BitCoin Simple BuyerMany people asking me: How to find the right time to exit BitCoin long position? First, that comes to mind is Do Not use simple Buy-and-Hold strategy, but make short-term trades. Here is the simple algorithm for D1 or 4H timeframes.
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MÈGAS ALGO : CNA (Cognitio Analysis) [INDICATOR]Overview
The CNA (Cognitio Analysis) is a comprehensive financial analysis tool designed to evaluate the overall health and potential of a market or company based on fundamental metrics. It aggregates data across five key metric groups—**Growth**, **Profitability**, **Cash Flow**, **Income**, and **Valuation**—to provide a final interpretation of market conditions. The indicator dynamically adapts to the selected fiscal period (Quarter, Year, or Trailing Twelve Months) and delivers insights into dominant trends and conflicting signals.
Key Features
1. Customizable Fiscal Period:
- Users can select between "Quarter", "Year", or "Trailing Twelve Months" (TTM) to analyze data for their desired timeframe.
2. Dynamic Table Visualization:
- Displays raw metric values, aggregated scores, and the final interpretation in an intuitive
table.
- Highlights the final interpretation with dynamic background colors (`color.teal` for bullish,
`color.red` for bearish, etc.).
3. Comprehensive Data Integration:
- Pulls financial data using TradingView's `request.financial()` function for metrics like
revenue, earnings, margins, and valuation ratios.
4. Normalization and Scoring:
- Normalizes data to create a consistent scoring system, ensuring accurate comparisons across
metrics.
How It Works
1. Metric Group Analysis
- Growth Metrics: Measures revenue growth, earnings per share (EPS) growth, and tax
efficiency.
- Profitability Metrics: Analyzes net profit margin, return on equity (ROE), and EBITDA margin.
- Cash Metrics: Assesses operating cash flow margin, free cash flow to operating cash flow
ratio, and cash flow coverage.
- Income Metrics: Examines gross profit margin, operating profit margin, and EBIT margin.
- Valuation Metrics: Evaluates price-to-earnings (P/E), price-to-sales (P/S), and enterprise
value-to-EBITDA (EV/EBITDA).
2. Dynamic Scoring System
- Metrics are normalized to ensure consistency across different scales.
- A geometric mean is used to calculate scores for each metric group, ensuring that all metrics
within a group contribute equally to the final score.
3. Dominant Trend Identification
- Scores from all five metric groups are aggregated to determine the **dominant trend** of the
market.
- The dominant trend is categorized as:
- Bullish: Strong fundamentals across most metrics.
- Bearish: Weak fundamentals across most metrics.
- Neutral: Balanced conditions with no clear direction.
- Unclear: Mixed signals dominate, requiring further monitoring.
4. Conflicting Signals Interpretation
- The indicator identifies scenarios where metrics conflict (e.g., high growth but low valuation).
- These conflicting signals provide nuanced insights into market conditions, highlighting rare opportunities or potential risks.
How to Use the Indicator
1. Select Fiscal Period:
- Choose between "FQ", "FY", or "TTM" to analyze data for the desired timeframe.
2. Review Metric Scores:
- Examine the scores for each metric group (Growth, Profitability, Cash, Income, Valuation) to
understand the underlying performance.
3. Interpret Final Output:
- The final interpretation provides a summary of the dominant trend and conflicting signals,
helping users make informed decisions.
4. Dynamic Coloring:
- Use the dynamic background colors in the table to quickly identify market sentiment
(bullish, bearish, neutral, or mixed).
Applications
- Identifying Opportunities:
- Look for bullish dominant trends combined with undervalued growth opportunities for
potential long positions.
- Avoiding Risks:
- Watch out for bearish dominant trends with overvaluation alerts to avoid potential losses.
- Monitoring Neutral Markets:
- Use the indicator to identify neutral markets and wait for clearer signals before making
decisions.
Conclusion
The CNA (Cognitio Analysis) is a powerful tool for traders and investors seeking to make informed decisions based on fundamental analysis. By combining detailed metric evaluations, dynamic scoring, and sentiment-based interpretations, this indicator provides a comprehensive view of market conditions. Whether you're identifying undervalued opportunities, avoiding overvalued risks, or monitoring neutral markets, this indicator equips you with the insights needed to navigate complex financial landscapes.
Please Note:
This indicator is provided for informational and educational purposes only. It is not financial advice, and it should not be considered a recommendation to buy, sell, or trade any financial instrument. Trading involves significant risks, including the potential loss of your entire investment. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
The results and images provided are based on algorithms and historical/paid real-time market data but do not guarantee future results or accuracy. Use this tool at your own risk, and understand that past performance is not indicative of future outc
MÈGAS ALGO : ZIG-ZAG CYCLE INSIGTH [INDICATOR]Overview
The Zig-Zag Cycle Insigth is a revisited version of the classic Zig Zag indicator, designed to provide traders with a more comprehensive and actionable view of price movements.
This advanced tool not only highlights significant price swings but also incorporates additional features such as cycle analysis, real-time data tracking, and Fibonacci retracement levels. These enhancements make it an invaluable resource for identifying trends, potential reversal points, and market structure.
This indicator adheres to TradingView's guidelines and is optimized for both technical analysts and active traders who seek deeper insights into market dynamics.
Key Features:
1. Customizable Thresholds for Price Movements:
- Users can set personalized thresholds for price movement percentages and time periods.
This ensures that only significant price swings are plotted, reducing noise and increasing
clarity.
- Straight lines connect swing highs and lows, providing a cleaner visual representation of
the trend.
2. Cycle Analysis Table:
- A dynamic table is included to analyze price cycles based on three key factors:
- Price Change: Measures the magnitude of each swing (high-to-low or low-to-high).
- Time Duration (Bar Count): Tracks the number of bars elapsed between consecutive swings,
offering precise timing insights.
- Volume: Analyzes trading volume during each segment of the cycle.
- The indicator calculates the **maximum**, **minimum**, and **mean** values for each
parameter across all completed cycles, providing deeper statistical insights into market
behavior.
- This table updates in real-time, offering traders a quantitative understanding of how price
behaves over different cycles.
3. Real-Time Data Integration:
- The indicator displays live updates of current price action relative to the last identified
swing high/low. This includes:
- Current distance from the last pivot point.
- Percentage change since the last pivot.
- Volume traded since the last pivot.
4. Fibonacci Retracement Levels:
- Integrated Fibonacci retracement levels are dynamically calculated based on the most
recent significant swing high and low.
- Key retracement levels (23.6%, 38.2%, 50%, 61.8%, and 78.6%) are plotted alongside the Zig
Zag lines, helping traders identify potential support/resistance zones.
- Extension levels (100%, 161.8%, etc.) are also included to anticipate possible breakout
targets.
