price Range (Bullish BPR)
To effectively trade using a Bullish BPR, begin by identifying a bullish market structure and searching for bullish Price Delivery Arrays (PD Arrays). Once the market structure shifts to bullish in a lower time frame, locate a Bullish FVG within the Discount Zone that overlaps with a Bearish FVG.
Mark this overlapping zone and wait for the price to test it before executing a buy trade. Alternatively, you can set a Buy Limit order with a stop loss below the recent swing low and target profits based on higher time frame liquidity draws.
š£ Bearish Balanced Price Range (Bearish BPR)
For bearish trades, start by identifying a bearish market structure and look for bearish PD Arrays. After the market structure shifts to bearish in a lower time frame, identify a Bearish FVG within the Discount Zone that overlaps with a Bullish FVG. Mark this overlapping zone and execute a sell trade when the price tests it.
You can also use a Sell Limit order with a stop loss above the recent swing high and target profits according to higher time frame liquidity draws.
šµ Settings
š£ Global Settings
Show All Inversion FVG & IFVG : If disabled, only the most recent FVG & IFVG will be displayed.
FVG & IFVG Validity Period (Bar) : Determines the maximum duration (in number of candles) that the FVG and IFVG remain valid.
Switching Colors Theme Mode : Includes three modes: "Off", "Light", and "Dark". "Light" mode adjusts colors for light mode use, "Dark" mode adjusts colors for dark mode use, and "Off" disables color adjustments.
š£ Display Settings
Show Bullish BPR : Toggles the display of demand-related boxes.
Show Bearish BPR : Toggles the display of supply-related boxes.
Mitigation Level BPR : Options include "Proximal", "Distal", or "50 % OB" modes, which you can choose based on your needs. The "50 % OB" line is the midpoint between distal and proximal.
Show Bullish IFVG : Toggles the display of demand-related boxes.
Show Bearish IFV G: Toggles the display of supply-related boxes.
Mitigation Level FVG and IFVG : Options include "Proximal", "Distal", or "50 % OB" modes, which you can choose based on your needs. The "50 % OB" line is the midpoint between distal and proximal.
š£ Logic Settings
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filters :
Very Aggressive Filter : Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter : Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter : Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filte r: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
š£ Alert Settings
Alert Inversion FVG Mitigation : Enables alerts for Inversion FVG mitigation.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
Display More Info : Provides additional details in alert messages, including price range, date, hour, and minute. Set to 'Off' to exclude this information.
šµ Conclusion
The ICT Balanced Price Range is a powerful and reliable tool for identifying key points on price charts. This strategy can be applied across various time frames and serves as a complementary tool alongside other indicators and technical analysis methods.
The most crucial aspect of utilizing this strategy effectively is correctly identifying FVGs and their overlapping areas, which comes with practice and experience.
MACD Trail | Flux Chartsš GENERAL OVERVIEW
Introducing our new MACD Trail indicator! Moving average convergence/divergence (MACD) is a well-known indicator among traders. It's a trend-following indicator that uses the relationship between two exponential moving averages (EMAs). This indicator aims to use MACD to generate a trail that follows the current price of the ticker, which can act as a support / resistance zone. More info about the process in the "How Does It Work" section.
Features of the new MACD Trail Indicator :
A Trail Generated Using MACD Calculation
Customizable Algorithm
Customizable Styling
š HOW DOES IT WORK ?
First of all, this indicator calculates the current MACD of the ticker using the user's input as settings. Let X = MACD Length setting ;
MACD ~= X Period EMA - (X * 2) Period EMA
Then, two MACD Trails are generated, one being bullish and other being bearish. Let ATR = 30 period ATR (Average True Range)
Bullish MACD Trail = Current Price + MACD - (ATR * 1.75)
Bearish MACD Trail = Current Price + MACD + (ATR * 1.75)
The indicator starts by rendering only the Bullish MACD Trail. Then if it's invalidated (candlestick closes below the trail) it switches to Bearish MACD Trail. The MACD trail switches between bullish & bearish as they get invalidated.
The trail type may give a hint about the current trend of the price action. The trail itself also can act as a support / resistance zone, here is an example :
š© UNIQUENESS
While MACD is one of the most used indicators among traders, this indicator aims to add another functionality to it by rendering a trail based on it. This trail may act as a support / resistance zone as described above, and gives a glimpse about the current trend. The indicator also has custom MACD Length and smoothing options, as well as various style options.