5. Customizable Alerts:
- Users can configure alerts for specific real-time conditions, such as:
- Price Change
- Duration
- Volume
- Fibonacci Retracement Levels
How It Works:
1. Zig Zag Identification:
- The indicator scans historical price data to identify significant turning points where the
price moves by at least the user-defined percentage threshold.
- These turning points are connected by straight lines to form the Zig Zag pattern.
2. Cycle Analysis:
For each completed cycle (from one swing high/low to the next), the indicator calculates:
- Price Change: Difference between the start and end prices of the cycle.
- Maximum Price Change: The largest price difference observed across all cycles.
- Minimum Price Change: The smallest price difference observed across all cycles.
- Mean Price Change: The average price difference across all cycles.
- Time Duration (Bar Count): Number of bars elapsed between consecutive swings.
- Maximum Duration: The longest cycle in terms of bar count.
- Minimum Duration: The shortest cycle in terms of bar count.
- Mean Duration: The average cycle length in terms of bar count.
- Volume: Total volume traded during the cycle.
- Maximum Volume: The highest volume traded during any single cycle.
- Minimum Volume: The lowest volume traded during any single cycle.
- Mean Volume: The average volume traded across all cycles.
- These calculations provide traders with a statistical overview of market behavior, enabling
them to identify patterns and anomalies in price, time, and volume.
3. Fibonacci Integration:
- Once a new swing high or low is identified, the indicator automatically calculates Fibonacci
retracement and extension levels.
- These levels serve as reference points for potential entry/exit opportunities.
4. Real-Time Updates:
- As the market evolves, the indicator continuously monitors the relationship between the
current price and the last identified swing point.
- Real-time metrics, such as percentage change and volume, are updated dynamically.
5. Alerts Based on Real-Time Parameters:
- The indicator allows users to set customizable alerts based on real-time conditions:
- Price Change Alert: Triggered when the real-time price change is less or greater than a
predefined percentage threshold (e.g., > or < fixed value).
- Duration Alert: Triggered when the cycle duration (in bars) is less or greater than a
predefined
bar count threshold (e.g., > or < fixed value).
- Volume Alert: Triggered when the trading volume during the current cycle is less or greater
than a predefined volume threshold (e.g., > or < fixed value).
Advantages of Zig-Zag Cycle Insigth
- Comprehensive Insights: Combining cycle analysis, Fibonacci retracements, and real-time data
provides a holistic view of market conditions.
- Statistical Analysis: The inclusion of maximum, minimum, and mean values for price change,
duration, and volume offers deeper insights into market behavior.
- Actionable Signals: Customizable alerts ensure traders never miss critical market events based
on real-time price, duration, and volume parameters.
- User-Friendly Design: Clear visuals and intuitive controls make it accessible for traders of all
skill levels.
Reference:
TradingView/ZigZag
TradingView/AutofibRetracement
Please Note:
This indicator is provided for informational and educational purposes only. It is not financial advice, and it should not be considered a recommendation to buy, sell, or trade any financial instrument. Trading involves significant risks, including the potential loss of your entire investment. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
The results and images provided are based on algorithms and historical/paid real-time market data but do not guarantee future results or accuracy. Use this tool at your own risk, and understand that past performance is not indicative of future outcomes.
Market Structure Algo V2 [OmegaTools]The Market Structure Algo V2 (MS Algo V2) is an advanced TradingView indicator developed by OmegaTools to provide traders with a comprehensive analysis of market structure. This tool refines the insights provided by its predecessor, combining enhanced pivot point analysis, dynamic market structure scoring, and zone visualization to deliver an intuitive view of potential market movements. Through custom settings, the MS Algo V2 allows users to tailor the indicator to fit their trading strategies more closely, offering enhanced adaptability to both short-term and long-term trends.
Core Functionality
The MS Algo V2 differentiates between internal and external market structures by analyzing pivot highs and lows over user-defined periods. The internal market structure focuses on shorter timeframes, providing insights into recent price action, while the external structure considers broader trends. This dual-layered approach helps traders distinguish between immediate and overarching market trends.
The indicator introduces improved visualization for areas of interest or zones around pivot points, adjustable through zone distance settings. These zones serve as potential support and resistance areas, helping traders anticipate price reactions at key levels. In addition to the zones, the indicator now provides gradient-based color coding on bars, reflecting the market structure’s bullish or bearish intensity. This visual enhancement aids in quickly interpreting the current trend's strength.
Dynamic signal generation has been refined in MS Algo V2. The indicator now offers both classic signals and breakout signals based on the market structure, including entries, exits, and change-of-character (CHoCH) alerts. Signals are generated based on price interactions with pivot levels, indicating potential long and short opportunities.
Operational Mechanism
The MS Algo V2 calculates pivot highs and lows over specified periods to define internal and external market structures. A market structure score is derived from these pivot points, classifying the market into bullish or bearish extremes. Signals are generated as the closing price interacts with these levels, marking entry and exit points based on the calculated structure.
A new feature in this version is zone visualization, where zones are plotted around a dynamic moving average derived from the exponential and simple moving averages (EMA and SMA). The zones are adjusted based on ATR (Average True Range) and the specified zone distance percentile, providing a clear visual representation of potential support and resistance regions. The external and internal zones are represented with different levels of transparency for quick reference.
Usage Guidelines
To apply the MS Algo V2 to your TradingView charts, adjust the internal and external market structure settings to match your preferred analysis timeframes. The line style and width of each structure can also be customized for a tailored view. The Zone Distance setting allows users to define the percentile range of the zones around the moving average, providing further flexibility in identifying potential areas of support and resistance.
For a color-coded overview of market sentiment, the bar gradient feature can be enabled. This option uses a gradient that reflects the bullish or bearish intensity of the market structure, giving traders a visual cue on the market’s overall trend. Color-coded signals and zone fill areas further assist in interpreting the current market structure and identifying potential trade areas.
The indicator includes customizable alerts for long and short signals, as well as specific breakout alerts (BOS) and change-of-character (CHoCH) signals. These alerts can help traders stay informed about significant market structure changes, supporting timely trading decisions.
Understanding the Indicator’s Originality
The MS Algo V2 stands out due to its robust integration of pivot analysis, zone visualization, and market structure scoring, offering a unique perspective on market dynamics. With features like color-coded signals, bar gradients, and configurable alerts, MS Algo V2 provides an edge in understanding both the current market environment and potential turning points. This indicator’s ability to represent the market’s structure visually makes it a powerful addition to any trader’s toolkit, especially for those seeking a deeper, multi-layered approach to market analysis.
GannLSVZO Indicator [Algo Alert]The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Laplace with Gann Swing Entries and Exits (orange X) and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator.
The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
The Gann swings and the Gan 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 oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Laplace Stieltjes Transform approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs.
Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings.
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.
DeQuex Algo BISTIntroduction:
The DeQuex Algo is an advanced technical analysis tool designed to help traders identify high-probability entry and exit points in the Borsa Istanbul (BIST) market. This updated version incorporates an adaptive MACD to reduce false signals and improve the overall reliability of the indicator.
Key Features:
1. Adaptive MACD: The script utilizes an adaptive MACD that dynamically adjusts to market volatility, reducing the occurrence of false signals often associated with traditional MACD implementations.
2. RSI Confirmation: In addition to the adaptive MACD, the DeQuex Algo also considers RSI readings to provide stronger confirmation for buy and sell signals.
3. Signal Types:
- Buy Signal: Triggered when the adaptive MACD crosses above its signal line.
- Sell Signal: Triggered when the adaptive MACD crosses below its signal line.
- Strong Buy Signal: Triggered when both the adaptive MACD and RSI cross above their respective thresholds, indicating a high-probability bullish setup.
- Strong Sell Signal: Triggered when both the adaptive MACD and RSI cross below their respective thresholds, indicating a high-probability bearish setup.
4. Price Bar Highlighting: The script color-codes price bars to provide a visual representation of the current trend. Green bars indicate an uptrend, red bars indicate a downtrend, and purple bars signify a period of consolidation or uncertainty. This feature allows traders to quickly assess the market context at a glance.
5. Customizable Alerts: Users can enable alerts for each signal type, ensuring they never miss a potential trading opportunity.
6. Dynamic Support and Resistance: The DeQuex Algo incorporates dynamic support and resistance levels based on market volatility. These levels are plotted using an innovative approach that combines Donchian channels with a Kalman filter for smoother, more reliable zones.
7. User-Friendly Inputs: The script provides a range of input parameters, allowing traders to fine-tune the indicator's sensitivity and adapt it to their preferred trading style and timeframe.
How to Use:
1. Add the DeQuex Algo indicator to your TradingView chart.
2. Customize the input parameters as desired, or use the default settings.
3. Enable alerts for your preferred signal types.
4. Look for buy and sell signals based on the adaptive MACD and RSI readings, paying attention to the color-coded price bars for additional context.
5. Consider the dynamic support and resistance levels when planning your entries, exits, and stop-loss placements.
Please note that while the DeQuex Algo is designed to identify high-probability setups, no indicator is perfect, and false signals may still occur. Always use proper risk management and consider other factors, such as market sentiment and fundamental analysis, when making trading decisions.
We hope that the DeQuex Algo will be a valuable addition to your trading toolbox, and we welcome any feedback or suggestions for further improvement.
Best regards,
BrandonJames1337
TR:
İşte güncellenmiş DeQuex Algo göstergeniz için önerilen bir açıklama:
Giriş:
DeQuex Algo, yatırımcıların Borsa İstanbul (BIST) piyasasında yüksek olasılıklı giriş ve çıkış noktalarını belirlemelerine yardımcı olmak için tasarlanmış gelişmiş bir teknik analiz aracıdır. Bu güncellenmiş sürüm, yanlış sinyalleri azaltmak ve göstergenin genel güvenilirliğini artırmak için uyarlanabilir bir MACD içerir.
Temel Özellikler:
1. Uyarlanabilir MACD: Komut dosyası, piyasa oynaklığına dinamik olarak ayarlanan ve genellikle geleneksel MACD uygulamalarıyla ilişkili yanlış sinyallerin oluşumunu azaltan uyarlanabilir bir MACD kullanır.
2. RSI Onayı: Uyarlanabilir MACD'ye ek olarak DeQuex Algo, alım ve satım sinyalleri için daha güçlü onay sağlamak üzere RSI okumalarını da dikkate alır.
3. Sinyal Türleri:
- Alış Sinyali: Uyarlanabilir MACD sinyal çizgisinin üzerine çıktığında tetiklenir.
- Satış Sinyali: Uyarlanabilir MACD sinyal çizgisinin altından geçtiğinde tetiklenir.
- Güçlü Alış Sinyali: Hem uyarlanabilir MACD hem de RSI kendi eşiklerinin üzerine çıktığında tetiklenir ve yüksek olasılıklı bir yükseliş düzenine işaret eder.
- Güçlü Satış Sinyali: Hem uyarlanabilir MACD hem de RSI kendi eşiklerinin altına düştüğünde tetiklenir ve yüksek olasılıklı bir düşüş düzenine işaret eder.
4. Fiyat Çubuğu Vurgulama: Komut dosyası, mevcut eğilimin görsel bir temsilini sağlamak için fiyat çubuklarını renk kodlarıyla kodlar. Yeşil çubuklar yükseliş trendini, kırmızı çubuklar düşüş trendini ve mor çubuklar ise konsolidasyon veya belirsizlik dönemini gösterir. Bu özellik, yatırımcıların piyasa bağlamını bir bakışta hızlı bir şekilde değerlendirmelerine olanak tanır.
5. Özelleştirilebilir Uyarılar: Kullanıcılar her sinyal türü için uyarıları etkinleştirerek potansiyel bir alım satım fırsatını asla kaçırmamalarını sağlayabilir.
6. Dinamik Destek ve Direnç: DeQuex Algo, piyasa oynaklığına dayalı dinamik destek ve direnç seviyeleri içerir. Bu seviyeler, daha yumuşak ve daha güvenilir bölgeler için Donchian kanallarını Kalman filtresiyle birleştiren yenilikçi bir yaklaşım kullanılarak çizilir.
7. Kullanıcı Dostu Girişler: Komut dosyası, yatırımcıların göstergenin hassasiyetini ince ayarlamalarına ve tercih ettikleri ticaret tarzına ve zaman dilimine uyarlamalarına olanak tanıyan bir dizi giriş parametresi sağlar.
Nasıl Kullanılır:
1. DeQuex Algo göstergesini TradingView grafiğinize ekleyin.
2. Giriş parametrelerini istediğiniz gibi özelleştirin veya varsayılan ayarları kullanın.
3. Tercih ettiğiniz sinyal türleri için uyarıları etkinleştirin.
4. Ek bağlam için renk kodlu fiyat çubuklarına dikkat ederek uyarlanabilir MACD ve RSI okumalarına dayalı alım ve satım sinyallerini arayın.
5. Girişlerinizi, çıkışlarınızı ve stop-loss yerleşimlerinizi planlarken dinamik destek ve direnç seviyelerini göz önünde bulundurun.