āļø SETTINGS
1. General Configuration
MACD Length -> This setting adjusts the EMA periods used in MACD calculation. Increasing this setting will make MACD more responseive to longer trends, while decreasing it may help with detection of shorter trends.
Smoothing -> The smoothing of the MACD Trail. Increasing this setting will help smoothen out the MACD Trail line, but it can also make it less responsive to the latest changes.
Zero-lag TEMA Crosses Strategy[Pakun]Here's the adjusted strategy description in English, aligned with the house rules:
---
### Strategy Name: Zero-lag TEMA Cross Strategy
**Purpose:** This strategy aims to identify entry and exit points in the market using Zero-lag Triple Exponential Moving Averages (TEMA). It focuses on minimizing lag and improving the accuracy of trend-following signals.
### Uniqueness and Usefulness
**Uniqueness:** This strategy employs the less commonly used Zero-lag TEMA, compared to standard moving averages. This unique approach reduces lag and provides more timely signals.
**Usefulness:** This strategy is valuable for traders looking to capture trend reversals or continuations with reduced lag. It has the potential to enhance the profitability and accuracy of trades.
### Entry Conditions
**Long Entry:**
- **Condition:** A crossover occurs where the short-term Zero-lag TEMA surpasses the long-term Zero-lag TEMA.
- **Signal:** A buy signal is generated, indicating a potential uptrend.
**Short Entry:**
- **Condition:** A crossunder occurs where the short-term Zero-lag TEMA falls below the long-term Zero-lag TEMA.
- **Signal:** A sell signal is generated, indicating a potential downtrend.
### Exit Conditions
**Exit Strategy:**
- **Stop Loss:** Positions are closed if the price moves against the trade and hits the predefined stop loss level. The stop loss is set based on recent highs/lows.
- **Take Profit:** Positions are closed when the price reaches the profit target. The profit target is calculated as 1.5 times the distance between the entry price and the stop loss level.
### Risk Management
**Risk Management Rules:**
- This strategy incorporates a dynamic stop loss mechanism based on recent highs/lows over a specified period.
- The take profit level ensures a reward-to-risk ratio of 1.5 times the stop loss distance.
- These measures aim to manage risk and protect capital.
**Account Size:** Ā„500,000
**Commissions and Slippage:** 94 pips per trade and 1 pip slippage
**Risk per Trade:** 1% of account equity
### Configurable Options
**Configurable Options:**
- Lookback Period: The number of bars to calculate recent highs/lows.
- Fast Period: Length of the short-term Zero-lag TEMA (69).
- Slow Period: Length of the long-term Zero-lag TEMA (130).
- Signal Display: Option to display buy/sell signals on the chart.
- Bar Color: Option to change bar colors based on trend direction.
### Adequate Sample Size
**Sample Size Justification:**
- To ensure the robustness and reliability of the strategy, it should be tested with a sufficiently long period of historical data.
- It is recommended to backtest across multiple market cycles to adapt to different market conditions.
- This strategy was backtested using 10 days of historical data, including 184 trades.
### Notes
**Additional Considerations:**
- This strategy is designed for educational purposes and should be thoroughly tested in a demo environment before live trading.
- Settings should be adjusted based on the asset being traded and current market conditions.
### Credits
**Acknowledgments:**
- The concept and implementation of Zero-lag TEMA are based on contributions from technical analysts and the trading community.
- Special thanks to John Doe for the TEMA concept.
- Thanks to Zero-lag TEMA Crosses .
- This strategy has been enhanced by adding new filtering algorithms and risk management rules to the original TEMA code.
### Clean Chart Description
**Chart Appearance:**
- This strategy provides a clean and informative chart by plotting Zero-lag TEMA lines and optional entry/exit signals.
- The display of signals and color bars can be toggled to declutter the chart, improving readability and analysis.
Macro Times [Blu_Ju]About ICT Macro Times:
The Inner Circle Trader (ICT) has taught that there are certain time sessions when the Interbank Price Delivery Algorithm (IPDA) is running a macro. The macro itself could be a repricing macro, a consolidation macro, etc. - this depends on where price currently is in relation to its draw. The times the macro is active do not change however, and are always the following (in New York local time):
8:50-9:10 (premarket macro)
9:50-10:10 (AM macro 1)
10:50-11:10 (AM macro 2)
11:50-12:10 (lunch macro)
13:10-13:40 (PM macro)
15:15-15:45 (final hour macro)
Because these times are fixed, traders can anticipate a setup is likely to form in or around these sessions. Setups may involve sweeps of liquidity (highs/lows), repricing to inefficiencies (e.g., fair value gaps), breaker setups, etc. (The specific setup involved is beyond the scope of this script; this script is concerned with visually marking the time sessions only.)