DeQuex Algo yüksek olasılıklı kurulumları belirlemek için tasarlanmış olsa da, hiçbir göstergenin mükemmel olmadığını ve yine de yanlış sinyallerin oluşabileceğini lütfen unutmayın. Alım satım kararları verirken her zaman uygun risk yönetimini kullanın ve piyasa duyarlılığı ve temel analiz gibi diğer faktörleri göz önünde bulundurun.
DeQuex Algo'nun ticaret araç kutunuza değerli bir katkı sağlayacağını umuyor ve daha fazla iyileştirme için her türlü geri bildirim veya öneriyi memnuniyetle karşılıyoruz.
Saygılarımla,
BrandonJames1337
Buy / Sell Fractal Algorithm with SL Line GenerationThis algorithm is designed for usage across indices.
How it works?
The algorithm uses a variation of fractals, momentum, RSI and LRSI to determine a trends direction.
The Relative Strength Index (RSI) is a momentum-based oscillator used to measure the speed (velocity) and change (magnitude) of directional price movements. It provides a visual means to monitor both the current and historical strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period, creating a reliable metric of price and momentum changes
Momentum in trading refers to the direction and magnitude of price. Momentum plays a key role in assessing trend strength, and it is important to know when a trend is slowing down. Less momentum does not always lead to a reversal, but it does signal that something is changing, and the trend may consolidate or reverse
Fractals are patterns within price changes which are repeated across thousands of bars. Examples of fractals include the golden ratio, PHI and the spirals of the milk way. They are quite literally a universal concept.
Basics of usage:
When a bullish trend is detected; the algorithm will generate a green "SL Line" at a calculated point, which can be interpreted as an invalidation line.
If the price goes below this line, the bullish trend is invalidated. So long as it holds, the bullish trend is true until the next detection change.
When a bearish trend is detected; the algorithm will generate a red "SL Line", at a calculated point, which can be interpreted as an invalidation line.
If the prices goes above this line, the bearish trend is invalidated. So long as it holds, the bearish trend is true until the next detection change.
When a given trend is invalidated, the SL Line turns yellow and you enter a "pause zone", where neither a bearish nor bullish trend is calculated.
This resets itself on the next trend detection.
Additional information:
I have coded my own backtest to this algorithm, along with plotting the profit / loss of each generated trade.
The profit is calculated by the difference between the open bar of the trade after a long ( or short ) and the following trade.
If we are calculating a short, the resulting value is then multiplied by -1 to get a positive integer.
For calculating a loss we take the value of the open bar of the trade that generates a long, and take the difference between this and the SL line, and similarly for short positions. The code assumes the user is placing their SL at the indicated line.
Within the input settings there are a few customisation options:
Alpha & Fractal Energy Length & Source - Should not be changed.
Highly bands crossover? - Has no visible effect whether on or off. It refers to the fractal chart which in this iteration is not visible and rather a backend mechanic.
Apply fractal energy? - Should generally be left turned on. This is a noise reduction. Disabling will result in over-trading.
Apply normalization? - Has no impact, is solely used to make the fractal values more human-readable rather than decimal format.
Offset - refers to the offset value of the SL Line generations. This should be set to a value that gives you enough breathing room, and remember to include any spreads! Default is 0.2, written in %
Trading hours - This simply gives a session input for the trading hours you want to trade within, and then colours the background green for that session. Trading 24/7 is never a wise strategy, stick to whatever is most optimal for you.
Leverage - Whatever leverage you are using. Default is x20. This will affect the profit / loss calculations accordingly.
Start equity - refers to the equity value you want to backtest with. Some assets will generate NA for this in the backtest label explained later.
Label customisation options.
Note that the backtest label is by default hidden, and appears when you hover over the black label at the current bar. When enabled to visible, it will show a large text label that may cover your chart screen more than you wish.
Alerts -
There are dozens of alert functionalities here; first are the timeframe assignments for each alert, set by default to 2hrs.
These timeframes then affect the asset you select in the corresponding setting.
In total there are 8 additional assets you can set alerts for.
Once you have assigned the timeframe and asset for an alert, you can then check the tick box for that individual alert.
Once done, you set the alert as normal through the tradingview alerts window. Remember to set "alert function calls only"
-
Timers:
I have added some functionality for timers to be set, values are in minutes. These work on the exact time of placement. Do not change the extra symbol formula option.
-
Note that this backtest is not intended as a replacement for tradingview backtest, nor is there a guarantee that historical results are to be replicated in the future. Trading is inherently risky.
30 Second Futures Session Open RangeThis indicator displays 30 second opening ranges from Globex, Europe, and RTH sessions.
From the RTH session range, it also displays infinitely generating Price Targets based on a % of the opening range size.
I am retrieving the 30 second data using the new "request.security_lower_tf()" function.
The importance of these levels is based on the idea that when the market opens, algorithms establish their positions within the first 30 seconds.
These areas can also be seen as potential areas of support and resistance throughout the sessions.
Enjoy!
SBS AlgoHello traders, I am here again with a new and improved indicator.
This indicator is based on a pivot breakout algorithm which gives buy and sell signals according to the breakout of trendline. This is an advanced version of another script. It also takes price action into consideration along with some basic indicators like MACD and ADX to give good entry signals.
NOTE: This indicator is not designed to take entries completely based on signals it gives. Please use it along with your trading strategy to add more confluence to your trading system and maximize your profits.
I hope you guys will like this one too .Enjoy 👍
In case you find any bug, please do report in comment section .Thank you.
BollingerBands Strat + pending order alerts via TradingConnectorSoftware part of algotrading is simpler than you think. TradingView is a great place to do this actually. To present it, I'm publishing each of the default strategies you can find in Pinescript editor's "built-in" list with slight modification - I'm only adding 2 lines of code, which will trigger alerts, ready to be forwarded to your broker via TradingConnector and instantly executed there. Alerts added in this script: 14, 17, 20 and 23.
SCRIPT INCLUDES PENDING ORDERS AND ALERTS! Alert will be sent to MetaTrader when order is triggered, but not yet filled. That means if market conditions change and order does not get filled, it needs to be cancelled as well, and there are alerts for that in the script as well.
How it works:
1. TradingView alert fires.
2. TradingConnector catches it and forwards to MetaTrader4/5 you got from your broker.
3. Trade gets executed inside MetaTrader within 1 second of fired alert.
When configuring alert, make sure to select "alert() function calls only" in CreateAlert popup. One alert per ticker is required.
Adding stop-loss, take-profit, trailing-stop, break-even or executing pending orders is also possible. These topics have been covered in other example posts.
This routing works for Forex, indices, stocks, crypto - anything your broker offers via their MetaTrader4 or 5.
Disclaimer: This concept is presented for educational purposes only. Profitable results of trading this strategy are not guaranteed even if the backtest suggests so. By no means this post can be considered a trading advice. You trade at your own risk.
If you are thinking to execute this particular strategy, make sure to find the instrument, settings and timeframe which you like most. You can do this by your own research only.
Consecutive Up/Down Strat + alerts via TradingConnector to ForexSoftware part of algotrading is simpler than you think. TradingView is a great place to do this actually. To present it, I'm publishing each of the default strategies you can find in Pinescript editor's "built-in" list with slight modification - I'm only adding 2 lines of code, which will trigger alerts, ready to be forwarded to your broker via TradingConnector and instantly executed there. Alerts added in this script: 12 and 15.
How it works:
1. TradingView alert fires.
2. TradingConnector catches it and forwards to MetaTrader4/5 you got from your broker.
3. Trade gets executed inside MetaTrader within 1 second of fired alert.
When configuring alert, make sure to select "alert() function calls only" in CreateAlert popup. One alert per ticker is required.
Adding stop-loss, take-profit, trailing-stop, break-even or executing pending orders is also possible. These topics have been covered in other example posts.
This routing works for Forex, indices, stocks, crypto - anything your broker offers via their MetaTrader4 or 5.
Disclaimer: This concept is presented for educational purposes only. Profitable results of trading this strategy are not guaranteed even if the backtest suggests so. By no means this post can be considered a trading advice. You trade at your own risk.
If you are thinking to execute this particular strategy, make sure to find the instrument, settings and timeframe which you like most. You can do this by your own research only.
3Commas BotBjorgum 3Commas Bot
A strategy in a box to get you started today
With 3rd party API providers growing in popularity, many are turning to automating their strategies on their favorite assets. With so many options and layers of customization possible, TradingView offers a place no better for young or even experienced coders to build a platform from to meet these needs. 3Commas has offered easy access with straight forward TradingView compatibility. Before long many have their brokers hooked up and are ready to send their alerts (or perhaps they have been trying with mixed success for some time now) only they realize there might just be a little bit more to building a strategy that they are comfortable letting out of their sight to trade their money while they eat, sleep, etc. Many may have ideas for entry criteria they are excited to try, but further questions arise... "What about risk mitigation?" "How can I set stop or limit orders?" "Is there not some basic shell of a strategy that has laid some of this out for me to get me going?"
Well now there is just that. This strategy is meant for those that have begun to delve into the world of algorithmic trading providing a template that offers risk defined positions complete with stops, limit orders, and even trailing stops should one so choose to employ any of these criteria. It provides a framework that is easily manipulated (with some basic working knowledge of pine coding) to encompass ones own ideas and entry criteria, while also providing an already functioning strategy.
The default settings have a basic 1:1 risk to reward ratio, which sets a limit and a stop equal distance from the entry. The entry is a simple MA cross (up for long, down for short). There a variety of MA's to choose from and the user can define the lengths of the averages. The ratio can be adjusted from the menu along with a volatility based adder (ATR) that helps to distance a stop from support or resistance. These values are calculated off the swing low/high of the user defined lookback period. Risk is calculated from position entry to stop, and projected upwards to the limit as a function of the desired risk to reward ratio. Of note: the default settings include 0.05% commissions. Competitive commissions of the leading cryptocurrency exchanges are .1% round trip (one buy and one sell) for market orders. There is also some slippage to allow time for alerts to be sent and orders to fill giving the back test results a more accurate representation of real time conditions. Its recommended to research the going rates for your exchange and set them to default for the strategy you use or build.
To get started a user would:
1) Make a copy of the code and paste in their bot keys in the area provided under the "3Comma Keys" section
- eg. Long bot "start deal" copied from 3commas in to define "Long" etc. (code is commented)
2) Place alert on desired asset with desired settings ensuring to select "Order fills and alert() function calls"
3) Paste webhook into the webhook box and select webhook URL alerts (3rd party provided webhook)
3) Delete contents of alert message box and replace with {{strategy.order.alert_message}} and nothing else
- the codes will be sent to the webhook appropriately as the strategy enters and exits positions. Only 1 alert is needed
settings used for the display image:
1hr chart on BTCUSD
-ATR stop
-Risk adjustment 1.2
-ATR multiplier 1.3
-RnR 0.6
-MAs HEMA/SMA
-MA Length 50/100
-Order size percent of equity
-Trail trigger 60% of target
Experiment with your own settings on your crypto of choice or implement your own code!
Implementing your trailing stop (optional)
Among the options for possible settings is a trailing stop. This stop will ratchet higher once triggered as a function of the Average True Range (ATR). There is a variable level to choose where the user would like to begin trailing the stop during the trade. The level can be assigned with a decimal between 0 and 1 (eg. 0.5 = 50% of the distance between entry and the target which must be exceeded before the trail triggers to begin). This can allow for some dips to occur during the trade possibly keeping you in the trade for longer, while potentially reducing risk of drawdown over time. The default for this setting is 0 meaning unless adjusted, the trail will trigger on entry if the trailing stop exit method is selected. An example can be seen below:
Again, optional as well is the choice to implement a limit order. If one were to select a trailing stop they could choose not to set a limit, which could allow a trail to run further until hit. Drawdowns of this strategy would be foregoing locking gains at highs on target on other trades. This is a trade-off the user can decide on and test. An example of this working in favor can be observed below:
Conclusion
Although a simple strategy is implemented here, the benefits of this script allow a user a starting platform to build their strategies from with built in risk mitigation. This allows the user to sidestep some of the potential difficulties' that can arise while learning Pine and taking on the endeavor of automating their trading strategies. It is meant as an aid, a structure, and an educational piece that can be seen as a "pick-up-and-go" strategy with easy 3Commas compatibility. Additionally, this can help users become more comfortable with strategy alert messages and sending strings in the form of alerts from Pine. As well, FAQs are often littered with questions regarding "strategy.exit" calls, how to implement stops. how to properly set a trailing stop based on ATR, and more. The time this can save an individual to get started is likely of the best "take-aways" here.
Happy trading
Percentile Rank Market FilterA simple script to filter bull and bear markets by using percentile rank filter. Using market regimes to filter by bull/bear/sideways markets helps to understand how your strategy will
behave in various market regimes and allows you to avoid unprofitable regimes and only trade in profitable ones.
The idea of market regime filtering is used in the most successful technical algorithmic trading strategies, as one should always design a trading strategy with a particular market in mind according to trading legend, Larry Connors
Feel free to use this script in your strategies to improve your profits and lower drawdowns.
14/28 Day SMA Divergence and RSI - No RepaintIf you are interested in purchasing my algorithmic trading bot that receives Tradingview indicator alerts via email and then executes them in Bittrex, please visit my product page here: ilikestocks.com Additionally, I would love to create video/blog guides on creating Tradingview scripts or strategies. If you are a knowledgeable in finance or other related fields and would like to be featured on my page, please contact me at tanner@ilikestocks.com.