About this Script:
The scope of this script is to visually identify the macro active time sessions. This script draws vertical lines to mark the start and end of the macro time sessions. Optionally, the user can use a background color for the macro session with or without the vertical lines. The user can also toggle on or off any of the macro sessions, if he or she is only interested in certain ones. The user also has the freedom to change the times of the macro sessions if he or she is interested in a different time.
What makes this script unique is that it plots the macro time sessions after midnight for each day, before the real-time bar reaches the macro times. This is advantageous to the trader, as it gives the trader a visual cue that the macro times are approaching. When watching price it is easy to lose track of time, and the purpose of this script is to help the trader maintain where price is in relation to the macro time sessions in a simple, visual way.
RSI K-Means Clustering [UAlgo]The "RSI K-Means Clustering " indicator is a technical analysis tool that combines the Relative Strength Index (RSI) with K-means clustering techniques. This approach aims to provide more nuanced insights into market conditions by categorizing RSI values into overbought, neutral, and oversold clusters.
The indicator adjusts these clusters dynamically based on historical RSI data, allowing for more adaptive and responsive thresholds compared to traditional fixed levels. By leveraging K-means clustering, the indicator identifies patterns in RSI behavior, which can help traders make more informed decisions regarding market trends and potential reversals.
š¶ Key Features
K-means Clustering: The indicator employs K-means clustering, an unsupervised machine learning technique, to dynamically determine overbought, neutral, and oversold levels based on historical RSI data.
User-Defined Inputs: You can customize various aspects of the indicator's behavior, including:
RSI Source: Select the data source used for RSI calculation (e.g., closing price).
RSI Length: Define the period length for RSI calculation.
Training Data Size: Specify the number of historical RSI values used for K-means clustering.
Number of K-means Iterations: Set the number of iterations performed by the K-means algorithm to refine cluster centers.
Overbought/Neutral/Oversold Levels: You can define initial values for these levels, which will be further optimized through K-means clustering.
Alerts: The indicator can generate alerts for various events, including:
Trend Crossovers: Alerts for when the RSI crosses above/below the neutral zone, signaling potential trend changes.
Overbought/Oversold: Alerts when the RSI reaches the dynamically determined overbought or oversold thresholds.
Reversals: Alerts for potential trend reversals based on RSI crossing above/below the calculated overbought/oversold levels.
RSI Classification: Alerts based on the current RSI classification (ranging, uptrend, downtrend).
š¶ Interpreting Indicator
Adjusted RSI Value: The primary plot represents the adjusted RSI value, calculated based on the relative position of the current RSI compared to dynamically adjusted overbought and oversold levels. This value provides an intuitive measure of the market's momentum. The final overbought, neutral, and oversold levels are determined by K-means clustering and are displayed as horizontal lines. These levels serve as dynamic support and resistance points, indicating potential reversal zones.
Classification Symbols : The "RSI K-Means Clustering " indicator uses specific symbols to classify the current market condition based on the position of the RSI value relative to dynamically determined clusters. These symbols provide a quick visual reference to help traders understand the prevailing market sentiment. Here's a detailed explanation of each classification symbol:
Ranging Classification ("R")
This symbol appears when the RSI value is closest to the neutral threshold compared to the overbought or oversold thresholds. It indicates a ranging market, where the price is moving sideways without a clear trend direction. In this state, neither buyers nor sellers are in control, suggesting a period of consolidation or indecision. This is often seen as a time to wait for a breakout or reversal signal before taking a position.
Up-Trend Classification ("ā")
The up-trend symbol, represented by an upward arrow, is displayed when the RSI value is closer to the overbought threshold than to the neutral or oversold thresholds. This classification suggests that the market is in a bullish phase, with buying pressure outweighing selling pressure. Traders may consider this as a signal to enter or hold long positions, as the price is likely to continue rising until the market reaches an overbought condition.
Down-Trend Classification ("ā")
The down-trend symbol, depicted by a downward arrow, appears when the RSI value is nearest to the oversold threshold. This indicates a bearish market condition, where selling pressure dominates. The market is likely experiencing a downward movement, and traders might view this as an opportunity to enter or hold short positions. This symbol serves as a warning of potential further declines, especially if the RSI continues to move toward the oversold level.
Bullish Reversal ("ā²")
This signal occurs when the RSI value crosses above the oversold threshold. It indicates a potential shift from a downtrend to an uptrend, suggesting that the market may start to move higher. Traders might use this signal as an opportunity to enter long positions.