No crossovers were used in this script, and this is likely the reason for the no repaint(Correct me if wrong).
This strategy script uses a 14-day SMA signal line, a 28-day SMA and RSI. The strategy works by determining whether the (14-day SMA is above the 28-day SMA and the RSI levels are overbought(below 30)) or RSI is very overbought(below 13 or so). Once either of these conditions have been met, a long position is opened.
The initial long position must be partially closed by the take profit first and then the final close is executed if the 14-day signal SMA is below the 28-day SMA; you may also exclusively use take profit to close positions.
The green plotted spikes are the initial long position conditions. The orange plotted spikes are take profit signals once a long position is opened. The red plotted spikes are plotted when the SMA 14-day is below the 28-day SMA.
Please do leave constructive criticism or comments below because it helps me better create scripts!
Harish algo for nifty and bankniftyHarish algo for nifty and banknifty
Overview
Harish Algo - Buy and Sell 11 is a powerful trading indicator designed for intraday traders, incorporating multiple technical analysis concepts to identify potential breakout and breakdown levels. It uses pivot points, exponential moving averages (EMAs), and volatility-based levels to generate buy and sell signals with visual markers for better decision-making.
Features & Functionality
✅ Pivot Points Calculation:
The indicator calculates daily pivot points along with resistance (R1) and support (S1) levels.
Helps in identifying potential reversal or breakout areas.
✅ EMA Trend Confirmation:
Uses three EMAs (21, 55, and 200) to confirm trend direction.
Ensures that buy signals align with uptrends and sell signals align with downtrends.
✅ 15-Minute Candle Analysis for Precision:
Captures the last three 15-minute closes of the previous day.
Computes an average and determines volatility-based price levels to anticipate price movements.
✅ Dynamic Buy & Sell Signals:
Bullish (Buy) Signals:
Price breaks above key resistance levels and EMAs confirm an uptrend.
Displayed as yellow (tiny) or green (small) upward triangles below candles.
Bearish (Sell) Signals:
Price drops below key support levels with EMA confirmation of a downtrend.
Displayed as fuchsia (tiny) or red (small) downward triangles above candles.
✅ Alerts for Trade Execution:
Get notified instantly with alerts when a buy or sell signal is triggered.
✅ Customizable Settings:
Modify EMA lengths and adjust parameters to fit different trading strategies.
Usage & Benefits
🔹 Helps traders identify potential entry and exit points with precision.
🔹 Reduces false signals by combining pivot points, EMAs, and price action.
🔹 Works best for intraday traders in the Indian stock markets, but can be applied to other markets as well.
🔹 Suitable for both beginners and experienced traders looking for a structured approach to trading.
How to Use
Add the indicator to your chart.
Observe the plotted pivot points, EMAs, and price levels.
Watch for triangle markers (buy/sell signals).
Use alerts to receive real-time notifications.
Combine with your own risk management strategy for best results.
🔹 Works on all timeframes but optimized for intraday trading.
Disclaimer
📢 This indicator is for educational purposes only and should not be considered financial advice. Always perform your own analysis before taking trades.
PIP Algorithm
# **Script Overview (For Non-Coders)**
1. **Purpose**
- The script tries to capture the essential “shape” of price movement by selecting a limited number of “key points” (anchors) from the latest bars.
- After selecting these anchors, it draws straight lines between them, effectively simplifying the price chart into a smaller set of points without losing major swings.
2. **How It Works, Step by Step**
1. We look back a certain number of bars (e.g., 50).
2. We start by drawing a straight line from the **oldest** bar in that range to the **newest** bar—just two points.
3. Next, we find the bar whose price is *farthest away* from that straight line. That becomes a new anchor point.
4. We “snap” (pin) the line to go exactly through that new anchor. Then we re-draw (re-interpolate) the entire line from the first anchor to the last, in segments.
5. We repeat the process (adding more anchors) until we reach the desired number of points. Each time, we choose the biggest gap between our line and the actual price, then re-draw the entire shape.
6. Finally, we connect these anchors on the chart with red lines, visually simplifying the price curve.
3. **Why It’s Useful**
- It highlights the most *important* bends or swings in the price over the chosen window.
- Instead of plotting every single bar, it condenses the information down to the “key turning points.”
4. **Key Takeaway**
- You’ll see a small number of red line segments connecting the **most significant** points in the price data.
- This is especially helpful if you want a simplified view of recent price action without minor fluctuations.
## **Detailed Logic Explanation**
# **Script Breakdown (For Coders)**
//@version=5
indicator(title="PIP Algorithm", overlay=true)
// 1. Inputs
length = input.int(50, title="Lookback Length")
num_points = input.int(5, title="Number of PIP Points (≥ 3)")
// 2. Helper Functions
// ---------------------------------------------------------------------
// reInterpSubrange(...):
// Given two “anchor” indices in `linesArr`, linearly interpolate
// the array values in between so that the subrange forms a straight line
// from linesArr to linesArr .
reInterpSubrange(linesArr, segmentLeft, segmentRight) =>
float leftVal = array.get(linesArr, segmentLeft)
float rightVal = array.get(linesArr, segmentRight)
int segmentLen = segmentRight - segmentLeft
if segmentLen > 1
for i = segmentLeft + 1 to segmentRight - 1
float ratio = (i - segmentLeft) / segmentLen
float interpVal = leftVal + (rightVal - leftVal) * ratio
array.set(linesArr, i, interpVal)
// reInterpolateAllSegments(...):
// For the entire “linesArr,” re-interpolate each subrange between
// consecutive breakpoints in `lineBreaksArr`.
// This ensures the line is globally correct after each new anchor insertion.
reInterpolateAllSegments(linesArr, lineBreaksArr) =>
array.sort(lineBreaksArr, order.asc)
for i = 0 to array.size(lineBreaksArr) - 2
int leftEdge = array.get(lineBreaksArr, i)
int rightEdge = array.get(lineBreaksArr, i + 1)
reInterpSubrange(linesArr, leftEdge, rightEdge)
// getMaxDistanceIndex(...):
// Return the index (bar) that is farthest from the current “linesArr.”
// We skip any indices already in `lineBreaksArr`.
getMaxDistanceIndex(linesArr, closeArr, lineBreaksArr) =>
float maxDist = -1.0
int maxIdx = -1
int sizeData = array.size(linesArr)
for i = 1 to sizeData - 2
bool isBreak = false
for b = 0 to array.size(lineBreaksArr) - 1
if i == array.get(lineBreaksArr, b)
isBreak := true
break
if not isBreak
float dist = math.abs(array.get(linesArr, i) - array.get(closeArr, i))
if dist > maxDist
maxDist := dist
maxIdx := i
maxIdx
// snapAndReinterpolate(...):
// "Snap" a chosen index to its actual close price, then re-interpolate the entire line again.
snapAndReinterpolate(linesArr, closeArr, lineBreaksArr, idxToSnap) =>
if idxToSnap >= 0
float snapVal = array.get(closeArr, idxToSnap)
array.set(linesArr, idxToSnap, snapVal)
reInterpolateAllSegments(linesArr, lineBreaksArr)
// 3. Global Arrays and Flags
// ---------------------------------------------------------------------
// We store final data globally, then use them outside the barstate.islast scope to draw lines.
var float finalCloseData = array.new_float()
var float finalLines = array.new_float()
var int finalLineBreaks = array.new_int()
var bool didCompute = false
var line pipLines = array.new_line()
// 4. Main Logic (Runs Once at the End of the Current Bar)
// ---------------------------------------------------------------------
if barstate.islast
// A) Prepare closeData in forward order (index 0 = oldest bar, index length-1 = newest)
float closeData = array.new_float()
for i = 0 to length - 1
array.push(closeData, close )
// B) Initialize linesArr with a simple linear interpolation from the first to the last point
float linesArr = array.new_float()
float firstClose = array.get(closeData, 0)
float lastClose = array.get(closeData, length - 1)
for i = 0 to length - 1
float ratio = (length > 1) ? (i / float(length - 1)) : 0.0
float val = firstClose + (lastClose - firstClose) * ratio
array.push(linesArr, val)
// C) Initialize lineBreaks with two anchors: 0 (oldest) and length-1 (newest)
int lineBreaks = array.new_int()
array.push(lineBreaks, 0)
array.push(lineBreaks, length - 1)
// D) Iteratively insert new breakpoints, always re-interpolating globally
int iterationsNeeded = math.max(num_points - 2, 0)
for _iteration = 1 to iterationsNeeded
// 1) Re-interpolate entire shape, so it's globally up to date
reInterpolateAllSegments(linesArr, lineBreaks)
// 2) Find the bar with the largest vertical distance to this line
int maxDistIdx = getMaxDistanceIndex(linesArr, closeData, lineBreaks)
if maxDistIdx == -1
break
// 3) Insert that bar index into lineBreaks and snap it
array.push(lineBreaks, maxDistIdx)
array.sort(lineBreaks, order.asc)
snapAndReinterpolate(linesArr, closeData, lineBreaks, maxDistIdx)
// E) Save results into global arrays for line drawing outside barstate.islast
array.clear(finalCloseData)
array.clear(finalLines)
array.clear(finalLineBreaks)
for i = 0 to array.size(closeData) - 1
array.push(finalCloseData, array.get(closeData, i))
array.push(finalLines, array.get(linesArr, i))
for b = 0 to array.size(lineBreaks) - 1
array.push(finalLineBreaks, array.get(lineBreaks, b))
didCompute := true
// 5. Drawing the Lines in Global Scope
// ---------------------------------------------------------------------
// We cannot create lines inside barstate.islast, so we do it outside.
array.clear(pipLines)
if didCompute
// Connect each pair of anchors with red lines
if array.size(finalLineBreaks) > 1
for i = 0 to array.size(finalLineBreaks) - 2
int idxLeft = array.get(finalLineBreaks, i)
int idxRight = array.get(finalLineBreaks, i + 1)
float x1 = bar_index - (length - 1) + idxLeft
float x2 = bar_index - (length - 1) + idxRight
float y1 = array.get(finalCloseData, idxLeft)
float y2 = array.get(finalCloseData, idxRight)
line ln = line.new(x1, y1, x2, y2, extend=extend.none)
line.set_color(ln, color.red)
line.set_width(ln, 2)
array.push(pipLines, ln)
1. **Data Collection**
- We collect the **most recent** `length` bars in `closeData`. Index 0 is the oldest bar in that window, index `length-1` is the newest bar.
2. **Initial Straight Line**
- We create an array called `linesArr` that starts as a simple linear interpolation from `closeData ` (the oldest bar’s close) to `closeData ` (the newest bar’s close).
3. **Line Breaks**
- We store “anchor points” in `lineBreaks`, initially ` `. These are the start and end of our segment.
4. **Global Re-Interpolation**
- Each time we want to add a new anchor, we **re-draw** (linear interpolation) for *every* subrange ` [lineBreaks , lineBreaks ]`, ensuring we have a globally consistent line.
- This avoids the “local subrange only” approach, which can cause clustering near existing anchors.
5. **Finding the Largest Distance**
- After re-drawing, we compute the vertical distance for each bar `i` that isn’t already a line break. The bar with the biggest distance from the line is chosen as the next anchor (`maxDistIdx`).
6. **Snapping and Re-Interpolate**
- We “snap” that bar’s line value to the actual close, i.e. `linesArr = closeData `. Then we globally re-draw all segments again.
7. **Repeat**
- We repeat these insertions until we have the desired number of points (`num_points`).
8. **Drawing**
- Finally, we connect each consecutive pair of anchor points (`lineBreaks`) with a `line.new(...)` call, coloring them red.
- We offset the line’s `x` coordinate so that the anchor at index 0 lines up with `bar_index - (length - 1)`, and the anchor at index `length-1` lines up with `bar_index` (the current bar).
**Result**:
You get a simplified representation of the price with a small set of line segments capturing the largest “jumps” or swings. By re-drawing the entire line after each insertion, the anchors tend to distribute more *evenly* across the data, mitigating the issue where anchors bunch up near each other.
Enjoy experimenting with different `length` and `num_points` to see how the simplified lines change!
Han Algo - Moving average strategyHan Algo Indicator Strategy Description
Overview:
The Han Algo Indicator is designed to identify trend directions and signal potential buy and sell opportunities based on moving average crossovers. It aims to provide clear signals while filtering out noise and minimizing false signals.
Indicators Used:
Moving Averages:
200 SMA (Simple Moving Average): Used as a long-term trend indicator.
100 SMA: Provides a medium-term perspective on price movements.
50 SMA: Offers insights into shorter-term trends.
20 SMA: Provides a very short-term perspective on recent price actions.
Trend Identification:
The indicator identifies the trend based on the relationship between the closing price (close) and the 200 SMA (ma_long):
Uptrend: When the closing price is above the 200 SMA.
Downtrend: When the closing price is below the 200 SMA.
Sideways: When the closing price is equal to the 200 SMA.
Buy and Sell Signals:
Buy Signal: Generated when transitioning from a downtrend to an uptrend (buy_condition):
Displayed as a green "BUY" label above the price bar.