Bearish Reversal ("ā¼")
This signal appears when the RSI value crosses below the overbought threshold. It suggests a possible transition from an uptrend to a downtrend, indicating that the market may begin to decline. This signal can alert traders to consider entering short positions or taking profits on long positions.
These classification symbols are plotted near the adjusted RSI line, with their positions adjusted based on the standard deviation and a distance multiplier. This placement helps in visualizing the classification's strength and ensuring clarity in the indicator's presentation. By monitoring these symbols, traders can quickly assess the market's state and make more informed trading decisions.
š¶ Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Gann Swing Strategy [1 Bar - Multi Layer]Use this Strategy to Fine-tune inputs for your Gann swing strategy.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
MEANINGFUL DESCRIPTION:
The Gann Swing Chart using the One-Bar type, also known as the Minor Trend Chart, is designed to follow single-bar movements in the market. It helps identify trends by tracking price movements. When the market makes a higher high than the previous bar from a low price, the One-Bar trend line moves up, indicating a new high and establishing the previous low as a One-Bar bottom. Conversely, when the market makes a lower low than the previous bar from a high price, the One-Bar swing line moves down, marking a new low and setting the previous high as a One-Bar top. The crossing of these swing tops and bottoms indicates a change in trend direction.
HOW TO USE THE INDICATOR / Gann-swing Strategy:
The indicator shows 1, 2, and 3-bar swings. The strategy triggers a buy when the price crosses the previously determined high.
HOW TO USE THE STRATEGY:
Strategy to Fine-Tune Inputs for Your Gann Swing Strategy
This strategy allows for the fine-tuning of indicators for one timeframe at a time. Cross-timeframe input fine-tuning is done manually after exporting the chart data.
Meaningful Description:
The Gann Swing Chart using the One-Bar type, also known as the Minor Trend Chart, is designed to follow single-bar movements in the market. It helps identify trends by tracking price movements. When the market makes a higher high than the previous bar from a low price, the One-Bar trend line moves up, indicating a new high and establishing the previous low as a One-Bar bottom. Conversely, when the market makes a lower low than the previous bar from a high price, the One-Bar swing line moves down, marking a new low and setting the previous high as a One-Bar top. The crossing of these swing tops and bottoms indicates a change in trend direction.
How to Use the Indicator / Gann-Swing Strategy:
The indicator shows 1, 2, and 3-bar swings. The strategy triggers a buy when the price crosses the previously determined high.
How to Use the Strategy:
The strategy initiates a buy if the price breaks 1, 2, or 3-bar highs, or any combination thereof. Use the inputs to determine which highs or lows need to be crossed for the strategy to go long or short.
ORIGINALITY & USEFULNESS:
The One-Bar Swing Chart stands out for its simplicity and effectiveness in capturing minor market trends. Developed by meomeo105, this Gann high and low algorithm forms the basis of the strategy. I used my approach to creating strategy out of Gann swing indicator.
DETAILED DESCRIPTION:
What is a Swing Chart?
Swing charts help traders visualize price movements and identify trends by focusing on price highs and lows. They are instrumental in spotting trend reversals and continuations.
What is the One-Bar Swing Chart?
The One-Bar Swing Chart, also known as the Minor Trend Chart, follows single-bar price movements. It plots upward swings from a low price when a higher high is made, and downward swings from a high price when a lower low is made.
Key Features:
Trend Identification : Highlights minor trends by plotting swing highs and lows based on one-bar movements.
Simple Interpretation : Crossing a swing top indicates an uptrend, while crossing a swing bottom signals a downtrend.
Customizable Periods : Users can adjust the period to fine-tune the sensitivity of the swing chart to market movements.
Practical Application:
Bullish Trend : When the One-Bar Swing line moves above a previous swing top, it indicates a bullish trend.
Bearish Trend : When the One-Bar Swing line moves below a previous swing bottom, it signals a bearish trend.
Trend Reversal : Watch for crossings of swing tops and bottoms to detect potential trend reversals.
The One-Bar Swing Chart is a powerful tool for traders looking to capture and understand market trends. By following the simple rules of swing highs and lows, it provides clear and actionable insights into market direction.
Why the Strategy Uses 100% Allocation of a Portfolio:
This strategy allocates 100% of the portfolio to trading this specific pair, which does not mean 100% of all capital but 100% of the allocated trading capital for this pair. The strategy is swing-based and does not use take profit (TP) or stop losses.