Sell Signal: Generated when transitioning from an uptrend to a downtrend (sell_condition):
Displayed as a red "SELL" label below the price bar.
Signal Filtering:
Signals are filtered to prevent consecutive signals occurring too closely (min_distance_bars parameter):
Ensures that only significant trend reversals are captured, minimizing false signals.
Visualization:
Background Color:
Changes to green for uptrend and red for downtrend (bgcolor function):
Provides visual cues for current market sentiment.
Usage:
Traders can customize the indicator's parameters (long_term_length, medium_term_length, short_term_length, very_short_term_length, min_distance_bars) to align with their trading preferences and timeframes.
The Han Algo Indicator helps traders make informed decisions by highlighting potential trend reversals and aligning with market trends identified through moving average analysis.
Disclaimer:
This indicator is intended for educational purposes and as a visual aid to support trading decisions. It should be used in conjunction with other technical analysis tools and risk management strategies.
Rocket Grid Algorithm - The Quant ScienceThe Rocket Grid Algorithm is a trading strategy that enables traders to engage in both long and short selling strategies. The script allows traders to backtest their strategies with a date range of their choice, in addition to selecting the desired strategy - either SMA Based Crossunder or SMA Based Crossover.
The script is a combination of trend following and short-term mean reversing strategies. Trend following involves identifying the current market trend and riding it for as long as possible until it changes direction. This type of strategy can be used over a medium- to long-term time horizon, typically several months to a few years.
Short-term mean reversing, on the other hand, involves taking advantage of short-term price movements that deviate from the average price. This type of strategy is usually applied over a much shorter time horizon, such as a few days to a few weeks. By rapidly entering and exiting positions, the strategy seeks to capture small, quick gains in volatile market conditions.
Overall, the script blends the best of both worlds by combining the long-term stability of trend following with the quick gains of short-term mean reversing, allowing traders to potentially benefit from both short-term and long-term market trends.
Traders can configure the start and end dates, months, and years, and choose the length of the data they want to work with. Additionally, they can set the percentage grid and the upper and lower destroyers to manage their trades effectively. The script also calculates the Simple Moving Average of the chosen data length and plots it on the chart.
The trigger for entering a trade is defined as a crossunder or crossover of the close price with the Simple Moving Average. Once the trigger is activated, the script calculates the total percentage of the side and creates a grid range. The grid range is then divided into ten equal parts, with each part representing a unique grid level. The script keeps track of each grid level, and once the close price reaches the grid level, it opens a trade in the specified direction.
The equity management strategy in the script involves a dynamic allocation of equity to each trade. The first order placed uses 10% of the available equity, while each subsequent order uses 1% less of the available equity. This results in the allocation of 9% for the second order, 8% for the third order, and so on, until a maximum of 10 open trades. This approach allows for risk management and can help to limit potential losses.
Overall, the Rocket Grid Algorithm is a flexible and powerful trading strategy that can be customized to meet the specific needs of individual traders. Its user-friendly interface and robust backtesting capabilities make it an excellent tool for traders looking to enhance their trading experience.
tvbot Trend Following with Mean Reversion algoDefault settings are for the ETHUSDT 5 min Binance Chart regular candles.
Back test Default settings are 10,000 usd to start, Commission 0.075%, capital deployment per position is 10%, slippage value of 1.
This algo uses the EMA to set the trend line . You are also able to turn the trend line into a range instead of just a static line. The algo uses the VWMA to set the base entry parameters. When a candle closes above or below the VWMA it will record that price and then wait for the VWMA to meet the candle close price. When that happens the Base entry condition is met. (it causes the vwma to create a hook like structure. essentially tell you that the momentum has changed directions.)
The algo will always check to see if the trend line has either breached or has been tested and held. If this condition has been met it will then go to the base entry condition to check to see if the momentum has changed.
There is a mean reversion component in this algo as well. When the price has moved away from the mean(set by user) by a certain amount the algo will start to look for a top or bottom. Once that condition has been met it will then use the base entry condition to look for a change in momentum, but the mean reversion base entry condition uses the HMA to check for a change in momentum.
This algo effectively looks like a hamburger. Mean reversion being the tops and bottoms(bun) and the trend following(beef patty)
[Fedra Algotrading LR + TTP Indicator Lite]How it works?
- It calculates the linear regression of the last X candles and define a range based on a linear regression deviation (represented by the 3 parallel lines over the last candle).
-Open trades based on the breakout of the deviation of the linear regression (represented by the yellow triangle).
-Advanced trend filter to not open trades against the trend consist in 2 SMA cross and and a few other conditions, including sptionally super trend (Represented by the red and green background).
-Percentage take profit (represented by the horizontal green line. configurable)
-Percentage stop loss (represented by the horizontal red line. Configurable
-Break even when a trade has already opened and there is a change of trend. Calculated in 1.5% when the price is under the yellow SMA.
Alerts in each case to receive notifications (BUY & SELL, TP BE SL).
Added labels with entry price and PnL of each closed trade to facilitate optimization
Daily Algo LevelsQuickly plot stoo's algo levels. Gives option to expand range based on algo error formula. Gives option to display suggested entry points.
FUNCTION: Goertzel algorithm -- DFT of a specific frequency binThis function implements the Goertzel algorithm (for integer N).
The Goertzel algorithm is a technique in digital signal processing (DSP) for efficient evaluation of the individual terms of the discrete Fourier transform (DFT).
In short, it measure the power of a specific frequency like one bin of a DFT, over a rolling window (N) of samples.
Here you see an input signal that changes frequency and amplitude (from 7 bars to 17). I am running the indicator 3 times to show it measuring both frequencies and one in between (13). You can see it very accurately measures the signals present and their power, but is noisy in the transition. Changing the block len will cause it to be more responsive but noisier.
Here is a picture of the same signal, but with white noise added.
If you have a cycle you think is present you could use this to test it, but the function is designed for integration in to more complicated scripts. I think power is best interrupted on a log scale.
Given a period (in bars or samples) and a block_len (N in Goertzel terminology) the function returns the Real (InPhase) and Quadrature (Imaginary) components of your signal as well as calculating the power and the instantaneous angle (in radians).
I hope this proves useful to the DSP folks here.
Patient Trendfollower (7)(alpha) Backtesting AlgorithmThis is an alpha version of backtesting algorithm for my Patient Trendfollower (7) strategy. It can help you adapt the indicator to other charts than EURUSD. Please bear in mind that price action, volume profiles and supzistences are a catalyst for successful trading, not an indicator. You can get significantly better results if you use these things in your trading and use Trendfollower only as a secondary tool.
Patient Trendfollower Indicator
Thanks belongs to @everget and Satik FX, their contributions are highlighted on an indicator page.
